different types of studies in research

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Types of Research – Explained with Examples

• By DiscoverPhDs
• October 2, 2020

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

• Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
• Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

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Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental . 

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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10 Comments

Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

how can I put this blog as my reference(APA style) in bibliography part?

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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
• Text Mining and Computational Text Analysis
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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
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• Last Updated: Apr 25, 2024 11:09 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

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Study designs

This short article gives a brief guide to the different study types and a comparison of the advantages and disadvantages.

See also  Levels of Evidence  

These study designs all have similar components (as we’d expect from the PICO):

• A defined population (P) from which groups of subjects are studied
• Outcomes (O) that are measured

And for experimental and analytic observational studies:

• Interventions (I) or exposures (E) that are applied to different groups of subjects

Overview of the design tree

Figure 1 shows the tree of possible designs, branching into subgroups of study designs by whether the studies are descriptive or analytic and by whether the analytic studies are experimental or observational. The list is not completely exhaustive but covers most basics designs.

Figure: Tree of different types of studies (Q1, 2, and 3 refer to the three questions below)

> Download a PDF by Jeremy Howick about study designs

Our first distinction is whether the study is analytic or non-analytic. A  non-analytic  or  descriptive  study does not try to quantify the relationship but tries to give us a picture of what is happening in a population, e.g., the prevalence, incidence, or experience of a group. Descriptive studies include case reports, case-series, qualitative studies and surveys (cross-sectional) studies, which measure the frequency of several factors, and hence the size of the problem. They may sometimes also include analytic work (comparing factors “” see below).

An  analytic  study attempts to quantify the relationship between two factors, that is, the effect of an intervention (I) or exposure (E) on an outcome (O). To quantify the effect we will need to know the rate of outcomes in a comparison (C) group as well as the intervention or exposed group. Whether the researcher actively changes a factor or imposes uses an intervention determines whether the study is considered to be observational (passive involvement of researcher), or experimental (active involvement of researcher).

In  experimental  studies, the researcher manipulates the exposure, that is he or she allocates subjects to the intervention or exposure group. Experimental studies, or randomised controlled trials (RCTs), are similar to experiments in other areas of science. That is, subjects are allocated to two or more groups to receive an intervention or exposure and then followed up under carefully controlled conditions. Such studies controlled trials, particularly if randomised and blinded, have the potential to control for most of the biases that can occur in scientific studies but whether this actually occurs depends on the quality of the study design and implementation.

In  analytic observational  studies, the researcher simply measures the exposure or treatments of the groups. Analytical observational studies include case””control studies, cohort studies and some population (cross-sectional) studies. These studies all include matched groups of subjects and assess of associations between exposures and outcomes.

Observational studies investigate and record exposures (such as interventions or risk factors) and observe outcomes (such as disease) as they occur. Such studies may be purely descriptive or more analytical.

We should finally note that studies can incorporate several design elements. For example, a the control arm of a randomised trial may also be used as a cohort study; and the baseline measures of a cohort study may be used as a cross-sectional study.

Spotting the study design

The type of study can generally be worked at by looking at three issues (as per the Tree of design in Figure 1):

Q1. What was the aim of the study?

• To simply describe a population (PO questions) descriptive
• To quantify the relationship between factors (PICO questions) analytic.

Q2. If analytic, was the intervention randomly allocated?

• No? Observational study

For observational study the main types will then depend on the timing of the measurement of outcome, so our third question is:

Q3. When were the outcomes determined?

• Some time after the exposure or intervention? cohort study (‘prospective study’)
• At the same time as the exposure or intervention? cross sectional study or survey
• Before the exposure was determined? case-control study (‘retrospective study’ based on recall of the exposure)

Advantages and Disadvantages of the Designs

Randomised Controlled Trial

An experimental comparison study in which participants are allocated to treatment/intervention or control/placebo groups using a random mechanism (see randomisation). Best for study the effect of an intervention.

Advantages:

• unbiased distribution of confounders;
• blinding more likely;
• randomisation facilitates statistical analysis.

Disadvantages:

• expensive: time and money;
• volunteer bias;
• ethically problematic at times.

Crossover Design

A controlled trial where each study participant has both therapies, e.g, is randomised to treatment A first, at the crossover point they then start treatment B. Only relevant if the outcome is reversible with time, e.g, symptoms.

• all subjects serve as own controls and error variance is reduced thus reducing sample size needed;
• all subjects receive treatment (at least some of the time);
• statistical tests assuming randomisation can be used;
• blinding can be maintained.
• all subjects receive placebo or alternative treatment at some point;
• washout period lengthy or unknown;
• cannot be used for treatments with permanent effects

Cohort Study

Data are obtained from groups who have been exposed, or not exposed, to the new technology or factor of interest (eg from databases). No allocation of exposure is made by the researcher. Best for study the effect of predictive risk factors on an outcome.

• ethically safe;
• subjects can be matched;
• can establish timing and directionality of events;
• eligibility criteria and outcome assessments can be standardised;
• administratively easier and cheaper than RCT.
• controls may be difficult to identify;
• exposure may be linked to a hidden confounder;
• blinding is difficult;
• randomisation not present;
• for rare disease, large sample sizes or long follow-up necessary.

Case-Control Studies

Patients with a certain outcome or disease and an appropriate group of controls without the outcome or disease are selected (usually with careful consideration of appropriate choice of controls, matching, etc) and then information is obtained on whether the subjects have been exposed to the factor under investigation.

• quick and cheap;
• only feasible method for very rare disorders or those with long lag between exposure and outcome;
• fewer subjects needed than cross-sectional studies.
• reliance on recall or records to determine exposure status;
• confounders;
• selection of control groups is difficult;
• potential bias: recall, selection.

Cross-Sectional Survey

A study that examines the relationship between diseases (or other health-related characteristics) and other variables of interest as they exist in a defined population at one particular time (ie exposure and outcomes are both measured at the same time). Best for quantifying the prevalence of a disease or risk factor, and for quantifying the accuracy of a diagnostic test.

• cheap and simple;
• ethically safe.
• establishes association at most, not causality;
• recall bias susceptibility;
• confounders may be unequally distributed;
• Neyman bias;
• group sizes may be unequal.

Public Health Doctoral Studies (PhD and DrPH): Types of Studies

• Searching the Literature
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Study Definitions

Meta-Analysis

A quantitative method of combining the results of independent studies, which are drawn from the published literature, and synthesizing summaries and conclusions.

Systematic Review

A review which endeavors to consider all published and unpublished material on a specific question.  Studies that are judged methodologically sound are then combined quantitatively or qualitatively depending on their similarity.

Randomized Control Trial (RCT)

A  clinical trial involving one or more new treatments and at least one control treatment with specified outcome measures for evaluating the intervention.  The treatment may be a drug, device, or procedure. Controls are either placebo or an active treatment that is currently considered the "gold standard".  If patients are randomized via mathmatical techniques then the trial is designated as a randomized controlled trial.

Cohort Study

In cohort studies, groups of individuals, who are initially free of disease, are classified according to exposure or non-exposure to a risk factor and followed over time to determine the incidence of an outcome of interest.  In a prospective cohort study, the exposure information for the study subjects is collected at the start of the study and the new cases of disease are identified from that point on.  In a retrospective cohort study, the exposure status was measured in the past and disease identification has already begun. 

Case-Control Study

Studies that start by identifying persons with and without a disease of interest (cases and controls, respectively) and then look back in time to find differences in exposure to risk factors. 

Cross-Sectional Study

Studies in which the presence or absence of disease or other health-related variables are determined in each member of a population at one particular time. 

Levels of Evidence Pyramid

Levels of Evidence Pyramid created by Andy Puro, September 2014

Experimental vs. Observational Studies

An observational study is a study in which the investigator cannot control the assignment of treatment to subjects because the participants or conditions are not being directly assigned by the researcher.

• Examines predetermined treatments, interventions, policies, and their effects
• Four main types: case-series , case-control , cross-sectional , and cohort studies

In an experimental study , the investigators directly manipulate or assign participants to different interventions or environments.

• Controlled trials - studies in which the experimental drug or procedure is compared with another drug or procedure
• Uncontrolled trials - studies in which the investigators' experience with the experimental drug or procedure is described, but the treatment is not compared with another treatment

Formal Trials versus Observational Studies (Ravi Thadhani, Harvard Medical School)

Study Designs (Centre for Evidence Based Medicine, University of Oxford)

Learn about Clinical Studies (ClinicalTrials.gov, National Institutes of Health)

Definitions taken from: Dawson B, Trapp R.G. (2004). Chapter 2. Study Designs in Medical Research. In Dawson B, Trapp R.G. (Eds), Basic & Clinical Biostatistics, 4e Retrieved September 15, 2014 from http://accessmedicine.mhmedical.com/content.aspx?bookid=356&Sectionid=40086281.

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An introduction to different types of study design

Posted on 6th April 2021 by Hadi Abbas

Study designs are the set of methods and procedures used to collect and analyze data in a study.

Broadly speaking, there are 2 types of study designs: descriptive studies and analytical studies.

Descriptive studies

• Describes specific characteristics in a population of interest
• The most common forms are case reports and case series
• In a case report, we discuss our experience with the patient’s symptoms, signs, diagnosis, and treatment
• In a case series, several patients with similar experiences are grouped.

Analytical Studies

Analytical studies are of 2 types: observational and experimental.

Observational studies are studies that we conduct without any intervention or experiment. In those studies, we purely observe the outcomes.  On the other hand, in experimental studies, we conduct experiments and interventions.

Observational studies

Observational studies include many subtypes. Below, I will discuss the most common designs.

Cross-sectional study:

• This design is transverse where we take a specific sample at a specific time without any follow-up
• It allows us to calculate the frequency of disease ( p revalence ) or the frequency of a risk factor
• This design is easy to conduct
• For example – if we want to know the prevalence of migraine in a population, we can conduct a cross-sectional study whereby we take a sample from the population and calculate the number of patients with migraine headaches.

Cohort study:

• We conduct this study by comparing two samples from the population: one sample with a risk factor while the other lacks this risk factor
• It shows us the risk of developing the disease in individuals with the risk factor compared to those without the risk factor ( RR = relative risk )
• Prospective : we follow the individuals in the future to know who will develop the disease
• Retrospective : we look to the past to know who developed the disease (e.g. using medical records)
• This design is the strongest among the observational studies
• For example – to find out the relative risk of developing chronic obstructive pulmonary disease (COPD) among smokers, we take a sample including smokers and non-smokers. Then, we calculate the number of individuals with COPD among both.

Case-Control Study:

• We conduct this study by comparing 2 groups: one group with the disease (cases) and another group without the disease (controls)
• This design is always retrospective
•  We aim to find out the odds of having a risk factor or an exposure if an individual has a specific disease (Odds ratio)
•  Relatively easy to conduct
• For example – we want to study the odds of being a smoker among hypertensive patients compared to normotensive ones. To do so, we choose a group of patients diagnosed with hypertension and another group that serves as the control (normal blood pressure). Then we study their smoking history to find out if there is a correlation.

Experimental Studies

• Also known as interventional studies
• Can involve animals and humans
• Pre-clinical trials involve animals
• Clinical trials are experimental studies involving humans
• In clinical trials, we study the effect of an intervention compared to another intervention or placebo. As an example, I have listed the four phases of a drug trial:

I:  We aim to assess the safety of the drug ( is it safe ? )

II: We aim to assess the efficacy of the drug ( does it work ? )

III: We want to know if this drug is better than the old treatment ( is it better ? )

IV: We follow-up to detect long-term side effects ( can it stay in the market ? )

• In randomized controlled trials, one group of participants receives the control, while the other receives the tested drug/intervention. Those studies are the best way to evaluate the efficacy of a treatment.

Finally, the figure below will help you with your understanding of different types of study designs.

References (pdf)

You may also be interested in the following blogs for further reading:

An introduction to randomized controlled trials

Case-control and cohort studies: a brief overview

Cohort studies: prospective and retrospective designs

Prevalence vs Incidence: what is the difference?

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No Comments on An introduction to different types of study design

you are amazing one!! if I get you I’m working with you! I’m student from Ethiopian higher education. health sciences student

Very informative and easy understandable

You are my kind of doctor. Do not lose sight of your objective.

Wow very erll explained and easy to understand

I’m Khamisu Habibu community health officer student from Abubakar Tafawa Balewa university teaching hospital Bauchi, Nigeria, I really appreciate your write up and you have make it clear for the learner. thank you

well understood,thank you so much

Well understood…thanks

Simply explained. Thank You.

Thanks a lot for this nice informative article which help me to understand different study designs that I felt difficult before

That’s lovely to hear, Mona, thank you for letting the author know how useful this was. If there are any other particular topics you think would be useful to you, and are not already on the website, please do let us know.

it is very informative and useful.

thank you statistician

Fabulous to hear, thank you John.

Thanks for this information

Thanks so much for this information….I have clearly known the types of study design Thanks

That’s so good to hear, Mirembe, thank you for letting the author know.

Very helpful article!! U have simplified everything for easy understanding

I’m a health science major currently taking statistics for health care workers…this is a challenging class…thanks for the simified feedback.

That’s good to hear this has helped you. Hopefully you will find some of the other blogs useful too. If you see any topics that are missing from the website, please do let us know!

Hello. I liked your presentation, the fact that you ranked them clearly is very helpful to understand for people like me who is a novelist researcher. However, I was expecting to read much more about the Experimental studies. So please direct me if you already have or will one day. Thank you

Dear Ay. My sincere apologies for not responding to your comment sooner. You may find it useful to filter the blogs by the topic of ‘Study design and research methods’ – here is a link to that filter: https://s4be.cochrane.org/blog/topic/study-design/ This will cover more detail about experimental studies. Or have a look on our library page for further resources there – you’ll find that on the ‘Resources’ drop down from the home page.

However, if there are specific things you feel you would like to learn about experimental studies, that are missing from the website, it would be great if you could let me know too. Thank you, and best of luck. Emma

Great job Mr Hadi. I advise you to prepare and study for the Australian Medical Board Exams as soon as you finish your undergrad study in Lebanon. Good luck and hope we can meet sometime in the future. Regards ;)

You have give a good explaination of what am looking for. However, references am not sure of where to get them from.

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Types of Research Studies and How To Interpret Them

The field of nutrition is dynamic, and our understanding and practices are always evolving. Nutrition scientists are continuously conducting new research and publishing their findings in peer-reviewed journals. This adds to scientific knowledge, but it’s also of great interest to the public, so nutrition research often shows up in the news and other media sources. You might be interested in nutrition research to inform your own eating habits, or if you work in a health profession, so that you can give evidence-based advice to others. Making sense of science requires that you understand the types of research studies used and their limitations.

The Hierarchy of Nutrition Evidence

Researchers use many different types of study designs depending on the question they are trying to answer, as well as factors such as time, funding, and ethical considerations. The study design affects how we interpret the results and the strength of the evidence as it relates to real-life nutrition decisions. It can be helpful to think about the types of studies within a pyramid representing a hierarchy of evidence, where the studies at the bottom of the pyramid usually give us the weakest evidence with the least relevance to real-life nutrition decisions, and the studies at the top offer the strongest evidence, with the most relevance to real-life nutrition decisions .

Figure 2.3. The hierarchy of evidence shows types of research studies relative to their strength of evidence and relevance to real-life nutrition decisions, with the strongest studies at the top and the weakest at the bottom.

The pyramid also represents a few other general ideas. There tend to be more studies published using the methods at the bottom of the pyramid, because they require less time, money, and other resources. When researchers want to test a new hypothesis , they often start with the study designs at the bottom of the pyramid , such as in vitro, animal, or observational studies. Intervention studies are more expensive and resource-intensive, so there are fewer of these types of studies conducted. But they also give us higher quality evidence, so they’re an important next step if observational and non-human studies have shown promising results. Meta-analyses and systematic reviews combine the results of many studies already conducted, so they help researchers summarize scientific knowledge on a topic.

Non-Human Studies: In Vitro & Animal Studies

The simplest form of nutrition research is an in vitro study . In vitro means “within glass,” (although plastic is used more commonly today) and these experiments are conducted within flasks, dishes, plates, and test tubes. These studies are performed on isolated cells or tissue samples, so they’re less expensive and time-intensive than animal or human studies. In vitro studies are vital for zooming in on biological mechanisms, to see how things work at the cellular or molecular level. However, these studies shouldn’t be used to draw conclusions about how things work in humans (or even animals), because we can’t assume that the results will apply to a whole, living organism.

Animal studies are one form of  in vivo research, which translates to “within the living.” Rats and mice are the most common animals used in nutrition research. Animals are often used in research that would be unethical to conduct in humans. Another advantage of animal dietary studies is that researchers can control exactly what the animals eat. In human studies, researchers can tell subjects what to eat and even provide them with the food, but they may not stick to the planned diet. People are also not very good at estimating, recording, or reporting what they eat and in what quantities. In addition, animal studies typically do not cost as much as human studies.

There are some important limitations of animal research. First, an animal’s metabolism and physiology are different from humans. Plus, animal models of disease (cancer, cardiovascular disease, etc.), although similar, are different from human diseases. Animal research is considered preliminary, and while it can be very important to the process of building scientific understanding and informing the types of studies that should be conducted in humans, animal studies shouldn’t be considered relevant to real-life decisions about how people eat.

Observational Studies

Observational studies in human nutrition collect information on people’s dietary patterns or nutrient intake and look for associations with health outcomes. Observational studies do not give participants a treatment or intervention; instead, they look at what they’re already doing and see how it relates to their health. These types of study designs can only identify correlations (relationships) between nutrition and health; they can’t show that one factor causes another. (For that, we need intervention studies, which we’ll discuss in a moment.) Observational studies that describe factors correlated with human health are also called epidemiological studies . 1

One example of a nutrition hypothesis that has been investigated using observational studies is that eating a Mediterranean diet reduces the risk of developing cardiovascular disease. (A Mediterranean diet focuses on whole grains, fruits and vegetables, beans and other legumes, nuts, olive oil, herbs, and spices. It includes small amounts of animal protein (mostly fish), dairy, and red wine. 2 ) There are three main types of observational studies, all of which could be used to test hypotheses about the Mediterranean diet:

• Cohort studies follow a group of people (a cohort) over time, measuring factors such as diet and health outcomes. A cohort study of the Mediterranean diet would ask a group of people to describe their diet, and then researchers would track them over time to see if those eating a Mediterranean diet had a lower incidence of cardiovascular disease.
• Case-control studies compare a group of cases and controls, looking for differences between the two groups that might explain their different health outcomes. For example, researchers might compare a group of people with cardiovascular disease with a group of healthy controls to see whether there were more controls or cases that followed a Mediterranean diet.
• Cross-sectional studies collect information about a population of people at one point in time. For example, a cross-sectional study might compare the dietary patterns of people from different countries to see if diet correlates with the prevalence of cardiovascular disease in the different countries.

Prospective cohort studies, which enroll a cohort and follow them into the future, are usually considered the strongest type of observational study design. Retrospective studies look at what happened in the past, and they’re considered weaker because they rely on people’s memory of what they ate or how they felt in the past. There are several well-known examples of prospective cohort studies that have described important correlations between diet and disease:

• Framingham Heart Study : Beginning in 1948, this study has followed the residents of Framingham, Massachusetts to identify risk factors for heart disease.
• Health Professionals Follow-Up Study : This study started in 1986 and enrolled 51,529 male health professionals (dentists, pharmacists, optometrists, osteopathic physicians, podiatrists, and veterinarians), who complete diet questionnaires every 2 years.
• Nurses Health Studies : Beginning in 1976, these studies have enrolled three large cohorts of nurses with a total of 280,000 participants. Participants have completed detailed questionnaires about diet, other lifestyle factors (smoking and exercise, for example), and health outcomes.

Observational studies have the advantage of allowing researchers to study large groups of people in the real world, looking at the frequency and pattern of health outcomes and identifying factors that correlate with them. But even very large observational studies may not apply to the population as a whole. For example, the Health Professionals Follow-Up Study and the Nurses Health Studies include people with above-average knowledge of health. In many ways, this makes them ideal study subjects, because they may be more motivated to be part of the study and to fill out detailed questionnaires for years. However, the findings of these studies may not apply to people with less baseline knowledge of health.

We’ve already mentioned another important limitation of observational studies—that they can only determine correlation, not causation. A prospective cohort study that finds that people eating a Mediterranean diet have a lower incidence of heart disease can only show that the Mediterranean diet is correlated with lowered risk of heart disease. It can’t show that the Mediterranean diet directly prevents heart disease. Why? There are a huge number of factors that determine health outcomes such as heart disease, and other factors might explain a correlation found in an observational study. For example, people who eat a Mediterranean diet might also be the same kind of people who exercise more, sleep more, have higher income (fish and nuts can be expensive!), or be less stressed. These are called confounding factors ; they’re factors that can affect the outcome in question (i.e., heart disease) and also vary with the factor being studied (i.e., Mediterranean diet).

Intervention Studies

Intervention studies , also sometimes called experimental studies or clinical trials, include some type of treatment or change imposed by the researcher. Examples of interventions in nutrition research include asking participants to change their diet, take a supplement, or change the time of day that they eat. Unlike observational studies, intervention studies can provide evidence of cause and effect , so they are higher in the hierarchy of evidence pyramid.

The gold standard for intervention studies is the randomized controlled trial (RCT) . In an RCT, study subjects are recruited to participate in the study. They are then randomly assigned into one of at least two groups, one of which is a control group (this is what makes the study controlled ). In an RCT to study the effects of the Mediterranean diet on cardiovascular disease development, researchers might ask the control group to follow a low-fat diet (typically recommended for heart disease prevention) and the intervention group to eat a Mediterrean diet. The study would continue for a defined period of time (usually years to study an outcome like heart disease), at which point the researchers would analyze their data to see if more people in the control or Mediterranean diet had heart attacks or strokes. Because the treatment and control groups were randomly assigned, they should be alike in every other way except for diet, so differences in heart disease could be attributed to the diet. This eliminates the problem of confounding factors found in observational research, and it’s why RCTs can provide evidence of causation, not just correlation.

Imagine for a moment what would happen if the two groups weren’t randomly assigned. What if the researchers let study participants choose which diet they’d like to adopt for the study? They might, for whatever reason, end up with more overweight people who smoke and have high blood pressure in the low-fat diet group, and more people who exercised regularly and had already been eating lots of olive oil and nuts for years in the Mediterranean diet group. If they found that the Mediterranean diet group had fewer heart attacks by the end of the study, they would have no way of knowing if this was because of the diet or because of the underlying differences in the groups. In other words, without randomization, their results would be compromised by confounding factors, with many of the same limitations as observational studies.

In an RCT of a supplement, the control group would receive a placebo —a “fake” treatment that contains no active ingredients, such as a sugar pill. The use of a placebo is necessary in medical research because of a phenomenon known as the placebo effect. The placebo effect results in a beneficial effect because of a subject’s belief in the treatment, even though there is no treatment actually being administered.

For example, imagine an athlete who consumes a sports drink and then runs 100 meters in 11.0 seconds. On a different day, under the exact same conditions, the athlete is given a Super Duper Sports Drink and again runs 100 meters, this time in 10.5 seconds. But what the athlete didn’t know was that the Super Duper Sports Drink was the same as the regular sports drink—it just had a bit of food coloring added. There was nothing different between the drinks, but the athlete believed that the Super Duper Sports Drink was going to help him run faster, so he did. This improvement is due to the placebo effect. Ironically, a study similar to this example was published in 2015, demonstrating the power of the placebo effect on athletic performance. 3

Figure 2.4. An example of the placebo effect

Blinding is a technique to prevent bias in intervention studies. In a study without blinding, the subject and the researchers both know what treatment the subject is receiving. This can lead to bias if the subject or researcher have expectations about the treatment working, so these types of trials are used less frequently. It’s best if a study is double-blind , meaning that neither the researcher nor the subject know what treatment the subject is receiving. It’s relatively simple to double-blind a study where subjects are receiving a placebo or treatment pill, because they could be formulated to look and taste the same. In a single-blind study , either the researcher or the subject knows what treatment they’re receiving, but not both. Studies of diets—such as the Mediterranean diet example—often can’t be double-blinded because the study subjects know whether or not they’re eating a lot of olive oil and nuts. However, the researchers who are checking participants’ blood pressure or evaluating their medical records could be blinded to their treatment group, reducing the chance of bias.

Like all studies, RCTs and other intervention studies do have some limitations. They can be difficult to carry on for long periods of time and require that participants remain compliant with the intervention. They’re also costly and often have smaller sample sizes. Furthermore, it is unethical to study certain interventions. (An example of an unethical intervention would be to advise one group of pregnant mothers to drink alcohol to determine its effects on pregnancy outcomes, because we know that alcohol consumption during pregnancy damages the developing fetus.)

VIDEO: “ Not all scientific studies are created equal ” by David H. Schwartz, YouTube (April 28, 2014), 4:26.

Meta-Analyses and Systematic Reviews

At the top of the hierarchy of evidence pyramid are systematic reviews and meta-analyses . You can think of these as “studies of studies.” They attempt to combine all of the relevant studies that have been conducted on a research question and summarize their overall conclusions. Researchers conducting a systematic review formulate a research question and then systematically and independently identify, select, evaluate, and synthesize all high-quality evidence that relates to the research question. Since systematic reviews combine the results of many studies, they help researchers produce more reliable findings. A meta-analysis is a type of systematic review that goes one step further, combining the data from multiple studies and using statistics to summarize it, as if creating a mega-study from many smaller studies . 4

However, even systematic reviews and meta-analyses aren’t the final word on scientific questions. For one thing, they’re only as good as the studies that they include. The Cochrane Collaboration is an international consortium of researchers who conduct systematic reviews in order to inform evidence-based healthcare, including nutrition, and their reviews are among the most well-regarded and rigorous in science. For the most recent Cochrane review of the Mediterranean diet and cardiovascular disease, two authors independently reviewed studies published on this question. Based on their inclusion criteria, 30 RCTs with a total of 12,461 participants were included in the final analysis. However, after evaluating and combining the data, the authors concluded that “despite the large number of included trials, there is still uncertainty regarding the effects of a Mediterranean‐style diet on cardiovascular disease occurrence and risk factors in people both with and without cardiovascular disease already.” Part of the reason for this uncertainty is that different trials found different results, and the quality of the studies was low to moderate. Some had problems with their randomization procedures, for example, and others were judged to have unreliable data. That doesn’t make them useless, but it adds to the uncertainty about this question, and uncertainty pushes the field forward towards more and better studies. The Cochrane review authors noted that they found seven ongoing trials of the Mediterranean diet, so we can hope that they’ll add more clarity to this question in the future. 5

Science is an ongoing process. It’s often a slow process, and it contains a lot of uncertainty, but it’s our best method of building knowledge of how the world and human life works. Many different types of studies can contribute to scientific knowledge. None are perfect—all have limitations—and a single study is never the final word on a scientific question. Part of what advances science is that researchers are constantly checking each other’s work, asking how it can be improved and what new questions it raises.

Self-Check:

Attributions:

• “Chapter 1: The Basics” from Lindshield, B. L. Kansas State University Human Nutrition (FNDH 400) Flexbook. goo.gl/vOAnR , CC BY-NC-SA 4.0
• “ The Broad Role of Nutritional Science ,” section 1.3 from the book An Introduction to Nutrition (v. 1.0), CC BY-NC-SA 3.0

References:

• 1 Thiese, M. S. (2014). Observational and interventional study design types; an overview. Biochemia Medica , 24 (2), 199–210. https://doi.org/10.11613/BM.2014.022
• 2 Harvard T.H. Chan School of Public Health. (2018, January 16). Diet Review: Mediterranean Diet . The Nutrition Source. https://www.hsph.harvard.edu/nutritionsource/healthy-weight/diet-reviews/mediterranean-diet/
• 3 Ross, R., Gray, C. M., & Gill, J. M. R. (2015). Effects of an Injected Placebo on Endurance Running Performance. Medicine and Science in Sports and Exercise , 47 (8), 1672–1681. https://doi.org/10.1249/MSS.0000000000000584
• 4 Hooper, A. (n.d.). LibGuides: Systematic Review Resources: Systematic Reviews vs Other Types of Reviews . Retrieved February 7, 2020, from //libguides.sph.uth.tmc.edu/c.php?g=543382&p=5370369
• 5 Rees, K., Takeda, A., Martin, N., Ellis, L., Wijesekara, D., Vepa, A., Das, A., Hartley, L., & Stranges, S. (2019). Mediterranean‐style diet for the primary and secondary prevention of cardiovascular disease. Cochrane Database of Systematic Reviews , 3 . https://doi.org/10.1002/14651858.CD009825.pub3
• Figure 2.3. The hierarchy of evidence by Alice Callahan, is licensed under CC BY 4.0
• Research lab photo by National Cancer Institute on Unsplas h ; mouse photo by vaun0815 on Unsplash
• Figure 2.4. “Placebo effect example” by Lindshield, B. L. Kansas State University Human Nutrition (FNDH 400) Flexbook. goo.gl/vOAnR

Experiments that are conducted outside of living organisms, within flasks, dishes, plates, or test tubes.

Research that is conducted in living organisms, such as rats and mice.

In nutrition, research that is conducted by collecting information on people’s dietary patterns or nutrient intake to look for associations with health outcomes. Observational studies do not give participants a treatment or intervention; instead, they look at what they’re already doing and see how it relates to their health.

Relationships between two factors (e.g., nutrition and health).

Research that follows a group of people (a cohort) over time, measuring factors such as diet and health outcomes.

Research that compares a group of cases and controls, looking for differences between the two groups that might explain their different health outcomes.

Research that collects information about a population of people at one point in time.

Looking into the future.

Looking at what happened in the past.

Factors that can affect the outcome in question.

Research that includes some type of treatment or change imposed by the researchers; sometimes called experimental studies or clinical trials.

The gold standard for intervention studies, because the research involves a control group and participants are randomized.

A “fake” treatment that contains no active ingredients, such as a sugar pill.

The beneficial effect that results from a subject's belief in a treatment, not from the treatment itself.

technique to prevent bias in intervention studies, where either the research team, the subject, or both don’t know what treatment the subject is receiving.

Neither the research team nor the subject know what treatment the subject is receiving.

Either the research team or the subject know what treatment is being given, but not both.

Researchers formulate a research question and then systematically and independently identify, select, evaluate, and synthesize all high-quality evidence from previous research that relates to the research question.

A type of systematic review that combines data from multiple studies and uses statistical methods to summarize it, as if creating a mega-study from many smaller studies.

Nutrition: Science and Everyday Application, v. 1.0 Copyright © 2020 by Alice Callahan, PhD; Heather Leonard, MEd, RDN; and Tamberly Powell, MS, RDN is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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1.3: Types of Research Studies and How To Interpret Them

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The field of nutrition is dynamic, and our understanding and practices are always evolving. Nutrition scientists are continuously conducting new research and publishing their findings in peer-reviewed journals. This adds to scientific knowledge, but it’s also of great interest to the public, so nutrition research often shows up in the news and other media sources. You might be interested in nutrition research to inform your own eating habits, or if you work in a health profession, so that you can give evidence-based advice to others. Making sense of science requires that you understand the types of research studies used and their limitations.

The Hierarchy of Nutrition Evidence

Researchers use many different types of study designs depending on the question they are trying to answer, as well as factors such as time, funding, and ethical considerations. The study design affects how we interpret the results and the strength of the evidence as it relates to real-life nutrition decisions. It can be helpful to think about the types of studies within a pyramid representing a hierarchy of evidence, where the studies at the bottom of the pyramid usually give us the weakest evidence with the least relevance to real-life nutrition decisions, and the studies at the top offer the strongest evidence, with the most relevance to real-life nutrition decisions .

Figure 2.1. Hierarchy of research design and levels of scientific evidence with the strongest studies at the top and the weakest at the bottom.

The pyramid also represents a few other general ideas. There tend to be more studies published using the methods at the bottom of the pyramid, because they require less time, money, and other resources. When researchers want to test a new hypothesis , they often start with the study designs at the bottom of the pyramid , such as in vitro, animal, or observational studies. Intervention studies are more expensive and resource-intensive, so there are fewer of these types of studies conducted. But they also give us higher quality evidence, so they’re an important next step if observational and non-human studies have shown promising results. Meta-analyses and systematic reviews combine the results of many studies already conducted, so they help researchers summarize scientific knowledge on a topic.

Non-Human Studies: In Vitro & Animal Studies

The simplest form of nutrition research is an in vitro study . In vitro means “within glass,” (although plastic is used more commonly today) and these experiments are conducted within flasks, dishes, plates, and test tubes. One common form of in vitro research is cell culture. This involves growing cells in flasks and dishes. In order for cells to grow, they need a nutrient source. For cell culture, the nutrient source is referred to as media. Media supplies nutrients to the cells in vitro similarly to how blood performs this function within the body. Most cells adhere to the bottom of the flask and are so small that a microscope is needed to see them. The cells are grown inside an incubator, which is a device that provides the optimal temperature, humidity, and carbon dioxide (CO2CO2) concentrations for cells and microorganisms. By imitating the body's temperature and CO2CO2 levels (37 degrees Celsius, 5% CO2CO2), the incubator allows cells to grow even though they are outside the body.

A limitation of in vitro research compared to in vivo research is that it typically does not take digestion or bioavailability into account. This means that the concentration used might not be physiologically possible (it might be much higher) and that digestion and metabolism of what is being provided to cells may not be taken into account. Cell-based in vitro research is not as complex of a biological system as animals or people that have tissues, organs, etc. working together as well.

Since these studies are performed on isolated cells or tissue samples, they are less expensive and time-intensive than animal or human studies. In vitro studies are vital for zooming in on biological mechanisms, to see how things work at the cellular or molecular level. However, these studies shouldn’t be used to draw conclusions about how things work in humans (or even animals), because we can’t assume that the results will apply to a whole, living organism.

Animal studies are one form of in vivo research, which translates to “within the living.” Rats and mice are the most common animals used in nutrition research. Animals are often used in research that would be unethical to conduct in humans. Another advantage of animal dietary studies is that researchers can control exactly what the animals eat. In human studies, researchers can tell subjects what to eat and even provide them with the food, but they may not stick to the planned diet. People are also not very good at estimating, recording, or reporting what they eat and in what quantities. In addition, animal studies typically do not cost as much as human studies.

There are some important limitations of animal research. First, an animal’s metabolism and physiology are different from humans. Plus, animal models of disease (cancer, cardiovascular disease, etc.), although similar, are different from human diseases. Animal research is considered preliminary, and while it can be very important to the process of building scientific understanding and informing the types of studies that should be conducted in humans, animal studies shouldn’t be considered relevant to real-life decisions about how people eat.

Observational Studies

Observational studies in human nutrition collect information on people’s dietary patterns or nutrient intake and look for associations with health outcomes. Observational studies do not give participants a treatment or intervention; instead, they look at what they’re already doing and see how it relates to their health. These types of study designs can only identify correlations (relationships) between nutrition and health; they can’t show that one factor causes another. (For that, we need intervention studies, which we’ll discuss in a moment.) Observational studies that describe factors correlated with human health are also called epidemiological studies . 1

Epidemiology is defined as the study of human populations. These studies often investigate the relationship between dietary consumption and disease development. There are three main types of epidemiological studies: cross-sectional, case-control, and prospective cohort studies.

One example of a nutrition hypothesis that has been investigated using observational studies is that eating a Mediterranean diet reduces the risk of developing cardiovascular disease. (A Mediterranean diet focuses on whole grains, fruits and vegetables, beans and other legumes, nuts, olive oil, herbs, and spices. It includes small amounts of animal protein (mostly fish), dairy, and red wine. 2 ) There are three main types of observational studies, all of which could be used to test hypotheses about the Mediterranean diet:

• Cohort studies follow a group of people (a cohort) over time, measuring factors such as diet and health outcomes. A cohort study of the Mediterranean diet would ask a group of people to describe their diet, and then researchers would track them over time to see if those eating a Mediterranean diet had a lower incidence of cardiovascular disease.
• Case-control studies compare a group of cases and controls, looking for differences between the two groups that might explain their different health outcomes. For example, researchers might compare a group of people with cardiovascular disease with a group of healthy controls to see whether there were more controls or cases that followed a Mediterranean diet.
• Cross-sectional studies collect information about a population of people at one point in time. For example, a cross-sectional study might compare the dietary patterns of people from different countries to see if diet correlates with the prevalence of cardiovascular disease in the different countries.

There are two types of cohort studies: retrospective and prospective. Retrospective studies look at what happened in the past, and they’re considered weaker because they rely on people’s memory of what they ate or how they felt in the past. Prospective cohort studies, which enroll a cohort and follow them into the future, are usually considered the strongest type of observational study design.

Most cohort studies are prospective. Initial information is collected (usually by food frequency questionnaires) on the intake of a cohort of people at baseline, or the beginning. This cohort is then followed over time (normally many years) to quantify health outcomes of the individual within it. Cohort studies are normally considered to be more robust than case-control studies, because these studies do not start with diseased people and normally do not require people to remember their dietary habits in the distant past or before they developed a disease. An example of a prospective cohort study would be if you filled out a questionnaire on your current dietary habits and are then followed into the future to see if you develop osteoporosis. As shown below, instead of separating based on disease versus disease-free, individuals are separated based on exposure. In this example, those who are exposed are more likely to be diseased than those who were not exposed.

Using trans-fat intake again as the exposure and cardiovascular disease as the disease, the figure would be expected to look like this:

There are several well-known examples of prospective cohort studies that have described important correlations between diet and disease:

• Framingham Heart Study : Beginning in 1948, this study has followed the residents of Framingham, Massachusetts to identify risk factors for heart disease.
• Health Professionals Follow-Up Study : This study started in 1986 and enrolled 51,529 male health professionals (dentists, pharmacists, optometrists, osteopathic physicians, podiatrists, and veterinarians), who complete diet questionnaires every 2 years.
• Nurses Health Studies : Beginning in 1976, these studies have enrolled three large cohorts of nurses with a total of 280,000 participants. Participants have completed detailed questionnaires about diet, other lifestyle factors (smoking and exercise, for example), and health outcomes.

Observational studies have the advantage of allowing researchers to study large groups of people in the real world, looking at the frequency and pattern of health outcomes and identifying factors that correlate with them. But even very large observational studies may not apply to the population as a whole. For example, the Health Professionals Follow-Up Study and the Nurses Health Studies include people with above-average knowledge of health. In many ways, this makes them ideal study subjects, because they may be more motivated to be part of the study and to fill out detailed questionnaires for years. However, the findings of these studies may not apply to people with less baseline knowledge of health.

We’ve already mentioned another important limitation of observational studies—that they can only determine correlation, not causation. A prospective cohort study that finds that people eating a Mediterranean diet have a lower incidence of heart disease can only show that the Mediterranean diet is correlated with lowered risk of heart disease. It can’t show that the Mediterranean diet directly prevents heart disease. Why? There are a huge number of factors that determine health outcomes such as heart disease, and other factors might explain a correlation found in an observational study. For example, people who eat a Mediterranean diet might also be the same kind of people who exercise more, sleep more, have a higher income (fish and nuts can be expensive!), or be less stressed. These are called confounding factors ; they’re factors that can affect the outcome in question (i.e., heart disease) and also vary with the factor being studied (i.e., Mediterranean diet).

Intervention Studies

Intervention studies , also sometimes called experimental studies or clinical trials, include some type of treatment or change imposed by the researcher. Examples of interventions in nutrition research include asking participants to change their diet, take a supplement, or change the time of day that they eat. Unlike observational studies, intervention studies can provide evidence of cause and effect , so they are higher in the hierarchy of evidence pyramid.

Randomization: The gold standard for intervention studies is the randomized controlled trial (RCT) . In an RCT, study subjects are recruited to participate in the study. They are then randomly assigned into one of at least two groups, one of which is a control group (this is what makes the study controlled ).

Randomization is the process of randomly assigning subjects to groups to decrease bias. Bias is a systematic error that may influence results. Bias can occur in assigning subjects to groups in a way that will influence the results. An example of bias in a study of an antidepressant drug is shown below. In this nonrandomized antidepressant drug example, researchers (who know what the subjects are receiving) put depressed subjects into the placebo group, while "less depressed" subjects are put into the antidepressant drug group. As a result, even if the drug isn't effective, the group assignment may make the drug appear effective, thus biasing the results as shown below.

This is a bit of an extreme example, but even if the researchers are trying to prevent bias, sometimes bias can still occur. However, if the subjects are randomized, the sick and the healthy people will ideally be equally distributed between the groups. Thus, the trial will be unbiased and a true test of whether or not the drug is effective.

Here is another example. In an RCT to study the effects of the Mediterranean diet on cardiovascular disease development, researchers might ask the control group to follow a low-fat diet (typically recommended for heart disease prevention) and the intervention group to eat a Mediterranean diet. The study would continue for a defined period of time (usually years to study an outcome like heart disease), at which point the researchers would analyze their data to see if more people in the control or Mediterranean diet had heart attacks or strokes. Because the treatment and control groups were randomly assigned, they should be alike in every other way except for diet, so differences in heart disease could be attributed to the diet. This eliminates the problem of confounding factors found in observational research, and it’s why RCTs can provide evidence of causation, not just correlation.

Imagine for a moment what would happen if the two groups weren’t randomly assigned. What if the researchers let study participants choose which diet they’d like to adopt for the study? They might, for whatever reason, end up with more overweight people who smoke and have high blood pressure in the low-fat diet group, and more people who exercised regularly and had already been eating lots of olive oil and nuts for years in the Mediterranean diet group. If they found that the Mediterranean diet group had fewer heart attacks by the end of the study, they would have no way of knowing if this was because of the diet or because of the underlying differences in the groups. In other words, without randomization, their results would be compromised by confounding factors, with many of the same limitations as observational studies.

Placebo: In an RCT of a supplement, the control group would receive a placebo—a “fake” treatment that contains no active ingredients, such as a sugar pill. The use of a placebo is necessary in medical research because of a phenomenon known as the placebo effect. The placebo effect results in a beneficial effect because of a subject’s belief in the treatment, even though there is no treatment actually being administered. An example would be an athlete who consumes a sports drink and runs the 100-meter dash in 11.00 seconds. The athlete then, under the exact same conditions, drinks what he is told is "Super Duper Sports Drink" and runs the 100-meter dash in 10.50 seconds. But what the athlete didn't know was that Super Duper Sports Drink was the Sports Drink + Food Coloring. There was nothing different between the drinks, but the athlete believed that the "Super Duper Sports Drink" was going to help him run faster, so he did. This improvement is due to the placebo effect.

Blinding is a technique to prevent bias in intervention studies. In a study without blinding, the subject and the researchers both know what treatment the subject is receiving. This can lead to bias if the subject or researcher has expectations about the treatment working, so these types of trials are used less frequently. It’s best if a study is double-blind , meaning that neither the researcher nor the subject knows what treatment the subject is receiving. It’s relatively simple to double-blind a study where subjects are receiving a placebo or treatment pill because they could be formulated to look and taste the same. In a single-blind study , either the researcher or the subject knows what treatment they’re receiving, but not both. Studies of diets—such as the Mediterranean diet example—often can’t be double-blinded because the study subjects know whether or not they’re eating a lot of olive oil and nuts. However, the researchers who are checking participants’ blood pressure or evaluating their medical records could be blinded to their treatment group, reducing the chance of bias.

Open-label study:

Single-blinded study:

Double-blinded study:

Like all studies, RCTs and other intervention studies do have some limitations. They can be difficult to carry on for long periods of time and require that participants remain compliant with the intervention. They’re also costly and often have smaller sample sizes. Furthermore, it is unethical to study certain interventions. (An example of an unethical intervention would be to advise one group of pregnant mothers to drink alcohol to determine its effects on pregnancy outcomes because we know that alcohol consumption during pregnancy damages the developing fetus.)

VIDEO: “ Not all scientific studies are created equal ” by David H. Schwartz, YouTube (April 28, 2014), 4:26.

Meta-Analyses and Systematic Reviews

At the top of the hierarchy of evidence pyramid are systematic reviews and meta-analyses . You can think of these as “studies of studies.” They attempt to combine all of the relevant studies that have been conducted on a research question and summarize their overall conclusions. Researchers conducting a systematic review formulate a research question and then systematically and independently identify, select, evaluate, and synthesize all high-quality evidence that relates to the research question. Since systematic reviews combine the results of many studies, they help researchers produce more reliable findings. A meta-analysis is a type of systematic review that goes one step further, combining the data from multiple studies and using statistics to summarize it, as if creating a mega-study from many smaller studies . 4

However, even systematic reviews and meta-analyses aren’t the final word on scientific questions. For one thing, they’re only as good as the studies that they include. The Cochrane Collaboration is an international consortium of researchers who conduct systematic reviews in order to inform evidence-based healthcare, including nutrition, and their reviews are among the most well-regarded and rigorous in science. For the most recent Cochrane review of the Mediterranean diet and cardiovascular disease, two authors independently reviewed studies published on this question. Based on their inclusion criteria, 30 RCTs with a total of 12,461 participants were included in the final analysis. However, after evaluating and combining the data, the authors concluded that “despite the large number of included trials, there is still uncertainty regarding the effects of a Mediterranean‐style diet on cardiovascular disease occurrence and risk factors in people both with and without cardiovascular disease already.” Part of the reason for this uncertainty is that different trials found different results, and the quality of the studies was low to moderate. Some had problems with their randomization procedures, for example, and others were judged to have unreliable data. That doesn’t make them useless, but it adds to the uncertainty about this question, and uncertainty pushes the field forward towards more and better studies. The Cochrane review authors noted that they found seven ongoing trials of the Mediterranean diet, so we can hope that they’ll add more clarity to this question in the future. 5

Science is an ongoing process. It’s often a slow process, and it contains a lot of uncertainty, but it’s our best method of building knowledge of how the world and human life works. Many different types of studies can contribute to scientific knowledge. None are perfect—all have limitations—and a single study is never the final word on a scientific question. Part of what advances science is that researchers are constantly checking each other’s work, asking how it can be improved and what new questions it raises.

Attributions:

• “Chapter 1: The Basics” from Lindshield, B. L. Kansas State University Human Nutrition (FNDH 400) Flexbook. goo.gl/vOAnR , CC BY-NC-SA 4.0
• “The Broad Role of Nutritional Science,” section 1.3 from the book An Introduction to Nutrition (v. 1.0), CC BY-NC-SA 3.0

References:

• 1 Thiese, M. S. (2014). Observational and interventional study design types; an overview. Biochemia Medica , 24 (2), 199–210. https://doi.org/10.11613/BM.2014.022
• 2 Harvard T.H. Chan School of Public Health. (2018, January 16). Diet Review: Mediterranean Diet . The Nutrition Source. https://www.hsph.harvard.edu/nutritionsource/healthy-weight/diet-reviews/mediterranean-diet/
• 3 Ross, R., Gray, C. M., & Gill, J. M. R. (2015). Effects of an Injected Placebo on Endurance Running Performance. Medicine and Science in Sports and Exercise , 47 (8), 1672–1681. https://doi.org/10.1249/MSS.0000000000000584
• 4 Hooper, A. (n.d.). LibGuides: Systematic Review Resources: Systematic Reviews vs Other Types of Reviews . Retrieved February 7, 2020, from //libguides.sph.uth.tmc.edu/c.php?g=543382&p=5370369
• 5 Rees, K., Takeda, A., Martin, N., Ellis, L., Wijesekara, D., Vepa, A., Das, A., Hartley, L., & Stranges, S. (2019). Mediterranean‐style diet for the primary and secondary prevention of cardiovascular disease. Cochrane Database of Systematic Reviews , 3 . doi.org/10.1002/14651858.CD009825.pub3
• 6Levin K. (2006) Study design III: Cross-sectional studies. Evidence - Based Dentistry 7(1): 24.
• Figure 2.3. The hierarchy of evidence by Alice Callahan, is licensed under CC BY 4.0
• Research lab photo by National Cancer Institute on Unsplas h ; mouse photo by vaun0815 on Unsplash
• Figure 2.4. “Placebo effect example” by Lindshield, B. L. Kansas State University Human Nutrition (FNDH 400) Flexbook. goo.gl/vOAnR

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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Researcher, Academic Writer, Web developer

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Types of Research Studies

Epidemiology studies.

Epidemiology is the study of the patterns and causes of disease in people.

The goal of epidemiology studies is to give information that helps support or disprove an idea about a possible link between an exposure (such as alcohol use) and an outcome (such as breast cancer) in people.

The 2 main types of epidemiology studies are:

• Observational studies ( prospective cohort or case-control )

Randomized controlled trials

Though they have the same goal, observational studies and randomized controlled trials differ in:

• The way they are conducted
• The strengths of the conclusions they reach

Observational studies

In observational studies, the people in the study live their daily lives as they choose. They exercise when they want, eat what they like and take the medicines their doctors prescribe. They report these activities to researchers.

There are 2 types of observational studies:

Prospective cohort studies

Case-control studies.

A prospective cohort study follows a large group of people forward in time.

Some people will have a certain exposure (such as alcohol use) and others will not.

Researchers compare the different groups (for example, they might compare heavy drinkers, moderate drinkers, light drinkers and non-drinkers) to see which group is more likely to develop an outcome (such as breast cancer).

In a case-control study, researchers identify 2 groups: cases and controls.

• Cases are people who already have an outcome (such as breast cancer).
• Controls are people who do not have the outcome.

The researchers compare the 2 groups to see if any exposure (such as alcohol use) was more common in the history of one group compared to the other.

In randomized controlled trials (randomized clinical trials), researchers divide people into groups to compare different treatments or other interventions.

These studies are called randomized controlled trials because people are randomly assigned (as if by coin toss) to a certain treatment or behavior.

For example, in a randomized trial of a new drug therapy, half the people might be randomly assigned to a new drug and the other half to the standard treatment.

In a randomized controlled trial on exercise and breast cancer risk, half the participants might be randomly assigned to walk 10 minutes a day and the other half to walk 2 hours a day. The researchers would then see which group was more likely to develop breast cancer, those who walked 10 minutes a day or those who walked 2 hours a day.

Many behaviors, such as smoking or heavy alcohol drinking, can’t be tested in this way because it isn’t ethical to assign people to a behavior known to be harmful. In these cases, researchers must use observational studies.

Patient series

A patient series is a doctor’s observations of a group of patients who are given a certain treatment.

There is no comparison group in a patient series. All the patients are given a certain treatment and the outcomes of these patients are studied.

With no comparison group, it’s hard to draw firm conclusions about the effectiveness of a treatment.

For example, if 10 women with breast cancer are given a new treatment, and 2 of them respond, how do we know if the new treatment is better than standard treatment?

If we had a comparison group of 10 women with breast cancer who got standard treatment, we could compare their outcomes to those of the 10 women on the new treatment. If no women in the comparison group responded to standard treatment, then the 2 women who responded to the new treatment would represent a success of the new treatment. If, however, 2 of the 10 women in the standard treatment group also responded, then the new treatment is no better than the standard.

The lack of a comparison group makes it hard to draw conclusions from a patient series. However, data from a patient series can help form hypotheses that can be tested in other types of studies.

Strengths and weaknesses of different types of research studies

When reviewing scientific evidence, it’s helpful to understand the strengths and weaknesses of different types of research studies.

Case-control studies have some strengths:

• They are easy and fairly inexpensive to conduct.
• They are a good way for researchers to study rare diseases. If a disease is rare, you would need to follow a very large group of people forward in time to have many cases of the disease develop.
• They are a good way for researchers to study diseases that take a long time to develop. If a disease takes a long time to develop, you would have to follow a group of people for many years for cases of the disease to develop.

Case-control studies look at past exposures of people who already have a disease. This causes some concerns:

• It can be hard for people to remember details about the past, especially when it comes to things like diet.
• Memories can be biased (or influenced) because the information is gathered after an event, such as the diagnosis of breast cancer.
• When it comes to sensitive topics (such as abortion), the cases (the people with the disease) may be much more likely to give complete information about their history than the controls (the people without the disease). Such differences in reporting bias study results.

For these reasons, the accuracy of the results of case-control studies can be questionable.

Cohort studies

Prospective cohort studies avoid many of the problems of case-control studies because they gather information from people over time and before the events being studied happen.

However, compared to case-control studies, they are expensive to conduct.

Nested case-control studies

A nested case-control study is a case-control study within a prospective cohort study.

Nested case-control studies use the design of a case-control study. However, they use data gathered as part of a cohort study, so they are less prone to bias than standard case-control studies.

All things being equal, the strength of nested case-control data falls somewhere between that of standard case-control studies and cohort studies.

Randomized controlled trials are considered the gold standard for studying certain exposures, such as breast cancer treatment. Similar to cohort studies, they follow people over time and are expensive to do.

Because people in a randomized trial are randomly assigned to an intervention (such as a new chemotherapy drug) or standard treatment, these studies are more likely to show the true link between an intervention and a health outcome (such as survival).

Learn more about randomized clinical trials , including the types of clinical trials, benefits, and possible drawbacks.

Overall study quality

The overall quality of a study is important. For example, the results from a well-designed case-control study can be more reliable than those from a poorly-designed randomized trial.

Finding more information on research study design

If you’re interested in learning more about research study design, a basic epidemiology textbook from your local library may be a good place to start. The National Cancer Institute also has information on epidemiology studies and randomized controlled trials.

Animal studies

Animal studies add to our understanding of how and why some factors cause cancer in people.

However, there are many differences between animals and people, so it makes it hard to translate findings directly from one to the other.

Animal studies are also designed differently. They often look at exposures in larger doses and for shorter periods of time than are suitable for people.

While animal studies can lay the groundwork for research in people, we need human studies to draw conclusions for people.

All data presented within this section of the website come from studies done with people.

Joining a research study

Research is ongoing to improve all areas of breast cancer, from prevention to treatment.

Whether you’re newly diagnosed, finished breast cancer treatment many years ago, or even if you’ve never had breast cancer, there may be breast cancer research studies you can join.

If you have breast cancer, BreastCancerTrials.org in collaboration with Susan G. Komen® offers a custom matching service that can help find a studies that fit your needs. You can also visit the National Institutes of Health’s website to find a breast cancer treatment study.

If you’re interested in being part of other studies, talk with your health care provider. Your provider may know of studies in your area looking for volunteers.

Learn more about joining a research study .

Learn more about clinical trials .

Learn what Komen is doing to help people find and participate in clinical trials .

Updated 12/16/20

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

Related Articles

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Qualitative Data Coding

What Is a Focus Group?

Cross-Cultural Research Methodology In Psychology

What Is Internal Validity In Research?

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What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

Types of Fat

Unsaturated fats

Unsaturated fats, which are liquid at room temperature, are considered beneficial fats because they can improve blood cholesterol levels, ease inflammation, stabilize heart rhythms, and play a number of other beneficial roles. Unsaturated fats are predominantly found in foods from plants, such as vegetable oils, nuts, and seeds.

There are two types of “good” unsaturated fats:

1. Monounsaturated fats are found in high concentrations in:

• Olive, peanut, and canola oils
• Nuts such as almonds, hazelnuts, and pecans
• Seeds such as pumpkin and sesame seeds

2. Polyunsaturated fats are found in high concentrations in

• Sunflower, corn, soybean, and flaxseed oils
• Canola oil – though higher in monounsaturated fat, it’s also a good source of polyunsaturated fat.

Omega-3 fats are an important  type of polyunsaturated fat. The body can’t make these, so they must come from food.

• An excellent way to get omega-3 fats is by eating fish 2-3 times a week.
• Good plant sources of omega-3 fats include flax seeds, walnuts, and canola or soybean oil.
• Higher blood omega-3 fats are associated with lower risk of premature death among older adults, according to a study by HSPH faculty.
• Read more about omega-3 fats in our Ask the Expert with Dr. Frank Sacks.

Most people don’t eat enough healthful unsaturated fats. The American Heart Association suggests that 8-10 percent of daily calories should come from polyunsaturated fats, and there is evidence that eating more polyunsaturated fat—up to 15 percent of daily calories—in place of saturated fat can lower heart disease risk. ( 7 )

• Dutch researchers conducted an analysis of 60 trials that examined the effects of carbohydrates and various fats on blood lipid levels. In trials in which polyunsaturated and monounsaturated fats were eaten in place of carbohydrates, these good fats decreased levels of harmful LDL and increased protective HDL. ( 8 )
• More recently, a randomized trial known as the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart) showed that replacing a carbohydrate-rich diet with one rich in unsaturated fat, predominantly monounsaturated fats, lowers blood pressure, improves lipid levels, and reduces the estimated cardiovascular risk. ( 9 )

Finding Foods with Healthy Fats   is a handy visual guide to help you determine which fats are beneficial, and which are harmful.

Saturated Fats

All foods containing fat have a mix of specific types of fats. Even healthy foods like chicken and nuts have small amounts of saturated fat, though much less than the amounts found in beef, cheese, and ice cream. Saturated fat is mainly found in animal foods, but a few plant foods are also high in saturated fats, such as coconut, coconut oil , palm oil, and palm kernel oil.

• The Dietary Guidelines for Americans recommends getting less than 10 percent of calories each day from saturated fat. ( 10 )
• The American Heart Association goes even further, recommending limiting saturated fat to no more than 7 percent of calories. ( 11 )
• Cutting back on saturated fat will likely have no benefit, however, if people replace saturated fat with refined carbohydrates. Eating refined carbohydrates in place of saturated fat does lower “bad” LDL cholesterol, but it also lowers the “good” HDL cholesterol and increases triglycerides. The net effect is as bad for the heart as eating too much saturated fat.

In the United States, the biggest sources of saturated fat ( 12 ) in the diet are

• Pizza and cheese
• Whole and reduced fat milk, butter and dairy desserts
• Meat products (sausage, bacon, beef, hamburgers)
• Cookies and other grain-based desserts
• A variety of mixed fast food dishes

Though decades of dietary advice ( 13 , 14 ) suggested saturated fat was harmful, in recent years that idea has begun to evolve. Several studies suggest that eating diets high in saturated fat do not raise the risk of heart disease, with one report analyzing the findings of 21 studies that followed 350,000 people for up to 23 years.

• Investigators looked at the relationship between saturated fat intake and coronary heart disease (CHD), stroke, and cardiovascular disease (CVD). Their controversial conclusion: “There is insufficient evidence from prospective epidemiologic studies to conclude that dietary saturated fat is associated with an increased risk of CHD, stroke, or CVD.”( 13 )
• A well-publicized 2014 study questioned the link between saturated fat and heart disease, but HSPH nutrition experts determined the paper to be seriously misleading . In order to set the record straight, Harvard School of Public Health convened a panel of nutrition experts and held a teach-in, “ Saturated or not: Does type of fat matter? “

The overarching message is that cutting back on saturated fat can be good for health if people replace saturated fat with good fats , especially, polyunsaturated fats. ( 1 , 15 , 22 ) Eating good fats in place of saturated fat lowers the “bad” LDL cholesterol, and it improves the ratio of total cholesterol to “good” HDL cholesterol, lowering the risk of heart disease.

Eating good fats in place of saturated fat can also help prevent insulin resistance, a precursor to diabetes. ( 16 ) So while saturated fat may not be as harmful as once thought, evidence clearly shows that unsaturated fat remains the healthiest type of fat.

*Values expressed as percent of total fat; data are from analyses at Harvard School of Public Health Lipid Laboratory and U.S.D.A. publications.

Trans fatty acids, more commonly called trans fats, are made by heating liquid vegetable oils in the presence of hydrogen gas and a catalyst, a process called hydrogenation.

• Partially hydrogenating vegetable oils makes them more stable and less likely to become rancid. This process also converts the oil into a solid, which makes them function as margarine or shortening.
• Partially hydrogenated oils can withstand repeated heating without breaking down, making them ideal for frying fast foods.
• For these reasons, partially hydrogenated oils became a mainstay in restaurants and the food industry – for frying, baked goods, and processed snack foods and margarine.

Partially hydrogenated oil is not the only source of trans fats in our diets. Trans fats are also naturally found in beef fat and dairy fat in small amounts.

Trans fats are the worst type of fat for the heart, blood vessels, and rest of the body because they:

• Raise bad LDL and lower good HDL
• Create inflammation, ( 18 ) – a reaction related to immunity – which has been implicated in heart disease, stroke, diabetes, and other chronic conditions
• Contribute to insulin resistance ( 16 )
• Can have harmful health effects even in small amounts – for each additional 2 percent of calories from trans fat consumed daily, the risk of coronary heart disease increases by 23 percent.

The long road to phasing-out artificial trans fats

7. Mozaffarian, D., R. Micha, and S. Wallace, Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials. PLoS Med , 2010. 7(3): p. e1000252.

8. Mensink, R.P., et al., Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials. Am J Clin Nutr , 2003. 77(5): p. 1146-55.

9. Appel, L.J., et al., Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA , 2005. 294(19): p. 2455-64.

10. U.S. Department of Agriculture, U.S.D.o.H.a.H.S., Washington, D.C.: U.S. Government Printing Office. Dietary Guidelines for Americans, 2010, 2010.

11. Lichtenstein, A.H., et al., Diet and lifestyle recommendations revision 2006: a scientific statement from the American Heart Association Nutrition Committee. Circulation , 2006. 114(1): p. 82-96.

12. Institute, N.C., Risk Factor Monitoring and Methods: Table 1. Top Food Sources of Saturated Fat among U.S. Population, 2005–2006. NHANES.

13. Siri-Tarino, P.W., et al., Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease. Am J Clin Nutr , 2010. 91(3): p. 535-46.

14. Micha, R. and D. Mozaffarian, Saturated fat and cardiometabolic risk factors, coronary heart disease, stroke, and diabetes: a fresh look at the evidence. Lipids , 2010. 45(10): p. 893-905.

15. Astrup, A., et al., The role of reducing intakes of saturated fat in the prevention of cardiovascular disease: where does the evidence stand in 2010? Am J Clin Nutr , 2011. 93(4): p. 684-8.

16. Riserus, U., W.C. Willett, and F.B. Hu, Dietary fats and prevention of type 2 diabetes. Prog Lipid Res , 2009. 48(1): p. 44-51.

18. Mozaffarian, D., et al., Dietary intake of trans fatty acids and systemic inflammation in women. Am J Clin Nutr, 2004. 79(4): p. 606-12.

22. Farvid MS, Ding M, Pan A, Sun Q, Chiuve SE, Steffen LM, Willett WC, Hu FB. Dietary Linoleic Acid and Risk of Coronary Heart Disease: A Systematic Review and Meta-Analysis of Prospective Cohort Studies. Circulation, 2014.

Terms of Use

The contents of this website are for educational purposes and are not intended to offer personal medical advice. You should seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition. Never disregard professional medical advice or delay in seeking it because of something you have read on this website. The Nutrition Source does not recommend or endorse any products.

• Open access
• Published: 21 May 2024

Are recent health, welfare and care graduates part of a rural and remote workforce solution? Evidence from Tasmania, Australia

• Belinda Jessup 1 ,
• Fiona Proudfoot 2 ,
• Merylin Cross 1 &
• Tony Barnett 1  

BMC Health Services Research volume  24 , Article number:  652 ( 2024 ) Cite this article

Metrics details

Strong growth in graduate supply from health, welfare and care courses across Australia may bode well for easing rural workforce shortages. However, little is known about the employment opportunities available for recent graduates in non-metropolitan areas. This study aimed to quantify and describe advertised job vacancies for health, welfare and care professions in Tasmania, a largely rural and geographically isolated island state of Australia. Further, it aimed to examine those job vacancies specifying that recent graduates were suitable to apply.

Job advertisements for health, welfare and care professionals were collected weekly throughout 2018 from six online job vacancy websites. Data were extracted on 25 variables pertaining to type of profession, number of positions, location, and graduate suitability. Location of positions were recoded into a Modified Monash Model (MM) category, the Australian geographic standard used to classify rurality. Positions advertised in MM2 areas were considered regional and MM3-7 areas rural to very remote. Data were analysed using descriptive and inferential statistics.

Over the twelve-month period, 3967 advertisements were identified, recruiting for more than 4700 positions across 49 different health, welfare and care professions in Tasmania. Most vacancies were in the non-government sector (58.5%) and located in regional areas (71.7%) of the state. Professions most frequently advertised were registered nurse (24.4%) and welfare worker (11.4%). Eleven professions, including physiotherapist and occupational therapist, recorded a disproportionate number of advertisements relative to workforce size, suggesting discipline specific workforce shortages. Only 4.6% of collected advertisements specified that a recent graduate would be suitable to apply. Of these, most were for the non-government sector (70.1%) and located in regional areas (73.4%). The professions of physiotherapist (26.6%) and occupational therapist (11.4%) were most frequently represented in advertised graduate suitable positions.

Conclusions

Despite a range of advertised employment opportunities for health, welfare and care professionals across Tasmania, few specified vacancies as suitable for recent graduates and most were located in regional areas of the state. Health, welfare and care services in non-metropolitan locations may need to develop more employment opportunities for recent graduates and explicitly advertise these to job-seeking graduates to help grow and sustain the rural and remote health workforce into the future.

Peer Review reports

The Australian health, welfare and care workforce has expanded rapidly over the past decade, largely due to jobs growth, the prospects of long term employment stability, and the substantial increase in graduates exiting these courses [ 1 , 2 , 3 , 4 , 5 ]. In part, growth in graduate numbers has been driven by projections of national workforce shortages in health, welfare and care by 2025 [ 6 ]. With the high rate of attrition of more experienced professionals [ 7 ], this expanding graduate workforce was also expected to meet the service demand given the ageing population, the growing prevalence of chronic disease and the roll out of the National Disability Insurance Scheme [ 8 ]. More recently, strong graduate supply has also been identified as a critical component of surge workforce capability [ 9 ], necessary given the unprecedented impact of the COVID-19 pandemic [ 10 ], the repercussions of natural disasters on welfare and care workforce demand, as well as the workforce mobility experienced within this sector [ 11 ].

There is emerging concern that health, welfare and care services may not be structured to cope with the record supply of graduates, with some recently qualified professionals experiencing difficulties securing initial employment [ 2 , 3 , 5 , 12 ]. In 2021, the Graduate Outcomes Survey [ 13 ], which measures short-term employment outcomes in Australia, recorded the lowest percentage of graduates employed in some capacity at four months post-graduation (84.8%), with full-time employment at 68.9%. This report indicated that 15.2% of graduates were unemployed, and a further 15.9% were underemployed at four months post-qualifying. Although the same survey repeated in 2022 recorded an increase in both overall employment and full-time employment figures to 88.3% and 78.5% respectively, full-time employment rates varied across disciplines (e.g., 72.0% for psychology, 82.6% for nursing and 96.2% for pharmacy) [ 13 ]. Overall employment figures were also higher, irrespective of discipline, indicating that many health, welfare and care graduates experienced underemployment from having to commence their careers in part-time roles [ 2 , 5 , 12 , 13 ]. Both unemployment and underemployment among health graduates is likely influenced by the restricted number, and hence competitive nature of graduate specific positions which offer additional support and supervision in the immediate post-graduate year [ 2 , 12 ]. For some health disciplines such as nursing, psychology and pharmacy with structured, and sometimes compulsory postgraduate registrar or internship requirements, competitively gaining a post-graduate position that offers the required supervision can prove time intensive [ 14 , 15 ]. A study by Wong and colleagues [ 15 ] for example showed that in Australia, 42.7% of clinical psychology and clinical neuropsychology graduates took six months or longer to commence employment in a registrar position after completing their postgraduate studies.

While an increasingly competitive labour market will concern some graduates, ongoing rural workforce shortages create key opportunities to gain initial employment [ 16 , 17 , 18 ]. Health, welfare and care service managers often offer graduate positions to build rural workforce capacity given they typically attract a greater applicant pool and are therefore easier to fill [ 19 , 20 ]. This is fortuitous as health, welfare and care graduates are becoming increasingly motivated to seek rural employment, through affirmative selection of students with a rural background [ 21 ], positive rural clinical training experiences [ 22 ], previous experience either living or studying in that location [ 23 ], or through personal motivation to practice in a rural setting [ 23 ]. While this opportunistic employment of recent graduates motivated toward a career in rural health is congruent with sustainable rural health workforce policy [ 24 ], recent studies show a degree of ‘urban drift’ amongst rural origin health graduates, suggesting a lack of suitable positions in rural areas [ 25 , 26 ]. In part, this may reflect the challenges in resourcing and supporting graduate positions in rural areas [ 18 , 27 ]. Recent graduates need adequate supervision, training, opportunities for career advancement, diverse work opportunities and community integration to support positive transition into the rural workforce [ 18 , 23 , 27 ].

Several studies have reported the number of health, welfare and care graduates practising in rural areas post-graduation [ 25 , 26 , 28 ], and others quantify rural job opportunities for specific professions [ 20 , 29 , 30 ]. However, this literature fails to reflect more broadly the discipline areas seeking to employ graduates in non-metropolitan locations, or how many positions are available. With a growing supply of graduates potentially able to ease rural workforce shortages, this study has dual aims. First, to describe employment opportunities for health, welfare and care professions in Tasmania; a largely rural island state of Australia which faces ongoing challenges building a sustainable health workforce [ 31 ]. It was hypothesised that the number of advertisements for these professions in Tasmania would be proportionate to the size of that workforce and that if the proportions were higher, this may reflect a shortage of professionals in that area. Second, this study aimed to examine advertised vacancies specifying graduate suitability, with professions explicitly seeking to recruit recent graduates anticipated to be experiencing greater flexibility in the employment of new graduates and hence their suitability to help address a workforce shortage.

As a geographically isolated island state of Australia separated from the mainland by Bass Strait, Tasmania offers a unique context to explore the issue of workforce supply and demand. It is a relatively small island of approximately 68,401km 2 , and home to 506,736 people [ 32 ]. Tasmania’s largest population centres of Hobart, the capital city, and Launceston, are both considered regional (MM2) under the Modified Monash Model for classifying rurality in Australia, and are home to around 60% of the state’s population [ 32 ]. The remainder of Tasmania’s population are dispersed across rural and remote communities (MM3-7), with the state having the largest percentage of residents living in small rural towns (MM5) (18.2%) Australia-wide [ 32 ]. In 2016, the health, welfare and care workforce in Tasmania comprised 25,413 professionals, with nursing and carers forming the largest cohorts [ 33 ]. The workforce was largely centralised in MM2 areas. Although growth has been observed in the health, welfare and care workforce in rural and remote areas (MM3-7), there continues to be a disproportionately lower per capita distribution of health professionals in these areas [ 33 ]. The ongoing challenge of resourcing Tasmania’s health, welfare and care workforce is, in part, due to the absence of local training pathways, especially for allied health professions such as physiotherapy, occupational therapy, optometry, and podiatry, and difficulties recruiting tertiary qualified health professionals from mainland Australia [ 31 ]. The findings of this study are therefore likely to prove useful in guiding policy initiatives and strategic investment to build sustainable rural and remote workforce in Tasmania, and elsewhere.

This study employed a repeated cross-sectional longitudinal design, with weekly collection of online job vacancy advertisements for health, welfare and care professions in Tasmania over a twelve-month period. Ethics approval was granted by the Tasmanian Human Research Ethics Committee at the University of Tasmania (H0017219).

Between 1 January 2018 and 31 December 2018, online advertisements were collected by a member of the research team (FP,BJ) for health, welfare and care professions. A broad and inclusive listing of eligible professions was compiled from a range of data sources to reflect the types of workers represented in the local Tasmanian health, welfare and care workforce [ 33 ]. In situations where there was ambiguity regarding a profession advertised, consensus discussion occurred with a second member of the research team (MC or TB) regarding inclusion.

Initially, advertisements were identified by searching 30 job vacancy data sources on the same day each week using search terms developed specifically for each source. Sources included three local newspapers, 11 online job vacancy websites and 16 professional associations related to one of the health, welfare and care professions included in this study. However, after a four-week review period, no unique advertisements were identified beyond searches conducted in six online job vacancy websites (see additional file 1 ). Therefore, for the remaining 11 months of the study, only these six websites were used to collect advertisements.

Included advertisements were clipped using Evernote and electronically stored. Where possible, data for 25 variables were extracted for each advertisement including: date of advertisement; number of positions vacant; health profession/s; job title/s; type of employer (government, non-government); employment contract/s (temporary versus permanent); employment tenure/s (full-time, part-time, casual); level/grade of position/s; qualifications and experience required; salary; location/s of position/s; whether the position had previously been advertised; and if applications would be used to fill subsequent or similar positions. Graduate suitability was also coded, which for the purposes of this study was when the advertisement explicitly encouraged recent graduates to apply. Position location/s were subsequently recoded using the Modified Monash Model (MM). Positions in MM2 were categorised as regional, MM3-5 as rural, and MM6-7 as remote [ 34 ]. Position/s with multiple locations across regional, rural and remote areas, or that were advertised as ‘statewide’, were categorised as ‘mixed MM2-7’.

All extracted data were analysed using IBM SPSS Statistics (Version 27) ( https://www.ibm.com/products/spss-statistics ). Descriptive statistics were conducted to identify sample characteristics and relationships between variables were analysed using the Chi-square statistic. Z scores were calculated between population proportions for workforce size (drawing on 2016 census data provided by the Australian Bureau of Statistics (ABS)) and advertising frequency for individual professions. A p -value of < 0.05 was accepted as statistically significant for all calculations.

Total advertisements

Over the study period, a total of 3967 job advertisements were collected for health, welfare and care vacancies located across Tasmania. The second half of the year (July through December, n  = 2082, 52.5%) yielded a significantly greater number of advertisements than the first half (January through June, n  = 1885, 47.5%) (χ 2  = 16.6, 3, p  < 0.001).

While most job advertisements were for a single vacancy, 734 (18.5%) were recruiting for multiple vacancies. The total number of positions advertised exceeded 4700 (Table  1 ). Most advertisements recruiting for multiple vacancies were seeking registered nurses ( n  = 222, 30.2%), mixed professional backgrounds ( n  = 110, 15.0%), carers and/or aides ( n  = 97, 13.2%), or welfare workers ( n  = 66, 9.0%). Advertisements for multiple vacancies represented more than 25% of total advertisements for the professions of paramedic, midwife, carer and/or aide, dental therapist, youth justice health professional, enrolled nurse and radiographer (see additional file 2 ).

Professions advertised

Advertisements were collected for a total of 49 different health, welfare and care professions. The largest number of advertisements were collected for the professions of registered nurse ( n  = 954, 24.0%), followed by welfare worker ( n  = 450, 11.4%) (Table  1 ). Together with vacancies that were open to applicants from multiple professions ( n  = 425, 10.7%) and health professional managers ( n  = 322, 8.1%), these four groups accounted for just over half of all job advertisements. Seventeen professions recorded less than 10 advertisements across the twelve month period.

Among the 425 (10.7%) advertisements promoting vacancies as suitable for multiple professions, up to eight different professions were listed, though most specified two ( n  = 214, 51.3%) or three ( n  = 113, 27.1%) professions (Table  2 ). Of the advertisements specifying two different professions, most were for combinations of: registered nurse or enrolled nurse ( n  = 61, 28.5%); occupational therapist or physiotherapist ( n  = 56, 26.2%); psychologist or counsellor ( n  = 38, 17.8%); and psychologist or social worker ( n  = 32, 15.0%). Just over three quarters ( n  = 86, 76.1%) of advertisements that listed three different professions were recruiting for combinations of: occupational therapist, physiotherapist or exercise physiologist ( n  = 42, 37.2%); occupational therapist, psychologist or social worker ( n  = 25, 22.1%); and psychologist, social worker or counsellor ( n  = 19, 16.8%).

Among the 49 professions identified, only advertisements for health professional managers and case workers listed various professions as suitable for the role. For health professional managers, up to five professions were listed; however, most advertisements specified a single profession ( n  = 310, 96.3%), predominantly a registered nurse ( n  = 200, 62.1%) (Table  2 ). While most advertisements for case managers also advertised for a single profession ( n  = 41, 77.4%), some listed up to four professions. Over half ( n  = 30, 56.6%) of the advertisements for case workers did not specify what profession should apply, with the remaining 23 advertisements seeking to recruit mostly social workers ( n  = 21) and psychologists ( n  = 11).

Based on ABS workforce data, eleven professions recorded significantly more advertisements than expected (welfare worker, health professional manager, physiotherapist, occupational therapist, nursing support worker, allied health assistant, podiatrist, sonographer, exercise physiologist, alcohol and other drug worker, cardiology health professional) (Table  3 ). Conversely, eight professions (carer and/or aide, enrolled nurse, social worker, midwife, counsellor, paramedic, hospital/medical scientist, complementary health therapist) showed proportionately fewer advertisements than expected.

Location of job vacancies

Most advertisements ( n  = 2845, 71.7%) were for positions located in the state’s two largest population centres, Hobart and Launceston (both MM2) (Table  4 ). The remainder were spread across rural (MM3-5) ( n  = 693, 17.4%) and remote communities (MM6-7) ( n  = 57, 1.5%), mixed (MM2-7) locations ( n  = 51, 1.3%), or were unspecified ( n  = 321, 8.1%).

Employment sector, tenure and hours of employment

Over half ( n  = 2321, 58.5%) of the advertisements were for positions within the non-government sector and a third ( n  = 1325, 33.4%) were government positions (Table  4 ). Irrespective of employer type, only 6.2% of advertisements indicated they were for a previously listed vacancy and 10.4% that applications may be used to ‘fill subsequent or similar positions’. The re-use of applicant data elicited from job advertisements for future vacancies was statistically more likely in the government than the non-government sector (χ 2  = 64.8,2, p  < 0.001).

Permanent positions were represented in only 1186 (29.9%) advertisements, with 982 (24.7%) temporary and the remaining 1667 (42.0%) not specified. Full-time positions were represented in 1514 (38.2%) advertisements, with 954 (24.1%) part-time and 439 (11.1%) casual. Locum positions were recorded in 57 (1.4%) advertisements and were largely recruiting physiotherapists ( n  = 23, 40.4%), occupational therapists ( n  = 10, 17.5%), or either of these two professions ( n  = 9, 15.8%). In those advertisements for full and part-time positions that specified tenure, a similar proportion indicated the vacancy was permanent (63%) versus fixed term (37%). Over 90% of all casual positions advertised were for a fixed term appointment.

Qualifications and experience required

Almost three in four advertisements specified that a tertiary or vocational qualification was required (Table  4 ). Vocational qualifications were largely (n = 374, 83.9%) specified in advertisements for welfare workers, carers and/or aide, allied health assistants and enrolled nurses. Prior work experience was listed as either ‘essential’ or desirable’ in around half ( n  = 1912, 48.2%) of all advertisements. However, more than half of the advertisements for health professional manager, case manager, alcohol and other drug worker, ACAT assessor, mammographer and health/medical physicist, required previous work experience (see additional file 2 ). Only five advertisements, recruiting for an allied health assistant, a carer and/or aide and physiotherapist, indicated prior experience was not necessary for the role.

Graduate suitable advertisements

Of the 3967 advertisements collected, only 184 (4.6%) indicated the vacancy was suitable for a recent graduate. A similar number of advertisements for graduate suitable positions were recorded in the first ( n  = 89, 48.4%) and second ( n  = 95, 51.6%) halves of the year.

While most advertisements for graduate suitable positions related to a single vacancy ( n  = 138), 46 (25.0%) were recruiting for multiple positions (Table  5 ). Advertisements seeking to fill multiple vacancies were mostly recruiting professionals of mixed disciplinary backgrounds ( n  = 17, 37.0%), physiotherapists ( n  = 7, 15.2%), registered nurses ( n  = 5, 10.9%), and midwives ( n  = 4, 8.7%). Advertisements for the professions of paramedic (100%) and registered nurse (80%) sought predominantly to fill multiple graduate suitable vacancies, while professions such as exercise physiologist, speech pathologist and radiographer only sought to fill single positions (see additional file 3 ).

Professions advertising graduate suitability

Only 23 of the 49 identified professions specified graduate suitable positions in one or more advertisements over the study period (Table  5 ). Over half of these advertisements were recruiting for physiotherapists ( n  = 49, 26.6%), professionals of mixed disciplinary backgrounds ( n  = 33, 17.9%), and occupational therapists ( n  = 21, 11.4%). Proportionately, podiatry (38.7%) and exercise physiology (35.0%) advertised graduate suitable positions the most. Another five professions (physiotherapist, midwife, paramedic, health/medical physicist, dental therapist) specified graduate suitability in more than 20% of advertisements.

Up to seven professions were listed as eligible to apply for graduate suitable vacancies calling for applicants of mixed disciplinary backgrounds. However, most advertisements specified two ( n  = 17, 51.5%), or three ( n  = 11, 33.3%) different eligible professions (Table  2 ). Of the advertisements specifying two different professions, most were for combinations of: physiotherapist and occupational therapist ( n  = 12, 70.6%), or psychologist and counsellor ( n  = 4, 23.5%). Of the advertisements specifying three different professions, most ( n  = 8, 72.7%) were recruiting for a combination of occupational therapist, physiotherapist or exercise physiologist.

Location of graduate suitable positions

Almost three quarters ( n  = 135, 73.4%) of the graduate suitable positions advertised were in the regional centres of Hobart and Launceston (MM2) (Table  4 ). Only 22 (11.9%) were for positions in rural areas (MM3-5), and no graduate suitable vacancies were advertised exclusively in remote areas (MM6-7). There were, however, 8 (4.3%) positions advertised in mixed regional/rural/remote areas (MM2-7). Only 12 of the 23 professions that advertised graduate suitable positions were recruiting for vacancies in rural areas (MM3-5) (see additional file 3 ).

Employment sector, tenure and hours of employment of graduate suitable positions

Most advertisements specifying graduate suitability were for the non-government sector ( n  = 129, 70.1%), with only 18 (9.8%) for Tasmanian government organisations (Table  4 ). Despite this low figure, over half of these government advertisements ( n  = 10, 55.6%) were seeking to fill multiple vacancies.

Almost two-thirds ( n  = 115, 62.5%) of advertisements for graduate suitable positions did not specify employment tenure. Only 27 (14.7%) related to a permanent role and less than half to a full-time position ( n  = 76, 41.3%). A further 39 (21.2%) offered temporary or fixed term contracts and 22 (12.0%) part-time positions. While nearly one in five ( n  = 33, 17.9%) of these advertisements offered variable hours of employment, a similar proportion did not specify the hours associated with the position ( n  = 34, 18.5%).

Qualifications and experience required for graduate suitable positions

The majority ( n  = 157, 85.3%) of advertisements specifying graduate suitability stated tertiary qualifications were required. Experience was indicated as either ‘essential’ or ‘desirable’ for the role in just under a quarter of the advertisements ( n  = 43, 23.4%). No graduate suitable advertisements stated that ‘no experience was necessary’ (Table  4 ).

This study identified 3967 job advertisements recruiting for over 4700 vacancies across 49 different health, welfare and care professions in Tasmania over a twelve-month period. This likely represents a subset of all available employment opportunities within the state at the time of the study for several reasons. First, other recruitment methods such as word of mouth, professional networks and social media were not used to source vacancies [ 35 ]. Second, around a quarter of advertisements were recruiting for multiple vacancies, with those for graduate transition programs likely seeking to fill large numbers of positions [ 36 ]. Third, around 10% of advertisements, predominantly for vacancies in the government sector, specified that applications would be used to fill similar roles in the future. This suggests prospective employers were taking efforts to reduce advertising for individual vacancies, possibly reflecting the burdensome human resource delays associated with the recruitment of health, welfare and care professionals [ 18 , 19 , 27 ].

Despite these caveats, the present findings provide evidence of health recruitment activity, with many of the 49 professions identified in this study recording advertising volume comparative to workforce size. However, eleven professions, including several allied health disciplines such as physiotherapist, occupational therapist, podiatrist, sonographer, exercise physiologist, and allied health assistant appeared in demand, with advertising activity proportionately greater than expected. Shortages of allied health professionals, especially occupational therapists and physiotherapists, have been long-standing in Tasmania [ 37 , 38 , 39 ], and exacerbated by the introduction of the National Disability Insurance Scheme [ 40 ], which likely explains some of these findings. To help compensate for allied health professional shortages, there has been a targeted effort to grow the allied health assistant workforce in the state [ 40 ], which may also explain the high number of advertisements recorded for this profession in this study. In its strategic planning for future health workforce growth and sustainability, the Tasmanian Government has recognised the absence of local training pathways as a specific barrier to building the allied health workforce [ 31 ]. Therefore, the University of Tasmania, in concert with the Tasmanian Government, has developed a suite of new allied health degrees in physiotherapy, speech pathology and occupational therapy, to offer a sustainable home-grown solution to building workforce capacity in health professions experiencing persistent shortages [ 41 ]. While this approach aligns with recommendations within the literature [ 24 ], future research will need to explore the success of this home-grown solution to allied health workforce growth by determining the number of graduates produced, their mobility and participation in the state’s health workforce over time.

While it was possible to directly compare expected and actual advertising activity for specific disciplines, this study observed a notable 10% of vacancies were open to applicants from different professional backgrounds. Common recruitment combinations included: ‘registered OR enrolled nurse’; ‘occupational therapist OR physiotherapist OR exercise physiologist’; and ‘psychologist OR social worker OR counsellor’. This broader approach to advertising has been observed in other studies of online job advertisements specifically for occupational therapists [ 42 ] and counsellors [ 43 ], and reflects not only the blurring of professional roles and responsibilities among certain health professions [ 44 ], but the broadening scope of non-discipline specific roles that health graduates can fulfil [ 42 ]. What is not yet clear in the literature is how attractive these broader advertisements are to potential applicants compared to discipline specific roles. Neither is it clear the extent to which new graduates require a period of immersion in their profession in order to develop a professional identity [ 45 ], and hence may prefer positions in which their discipline is specified. Important areas for future research.

In a recent study by Beel [ 43 ], analysis of online counselling advertisements observed a pattern of vacancies seeking either ‘a psychologist OR social worker OR counsellor’, the same as observed in this study, and suggested that this approach enabled a broader pool of applicants for positions. Others have described this advertising behaviour as ‘workforce substitution’, and is considered an effective way of filling workforce shortages when there is a relative oversupply of one health profession compared with another [ 46 ]. In the context of this study, most professionals sought in advertisements open to different disciplines were able to be trained within the state, except for occupational therapists and physiotherapists, suggesting that an issue may be that of undersupply at a local level. For example, Tasmania has a lower number of psychologists per capita compared to other mainland states and territories, despite training pathways for this discipline being available at the University of Tasmania [ 31 ]. Positively, the University of Tasmania has recently expanded its course offerings for psychology training to the north of the state, which may help build workforce capacity in this specific discipline [ 47 ]. It will be important for future research to explore the number of graduates trained in the state and their career pathways, including post-graduate work locations over time, to understand how Tasmania can better achieve a balance between local health graduate supply and workforce demand.

Less than 5% of job advertisements specified graduate suitability, with these vacancies being largely in the non-government sector. Further, only 23 of the 49 identified health, welfare and care professions advertised graduate suitable positions. Although this overall low figure and spread across professions provides evidence of limited online recruitment activity specifically for graduates, it is important to consider not all graduate suitable positions may have been captured in this study. Tasmanian employers were potentially using other advertising methods, including word of mouth, social media and clinical placements, to recruit recent graduates directly [ 17 , 35 ], especially for those professions trained within the state. Further, it is possible that online advertising activity underestimates graduate demand for some professions, with up to a quarter of graduate suitable advertisements recruiting for multiple vacancies. For professions such as midwifery, nursing and paramedicine who were found to advertise infrequently, but for many vacancies, this likely reflects graduate transition programs. For registered and enrolled nurses, such programs can offer up to 240 transition to practice positions across the state [ 36 ]. This infrequent advertising of large-scale graduate recruitment highlights a potential barrier to employment in these professions if graduates miss seeing the online advertisement, more so for interstate graduates who may not be made aware of positions by their host training university. Students in their final years and soon to graduate should obtain graduate recruitment process timelines across different jurisdictions to ensure that they do not miss out on available employment opportunities, especially for health professions with an oversupply of graduates that may require a move interstate to secure initial work [ 2 , 12 , 17 ].

Online advertising of graduate suitable vacancies was most common for physiotherapists, occupational therapists, or combinations thereof. Indeed, one in five of all advertised positions for physiotherapists, and over a third for podiatrists and exercise physiologists specifically sought to recruit recent graduates. This highlights the opportunities available to graduates from some allied health professions in the Tasmanian labour market and the need to reorient local employers toward how best to secure applicants for available vacancies [ 48 ]. In 2023, the Tasmanian Government began offering a scholarship program specifically targeting allied health disciplines to both attract and retain graduates to work within the state [ 49 ]. This scholarship offers students in their final year of study of select allied health disciplines a cash payment, with a second payment provided following three years service in a graduate suitable position within the state’s health workforce [ 49 ]. However, the effectiveness of this approach may be limited, with this study illustrating few graduate suitable positions to apply for. It may be a better approach to develop graduate transition programs for health, welfare and care professions in high demand such as physiotherapy and occupational therapy, and in collaboration with the non-government sector, to streamline recruitment efforts. Utilising the resources of rural workforce agencies available in each state and who are designated to support the recruitment of health, welfare and care professionals to rural areas to advertise such programs, may be an effective way to market opportunities to a broader local and interstate audience. Given the often broader nature of job advertisements noted in this study, this approach would limit wasted efforts by recent graduates who apply for positions never designed to be filled by less experienced health professionals [ 16 , 50 ]. Further, it would minimise administrative burden involved in recruitment and the delays which can impact on filling roles, especially in rural areas [ 19 , 27 ].

Of the graduate suitable positions identified, most were centralised in regional areas (MM2), with just over 10% located in rural towns (MM3-5), and none in remote areas (MM6-7) of the state. This finding provides some explanation for the ‘urban drift’ of rural origin health graduates toward metropolitan areas [ 25 , 26 ], and suggests that rural areas may lack sufficient opportunities to cater for the number of graduates who may be motivated to seek rural employment [ 22 ]. In the Tasmanian context, rural employment opportunities may be constrained by the state’s hub and spoke approach to healthcare delivery, with more complex health services centralised in the larger regional population centres to ensure safety and quality [ 51 ]. While some services are decentralised in rural communities when safe and sustainable, this often requires a health workforce that is generalist and experienced [ 51 ]. This may challenge sustainable long term rural workforce development which emphasises the importance of recruiting graduates directly into rural positions [ 24 ]. It is acknowledged that graduate employment is resource intensive and challenging within rural contexts where funding or population size often limit the only sustainable option to sole-practice positions. This can prohibit the provision of important transitional supports including clear orientation processes, regular career check-in and development sessions, collegial practice, senior staff supervision, and social connectedness [ 24 , 27 , 52 , 53 ]. The autonomy required for practice in more remote locations can also be challenging for recent graduates [ 27 , 53 ], and may explain why around a quarter of advertisements indicating graduate suitability specified experience as necessary or desirable in this study.

With growth in the number of health graduates motivated to seek rural employment [ 22 ], the lack of rural employment opportunities suitable for graduates is a missed opportunity for sustainable rural health workforce growth in Tasmania [ 24 ]. Greater attention and collaboration are therefore needed between government and non-government sectors, and regional and rural areas of the state to develop more employment opportunities suitable for recent health, welfare and care graduates that are structured to support transition to the workforce and promote longer-term retention. These opportunities should aim to be located outside of the larger regional centres and could include cross sector roles which combine work in hospital, primary care, aged care, disability and education settings to support sustainability; positions likely to appeal to graduates given their motivation toward the acquisition of a broad range of skills and experience [ 18 , 27 , 52 , 53 ]. However, graduates are vulnerable in their initial post-graduate years, and any positions created must seek to provide adequate supervision and training, regular access to more experienced professionals for orientation, guidance, ongoing support and mentorship, and opportunities to access quality professional development [ 27 , 52 , 53 , 54 ]. This may require enhanced mentor recruitment, recognition and reward strategies to ensure supervisory capacity within existing rural health workforce can be achieved. Ensuring supportive management and workplace culture, the development of professional and interprofessional relationships, especially for sole positions, and financial security through full-time, permanent employment, will also be important for fostering retention [ 27 , 28 , 52 , 53 ]. However, there is a need to ensure career pathways are available in rural settings that would allow graduates to remain in place after their completion of graduate positions [ 24 , 53 , 54 ].

The Tasmanian Government has already implemented strategic measures to address congoing health workforce shortages by investing in local training opportunities where sustainable to do so [ 31 , 41 ], and introducing scholarship schemes to attract candidates from interstate courses [ 49 ]. While these strategies align with evidence-based approaches to rural workforce growth and sustainability [ 23 , 54 , 55 ], other measures are recommended including: affirmative selection of Tasmanian rural origin students into health courses given these students are more likely to remain in the state and work in rural areas post-qualifying [ 17 , 21 , 23 , 54 , 55 ]; and building high-quality placement capacity across the state, especially for allied health professions and those without local training options, to build a pipeline of interested graduates [ 22 , 23 , 54 ] and promote job satisfaction among the existing workforce [ 56 ]. Improving rural curricula across health courses and building generalist capabilities will also support health graduates to transition successfully into rural positions when available [ 27 , 53 , 55 ].

Finally, despite the ongoing nature of rural health workforce shortages and the opportunities graduate recruitment can provide to fill gaps, there is a current lack of centralised, comprehensive data to enable collective evaluation and planning of solutions [ 46 ]. It may be that a comprehensive, integrated national tracking system is needed to determine the number of new health graduates ready to enter the workforce, their pathways into employment, and where they practice over time. Although some of this information is gathered through the Graduate Outcomes Survey [ 13 ], and the Australian Health Practitioner Regulation Agency (AHPRA), both have limitations in the scope of participation of health graduates [ 13 , 31 ]. The Nursing and Allied Health National Graduate Outcomes Tracking (NAHGOT) study is a coordinated effort to integrate these existing datasets to develop a more comprehensive graduate tracking system for the purposes of evaluating rural workforce participation [ 57 ]. Increased participation in NAHGOT by all University Departments of Rural Health would be a step toward improving the national picture of health graduate completions, recruitment and retention, especially in rural and remote settings. However, beyond this, continued efforts towards building a centralised, comprehensive dataset is needed to better understand the extent of health workforce shortages nationally.

There are inherent limitations with the use of online advertisements to explore health employment opportunities [ 58 ]. In addition to the limitations already described, this study may have inadvertently counted job advertisements more than once where they were advertised in different formats across the six websites. Although efforts were undertaken to match advertisement information across the different web sources from week to week to count job advertisements only once during their advertised period, this possibility cannot be discounted. The total advertisements figure may have also included readvertised job vacancies that were not filled through initial advertising efforts. Although this may have inflated the actual number of positions available over the study period, repeat advertisements profiled those professions more likely experiencing a greater workforce shortage and an inability to fill positions. Finally, advertisements for multiple vacancies were interpreted as offering two or more positions. However, as illustrated with the advertisements for graduate transition programs in some professions, including nursing [ 36 ], this may have substantially underreported the number of positions available.

More than 4,700 advertised job vacancies for 49 different health, welfare and care professions were identified in Tasmania across a twelve-month period. While most disciplines recorded levels of online advertising activity consistent with workforce size, eleven professions, including physiotherapist, occupational therapist, podiatrist, sonographer, exercise physiologist and allied health assistant, appeared in demand. Most of these eleven professions were allied health disciplines and were unable to be trained within the state at the time of this study, highlighting the importance of local training pathways to support health workforce growth and sustainability in rural settings such as Tasmania.

Fewer than 5% of job advertisements specified graduates were suitable to apply, with most seeking to recruit physiotherapists, occupational therapists, or a combination thereof. Most vacancies were in the two large regional centres of the state, with no employers in remote areas, and few in rural settings, advertised employment opportunities that were suitable for recent graduates to apply. This highlights the missed opportunities to foster long term rural workforce growth by offering more positions in rural settings for rurally motivated recent health graduates.

Collaborative efforts are needed between both government and non-government health sectors, and between regional, rural and remote settings of the state to harness graduates as a rural and remote workforce solution by creating more graduate positions within healthcare organisations or networks, and introducing local graduate transition support programs through enhanced mentor recruitment, recognition and reward. The development of career pathways in rural and remote areas are also needed to complement graduate recruitment, thus allowing opportunities for those who have completed their initial transition to practice program to be retained, and hence contribute both to the local health service and community longer-term. Finally, consideration is needed for a comprehensive, integrated national tracking system to monitor health graduate numbers, their pathways into employment, and where they practice over time to help support health workforce planning at both the state and national level.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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This research was supported by the Rural Health Multidisciplinary Training (RHMT) Program.

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This project was conceptualised by B.J., M.C. and T.B. The methodology was developed by B.J., M.C. and T.B. The data was collected by F.P. and B.J. The analysis was conducted by B.J. and T.B. Writing of the original draft was by B.J. Reviewing and editing of the draft was conducted by B.J., F.P., M.C. and T.B. All authors have read and approved the submitted manuscript.

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Supplementary Material 1. Additional File 1. Word document. Data sources used to identify job advertisements. Table showing search strategy for job advertisements

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Supplementary Material 2. Additional File 2. Word document. Proportion of job advertisements for health, welfare and care professions across Tasmania by advertisement characteristic ( n  = 3967). Detailed analysis of job advertisements by characteristics.

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Supplementary Material 3. Additional File 3. Word document. Proportion of graduate suitable job advertisements by advertisement characteristic ( n  = 184). Detailed analysis of graduate suitable job advertisements by characteristics.

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Jessup, B., Proudfoot, F., Cross, M. et al. Are recent health, welfare and care graduates part of a rural and remote workforce solution? Evidence from Tasmania, Australia. BMC Health Serv Res 24 , 652 (2024). https://doi.org/10.1186/s12913-024-11087-9

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Types of Study in Medical Research

Bernd röhrig.

1 MDK Rheinland-Pfalz, Referat Rehabilitation/Biometrie, Alzey

Jean-Baptist du Prel

2 Zentrum für Präventive Pädiatrie, Zentrum für Kinder- und Jugendmedizin, Mainz

Daniel Wachtlin

3 Interdisziplinäres Zentrum Klinische Studien (IZKS), Fachbereich Medizin der Universität Mainz

Maria Blettner

4 Institut für Medizinische Biometrie, Epidemiologie und Informatik (IMBEI), Johannes Gutenberg Universität Mainz

The choice of study type is an important aspect of the design of medical studies. The study design and consequent study type are major determinants of a study’s scientific quality and clinical value.

This article describes the structured classification of studies into two types, primary and secondary, as well as a further subclassification of studies of primary type. This is done on the basis of a selective literature search concerning study types in medical research, in addition to the authors’ own experience.

Three main areas of medical research can be distinguished by study type: basic (experimental), clinical, and epidemiological research. Furthermore, clinical and epidemiological studies can be further subclassified as either interventional or noninterventional.

Conclusions

The study type that can best answer the particular research question at hand must be determined not only on a purely scientific basis, but also in view of the available financial resources, staffing, and practical feasibility (organization, medical prerequisites, number of patients, etc.).

The quality, reliability and possibility of publishing a study are decisively influenced by the selection of a proper study design. The study type is a component of the study design (see the article "Study Design in Medical Research") and must be specified before the study starts. The study type is determined by the question to be answered and decides how useful a scientific study is and how well it can be interpreted. If the wrong study type has been selected, this cannot be rectified once the study has started.

After an earlier publication dealing with aspects of study design, the present article deals with study types in primary and secondary research. The article focuses on study types in primary research. A special article will be devoted to study types in secondary research, such as meta-analyses and reviews. This article covers the classification of individual study types. The conception, implementation, advantages, disadvantages and possibilities of using the different study types are illustrated by examples. The article is based on a selective literature research on study types in medical research, as well as the authors’ own experience.

Classification of study types

In principle, medical research is classified into primary and secondary research. While secondary research summarizes available studies in the form of reviews and meta-analyses, the actual studies are performed in primary research. Three main areas are distinguished: basic medical research, clinical research, and epidemiological research. In individual cases, it may be difficult to classify individual studies to one of these three main categories or to the subcategories. In the interests of clarity and to avoid excessive length, the authors will dispense with discussing special areas of research, such as health services research, quality assurance, or clinical epidemiology. Figure 1 gives an overview of the different study types in medical research.

Classification of different study types

*1 , sometimes known as experimental research; *2 , analogous term: interventional; *3 , analogous term: noninterventional or nonexperimental

This scheme is intended to classify the study types as clearly as possible. In the interests of clarity, we have excluded clinical epidemiology — a subject which borders on both clinical and epidemiological research ( 3 ). The study types in this area can be found under clinical research and epidemiology.

Basic research

Basic medical research (otherwise known as experimental research) includes animal experiments, cell studies, biochemical, genetic and physiological investigations, and studies on the properties of drugs and materials. In almost all experiments, at least one independent variable is varied and the effects on the dependent variable are investigated. The procedure and the experimental design can be precisely specified and implemented ( 1 ). For example, the population, number of groups, case numbers, treatments and dosages can be exactly specified. It is also important that confounding factors should be specifically controlled or reduced. In experiments, specific hypotheses are investigated and causal statements are made. High internal validity (= unambiguity) is achieved by setting up standardized experimental conditions, with low variability in the units of observation (for example, cells, animals or materials). External validity is a more difficult issue. Laboratory conditions cannot always be directly transferred to normal clinical practice and processes in isolated cells or in animals are not equivalent to those in man (= generalizability) ( 2 ).

Basic research also includes the development and improvement of analytical procedures—such as analytical determination of enzymes, markers or genes—, imaging procedures—such as computed tomography or magnetic resonance imaging—, and gene sequencing—such as the link between eye color and specific gene sequences. The development of biometric procedures—such as statistical test procedures, modeling and statistical evaluation strategies—also belongs here.

Clinical studies

Clinical studies include both interventional (or experimental) studies and noninterventional (or observational) studies. A clinical drug study is an interventional clinical study, defined according to §4 Paragraph 23 of the Medicines Act [Arzneimittelgesetz; AMG] as "any study performed on man with the purpose of studying or demonstrating the clinical or pharmacological effects of drugs, to establish side effects, or to investigate absorption, distribution, metabolism or elimination, with the aim of providing clear evidence of the efficacy or safety of the drug."

Interventional studies also include studies on medical devices and studies in which surgical, physical or psychotherapeutic procedures are examined. In contrast to clinical studies, §4 Paragraph 23 of the AMG describes noninterventional studies as follows: "A noninterventional study is a study in the context of which knowledge from the treatment of persons with drugs in accordance with the instructions for use specified in their registration is analyzed using epidemiological methods. The diagnosis, treatment and monitoring are not performed according to a previously specified study protocol, but exclusively according to medical practice."

The aim of an interventional clinical study is to compare treatment procedures within a patient population, which should exhibit as few as possible internal differences, apart from the treatment ( 4 , e1 ). This is to be achieved by appropriate measures, particularly by random allocation of the patients to the groups, thus avoiding bias in the result. Possible therapies include a drug, an operation, the therapeutic use of a medical device such as a stent, or physiotherapy, acupuncture, psychosocial intervention, rehabilitation measures, training or diet. Vaccine studies also count as interventional studies in Germany and are performed as clinical studies according to the AMG.

Interventional clinical studies are subject to a variety of legal and ethical requirements, including the Medicines Act and the Law on Medical Devices. Studies with medical devices must be registered by the responsible authorities, who must also approve studies with drugs. Drug studies also require a favorable ruling from the responsible ethics committee. A study must be performed in accordance with the binding rules of Good Clinical Practice (GCP) ( 5 , e2 – e4 ). For clinical studies on persons capable of giving consent, it is absolutely essential that the patient should sign a declaration of consent (informed consent) ( e2 ). A control group is included in most clinical studies. This group receives another treatment regimen and/or placebo—a therapy without substantial efficacy. The selection of the control group must not only be ethically defensible, but also be suitable for answering the most important questions in the study ( e5 ).

Clinical studies should ideally include randomization, in which the patients are allocated by chance to the therapy arms. This procedure is performed with random numbers or computer algorithms ( 6 – 8 ). Randomization ensures that the patients will be allocated to the different groups in a balanced manner and that possible confounding factors—such as risk factors, comorbidities and genetic variabilities—will be distributed by chance between the groups (structural equivalence) ( 9 , 10 ). Randomization is intended to maximize homogeneity between the groups and prevent, for example, a specific therapy being reserved for patients with a particularly favorable prognosis (such as young patients in good physical condition) ( 11 ).

Blinding is another suitable method to avoid bias. A distinction is made between single and double blinding. With single blinding, the patient is unaware which treatment he is receiving, while, with double blinding, neither the patient nor the investigator knows which treatment is planned. Blinding the patient and investigator excludes possible subjective (even subconscious) influences on the evaluation of a specific therapy (e.g. drug administration versus placebo). Thus, double blinding ensures that the patient or therapy groups are both handled and observed in the same manner. The highest possible degree of blinding should always be selected. The study statistician should also remain blinded until the details of the evaluation have finally been specified.

A well designed clinical study must also include case number planning. This ensures that the assumed therapeutic effect can be recognized as such, with a previously specified statistical probability (statistical power) ( 4 , 6 , 12 ).

It is important for the performance of a clinical trial that it should be carefully planned and that the exact clinical details and methods should be specified in the study protocol ( 13 ). It is, however, also important that the implementation of the study according to the protocol, as well as data collection, must be monitored. For a first class study, data quality must be ensured by double data entry, programming plausibility tests, and evaluation by a biometrician. International recommendations for the reporting of randomized clinical studies can be found in the CONSORT statement (Consolidated Standards of Reporting Trials, www.consort-statement.org ) ( 14 ). Many journals make this an essential condition for publication.

For all the methodological reasons mentioned above and for ethical reasons, the randomized controlled and blinded clinical trial with case number planning is accepted as the gold standard for testing the efficacy and safety of therapies or drugs ( 4 , e1 , 15 ).

In contrast, noninterventional clinical studies (NIS) are patient-related observational studies, in which patients are given an individually specified therapy. The responsible physician specifies the therapy on the basis of the medical diagnosis and the patient’s wishes. NIS include noninterventional therapeutic studies, prognostic studies, observational drug studies, secondary data analyses, case series and single case analyses ( 13 , 16 ). Similarly to clinical studies, noninterventional therapy studies include comparison between therapies; however, the treatment is exclusively according to the physician’s discretion. The evaluation is often retrospective. Prognostic studies examine the influence of prognostic factors (such as tumor stage, functional state, or body mass index) on the further course of a disease. Diagnostic studies are another class of observational studies, in which either the quality of a diagnostic method is compared to an established method (ideally a gold standard), or an investigator is compared with one or several other investigators (inter-rater comparison) or with himself at different time points (intra-rater comparison) ( e1 ). If an event is very rare (such as a rare disease or an individual course of treatment), a single-case study, or a case series, are possibilities. A case series is a study on a larger patient group with a specific disease. For example, after the discovery of the AIDS virus, the Center for Disease Control (CDC) in the USA collected a case series of 1000 patients, in order to study frequent complications of this infection. The lack of a control group is a disadvantage of case series. For this reason, case series are primarily used for descriptive purposes ( 3 ).

Epidemiological studies

The main point of interest in epidemiological studies is to investigate the distribution and historical changes in the frequency of diseases and the causes for these. Analogously to clinical studies, a distinction is made between experimental and observational epidemiological studies ( 16 , 17 ).

Interventional studies are experimental in character and are further subdivided into field studies (sample from an area, such as a large region or a country) and group studies (sample from a specific group, such as a specific social or ethnic group). One example was the investigation of the iodine supplementation of cooking salt to prevent cretinism in a region with iodine deficiency. On the other hand, many interventions are unsuitable for randomized intervention studies, for ethical, social or political reasons, as the exposure may be harmful to the subjects ( 17 ).

Observational epidemiological studies can be further subdivided into cohort studies (follow-up studies), case control studies, cross-sectional studies (prevalence studies), and ecological studies (correlation studies or studies with aggregated data).

In contrast, studies with only descriptive evaluation are restricted to a simple depiction of the frequency (incidence and prevalence) and distribution of a disease within a population. The objective of the description may also be the regular recording of information (monitoring, surveillance). Registry data are also suited for the description of prevalence and incidence; for example, they are used for national health reports in Germany.

In the simplest case, cohort studies involve the observation of two healthy groups of subjects over time. One group is exposed to a specific substance (for example, workers in a chemical factory) and the other is not exposed. It is recorded prospectively (into the future) how often a specific disease (such as lung cancer) occurs in the two groups ( figure 2a ). The incidence for the occurrence of the disease can be determined for both groups. Moreover, the relative risk (quotient of the incidence rates) is a very important statistical parameter which can be calculated in cohort studies. For rare types of exposure, the general population can be used as controls ( e6 ). All evaluations naturally consider the age and gender distributions in the corresponding cohorts. The objective of cohort studies is to record detailed information on the exposure and on confounding factors, such as the duration of employment, the maximum and the cumulated exposure. One well known cohort study is the British Doctors Study, which prospectively examined the effect of smoking on mortality among British doctors over a period of decades ( e7 ). Cohort studies are well suited for detecting causal connections between exposure and the development of disease. On the other hand, cohort studies often demand a great deal of time, organization, and money. So-called historical cohort studies represent a special case. In this case, all data on exposure and effect (illness) are already available at the start of the study and are analyzed retrospectively. For example, studies of this sort are used to investigate occupational forms of cancer. They are usually cheaper ( 16 ).

Graphical depiction of a prospective cohort study (simplest case [2a]) and a retrospective case control study (2b)

In case control studies, cases are compared with controls. Cases are persons who fall ill from the disease in question. Controls are persons who are not ill, but are otherwise comparable to the cases. A retrospective analysis is performed to establish to what extent persons in the case and control groups were exposed ( figure 2b ). Possible exposure factors include smoking, nutrition and pollutant load. Care should be taken that the intensity and duration of the exposure is analyzed as carefully and in as detailed a manner as possible. If it is observed that ill people are more often exposed than healthy people, it may be concluded that there is a link between the illness and the risk factor. In case control studies, the most important statistical parameter is the odds ratio. Case control studies usually require less time and fewer resources than cohort studies ( 16 ). The disadvantage of case control studies is that the incidence rate (rate of new cases) cannot be calculated. There is also a great risk of bias from the selection of the study population ("selection bias") and from faulty recall ("recall bias") (see too the article "Avoiding Bias in Observational Studies"). Table 1 presents an overview of possible types of epidemiological study ( e8 ). Table 2 summarizes the advantages and disadvantages of observational studies ( 16 ).

1 = slight; 2 = moderate; 3 = high; N/A, not applicable.

*Individual cases may deviate from this pattern.

Selecting the correct study type is an important aspect of study design (see "Study Design in Medical Research" in volume 11/2009). However, the scientific questions can only be correctly answered if the study is planned and performed at a qualitatively high level ( e9 ). It is very important to consider or even eliminate possible interfering factors (or confounders), as otherwise the result cannot be adequately interpreted. Confounders are characteristics which influence the target parameters. Although this influence is not of primary interest, it can interfere with the connection between the target parameter and the factors that are of interest. The influence of confounders can be minimized or eliminated by standardizing the procedure, stratification ( 18 ), or adjustment ( 19 ).

The decision as to which study type is suitable to answer a specific primary research question must be based not only on scientific considerations, but also on issues related to resources (personnel and finances), hospital capacity, and practicability. Many epidemiological studies can only be implemented if there is access to registry data. The demands for planning, implementation, and statistical evaluation for observational studies should be just as high for observational studies as for experimental studies. There are particularly strict requirements, with legally based regulations (such as the Medicines Act and Good Clinical Practice), for the planning, implementation, and evaluation of clinical studies. A study protocol must be prepared for both interventional and noninterventional studies ( 6 , 13 ). The study protocol must contain information on the conditions, question to be answered (objective), the methods of measurement, the implementation, organization, study population, data management, case number planning, the biometric evaluation, and the clinical relevance of the question to be answered ( 13 ).

Important and justified ethical considerations may restrict studies with optimal scientific and statistical features. A randomized intervention study under strictly controlled conditions of the effect of exposure to harmful factors (such as smoking, radiation, or a fatty diet) is not possible and not permissible for ethical reasons. Observational studies are a possible alternative to interventional studies, even though observational studies are less reliable and less easy to control ( 17 ).

A medical study should always be published in a peer reviewed journal. Depending on the study type, there are recommendations and checklists for presenting the results. For example, these may include a description of the population, the procedure for missing values and confounders, and information on statistical parameters. Recommendations and guidelines are available for clinical studies ( 14 , 20 , e10 , e11 ), for diagnostic studies ( 21 , 22 , e12 ), and for epidemiological studies ( 23 , e13 ). Since 2004, the WHO has demanded that studies should be registered in a public registry, such as www.controlled-trials.com or www.clinicaltrials.gov . This demand is supported by the International Committee of Medical Journal Editors (ICMJE) ( 24 ), which specifies that the registration of the study before inclusion of the first subject is an essential condition for the publication of the study results ( e14 ).

When specifying the study type and study design for medical studies, it is essential to collaborate with an experienced biometrician. The quality and reliability of the study can be decisively improved if all important details are planned together ( 12 , 25 ).

Acknowledgments

Translated from the original German by Rodney A. Yeates, M.A., Ph.D.

Conflict of interest statement

The authors declare that there is no conflict of interest in the sense of the International Committee of Medical Journal Editors.

Candel (CADL) Stock Skyrockets 431% Year to Date: Here's Why

Candel Therapeutics  CADL, a clinical-stage oncology company, is focused on developing two novel therapeutics, CAN-2409 and CAN-3110, to treat a variety of cancer indications.

The company’s most advanced product candidate, CAN-2409, is an investigational adenovirus immunotherapy candidate that is being developed in separate mid to late-stage studies across three different types of cancer, including, prostate cancer, non-small cell lung cancer (NSCLC) and pancreatic cancer.

On the other hand, CAN-3110, Candel’s HSV-1-based immunotherapy candidate, is currently being evaluated in an ongoing investigator-sponsored early-stage study to treat recurrent high-grade glioma (HGG).

Year to date, shares of CADL have skyrocketed 430.6% against the industry’s 5.7% decline. Developmental and regulatory updates from the clinical program for CAN-2409 fueled the colossal stock price rally.

Image Source: Zacks Investment Research

In April, Candel reported positive interim data from the phase II study evaluating CAN-2409 plus valacyclovir (prodrug), together with standard of care (SoC) chemoradiation, followed by resection for treating borderline resectable pancreatic ductal adenocarcinoma (PDAC).

The updated interim data from the ongoing phase II study showed that experimental treatment with CAN-2409 led to notable improvements in estimated median overall survival of 28.8 months compared with only 12.5 months in the control group in borderline resectable PDAC.

Patients treated with CAN-2409 had a survival rate of 71.4% compared with only 16.7% in the control group after chemoradiation at 24 months of treatment. Moreover, the survival rate was 47.6% for patients treated with CAN-2409 compared with a mere 16.7% in the control group at 36 months.

If successfully developed, CAN-2409 could present a significant commercial opportunity for Candel. There is a high unmet medical need for effective new treatments, given the frequent recurrence and short survival with SoC chemotherapy for non-metastatic PDAC.

Last week, Candel announced positive overall survival data from a phase II study evaluating CAN-2409 plusvalacyclovir, together with SoC in patients with stage III/IV NSCLCwho are non-responsive to immune checkpoint inhibitor therapy over a prolonged period.

Data from the study showed that treatment with two administrations of CAN-2409 plus valacyclovir led to a median overall survival of 20.6 months in NSCLC patients whose disease had progressed despite receiving prior anti-PD-(L)1 treatment. The median overall survival observed upon treatment with SoC docetaxel-based chemotherapy in a similar patient population was 11.6 months.

In April, the FDA granted orphan drug designation to CAN-2409 for the treatment of PDAC, which further boosted stock price.

Per management, the orphan designation grant reaffirms the potential of Candel’s CAN-2409 to treat rare and difficult-to-treat forms of cancer and will ensure market exclusivity upon potential approval. Please note that the FDA also granted the Fast Track designation to CAN-2409 last year for the same indication.

We remind the investors that CADL’s other pipeline candidate, CAN-3110, also enjoys the FDA’s Fast Track designation in the United States for treating HGG patients to improve overall survival.

The Fast Track designation is credited with facilitating and thereby expediting the developmental timeline of drug candidates that are being developed to treat serious conditions for which there is an unmet medical need.

Candel is also evaluating CAN-2409 to treat patients with newly diagnosed, localized prostate cancer who have an intermediate or high risk for progression, as well as patients with low-to-intermediate risk, localized prostate cancer in phase III and phase II studies, respectively.

Looking forward, the company expects to report top-line data from both these studies in the fourth quarter of 2024, which should be an important catalyst for the stock.

Candel Therapeutics, Inc. Price and Consensus

Candel Therapeutics, Inc. price-consensus-chart | Candel Therapeutics, Inc. Quote

Zacks Rank and Stocks to Consider

Candel currently carries a Zacks Rank #3 (Hold).

Some better-ranked stocks from the drug/biotech industry are ALX Oncology Holdings ALXO, Annovis Bio ANVS and Entera Bio Ltd.  ENTX, each carrying a Zacks Rank #2 (Buy) at present. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

In the past 30 days, the Zacks Consensus Estimate for ALX Oncology’s 2024 loss per share has narrowed from $3.33 to $2.89. During the same period, the consensus estimate for 2025 loss per share has narrowed from $2.85 to $2.73. Year to date, shares of ALXO have lost 11.6%.

ALX Oncology beat estimates in two of the trailing four quarters and missed twice, delivering an average negative surprise of 8.83%.

In the past 30 days, the Zacks Consensus Estimate for Annovis’ 2024 loss per share has narrowed from $3.35 to $2.46. During the same period, the consensus estimate for 2025 loss per share has narrowed from $2.82 to $1.95. Year to date, shares of ANVS have plunged 61%.

ANVS beat estimates in three of the trailing four quarters and missed once, delivering an average negative surprise of 1.39%.

In the past 30 days, the Zacks Consensus Estimate for Entera Bio’s 2024 loss per share has remained constant at 25 cents. During the same period, the consensus estimate for 2025 loss per share has remained constant at 54 cents. Year to date, shares of ENTX have skyrocketed 286.7%.

ENTX’s earnings beat estimates in three of the trailing four quarters and missed once, delivering an average surprise of 6.50%.

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