literature review topic nursing

Best Nursing Research Topics for Students

What is a nursing research paper.

• What They Include
• Choosing a Topic
• Best Nursing Research Topics
• Research Paper Writing Tips

Writing a research paper is a massive task that involves careful organization, critical analysis, and a lot of time. Some nursing students are natural writers, while others struggle to select a nursing research topic, let alone write about it.

If you're a nursing student who dreads writing research papers, this article may help ease your anxiety. We'll cover everything you need to know about writing nursing school research papers and the top topics for nursing research.  

Continue reading to make your paper-writing jitters a thing of the past.

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A nursing research paper is a work of academic writing composed by a nurse or nursing student. The paper may present information on a specific topic or answer a question.

During LPN/LVN and RN programs, most papers you write focus on learning to use research databases, evaluate appropriate resources, and format your writing with APA style. You'll then synthesize your research information to answer a question or analyze a topic.

BSN , MSN , Ph.D., and DNP programs also write nursing research papers. Students in these programs may also participate in conducting original research studies.

Writing papers during your academic program improves and develops many skills, including the ability to:

• Select nursing topics for research
• Conduct effective research
• Analyze published academic literature
• Format and cite sources
• Synthesize data
• Organize and articulate findings

About Nursing Research Papers

When do nursing students write research papers.

You may need to write a research paper for any of the nursing courses you take. Research papers help develop critical thinking and communication skills. They allow you to learn how to conduct research and critically review publications.

That said, not every class will require in-depth, 10-20-page papers. The more advanced your degree path, the more you can expect to write and conduct research. If you're in an associate or bachelor's program, you'll probably write a few papers each semester or term.

Do Nursing Students Conduct Original Research?

Most of the time, you won't be designing, conducting, and evaluating new research. Instead, your projects will focus on learning the research process and the scientific method. You'll achieve these objectives by evaluating existing nursing literature and sources and defending a thesis.

However, many nursing faculty members do conduct original research. So, you may get opportunities to participate in, and publish, research articles.

Example Research Project Scenario:

In your maternal child nursing class, the professor assigns the class a research paper regarding developmentally appropriate nursing interventions for the pediatric population. While that may sound specific, you have almost endless opportunities to narrow down the focus of your writing. 

You could choose pain intervention measures in toddlers. Conversely, you can research the effects of prolonged hospitalization on adolescents' social-emotional development.

What Does a Nursing Research Paper Include?

Your professor should provide a thorough guideline of the scope of the paper. In general, an undergraduate nursing research paper will consist of:

Introduction : A brief overview of the research question/thesis statement your paper will discuss. You can include why the topic is relevant.

Body : This section presents your research findings and allows you to synthesize the information and data you collected. You'll have a chance to articulate your evaluation and answer your research question. The length of this section depends on your assignment.

Conclusion : A brief review of the information and analysis you presented throughout the body of the paper. This section is a recap of your paper and another chance to reassert your thesis.

The best advice is to follow your instructor's rubric and guidelines. Remember to ask for help whenever needed, and avoid overcomplicating the assignment!

How to Choose a Nursing Research Topic

The sheer volume of prospective nursing research topics can become overwhelming for students. Additionally, you may get the misconception that all the 'good' research ideas are exhausted. However, a personal approach may help you narrow down a research topic and find a unique angle.

Writing your research paper about a topic you value or connect with makes the task easier. Additionally, you should consider the material's breadth. Topics with plenty of existing literature will make developing a research question and thesis smoother.

Finally, feel free to shift gears if necessary, especially if you're still early in the research process. If you start down one path and have trouble finding published information, ask your professor if you can choose another topic.

The Best Research Topics for Nursing Students

You have endless subject choices for nursing research papers. This non-exhaustive list just scratches the surface of some of the best nursing research topics.

1. Clinical Nursing Research Topics

• Analyze the use of telehealth/virtual nursing to reduce inpatient nurse duties.
• Discuss the impact of evidence-based respiratory interventions on patient outcomes in critical care settings.
• Explore the effectiveness of pain management protocols in pediatric patients.

2. Community Health Nursing Research Topics

• Assess the impact of nurse-led diabetes education in Type II Diabetics.
• Analyze the relationship between socioeconomic status and access to healthcare services.

3. Nurse Education Research Topics

• Review the effectiveness of simulation-based learning to improve nursing students' clinical skills.
• Identify methods that best prepare pre-licensure students for clinical practice.
• Investigate factors that influence nurses to pursue advanced degrees.
• Evaluate education methods that enhance cultural competence among nurses.
• Describe the role of mindfulness interventions in reducing stress and burnout among nurses.

4. Mental Health Nursing Research Topics

• Explore patient outcomes related to nurse staffing levels in acute behavioral health settings.
• Assess the effectiveness of mental health education among emergency room nurses .
• Explore de-escalation techniques that result in improved patient outcomes.
• Review the effectiveness of therapeutic communication in improving patient outcomes.

5. Pediatric Nursing Research Topics

• Assess the impact of parental involvement in pediatric asthma treatment adherence.
• Explore challenges related to chronic illness management in pediatric patients.
• Review the role of play therapy and other therapeutic interventions that alleviate anxiety among hospitalized children.

6. The Nursing Profession Research Topics

• Analyze the effects of short staffing on nurse burnout .
• Evaluate factors that facilitate resiliency among nursing professionals.
• Examine predictors of nurse dissatisfaction and burnout.
• Posit how nursing theories influence modern nursing practice.

Tips for Writing a Nursing Research Paper

The best nursing research advice we can provide is to follow your professor's rubric and instructions. However, here are a few study tips for nursing students to make paper writing less painful:

Avoid procrastination: Everyone says it, but few follow this advice. You can significantly lower your stress levels if you avoid procrastinating and start working on your project immediately.

Plan Ahead: Break down the writing process into smaller sections, especially if it seems overwhelming. Give yourself time for each step in the process.

Research: Use your resources and ask for help from the librarian or instructor. The rest should come together quickly once you find high-quality studies to analyze.

Outline: Create an outline to help you organize your thoughts. Then, you can plug in information throughout the research process. 

Clear Language: Use plain language as much as possible to get your point across. Jargon is inevitable when writing academic nursing papers, but keep it to a minimum.

Cite Properly: Accurately cite all sources using the appropriate citation style. Nursing research papers will almost always implement APA style. Check out the resources below for some excellent reference management options.

Revise and Edit: Once you finish your first draft, put it away for one to two hours or, preferably, a whole day. Once you've placed some space between you and your paper, read through and edit for clarity, coherence, and grammatical errors. Reading your essay out loud is an excellent way to check for the 'flow' of the paper.

Helpful Nursing Research Writing Resources:

Purdue OWL (Online writing lab) has a robust APA guide covering everything you need about APA style and rules.

Grammarly helps you edit grammar, spelling, and punctuation. Upgrading to a paid plan will get you plagiarism detection, formatting, and engagement suggestions. This tool is excellent to help you simplify complicated sentences.

Mendeley is a free reference management software. It stores, organizes, and cites references. It has a Microsoft plug-in that inserts and correctly formats APA citations.

Don't let nursing research papers scare you away from starting nursing school or furthering your education. Their purpose is to develop skills you'll need to be an effective nurse: critical thinking, communication, and the ability to review published information critically.

Choose a great topic and follow your teacher's instructions; you'll finish that paper in no time.

Joleen Sams is a certified Family Nurse Practitioner based in the Kansas City metro area. During her 10-year RN career, Joleen worked in NICU, inpatient pediatrics, and regulatory compliance. Since graduating with her MSN-FNP in 2019, she has worked in urgent care and nursing administration. Connect with Joleen on LinkedIn or see more of her writing on her website.

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• v.26(5); 2021 Aug

Conducting integrative reviews: a guide for novice nursing researchers

Shannon dhollande.

Lecturer, School of Nursing, Midwifery & Social Sciences, CQ University Brisbane, Australia

Annabel Taylor

Professor, School of Nursing, Midwifery & Social Sciences, CQ University Brisbane, Australia

Silke Meyer

Associate Professor, School of Social Sciences, Monash University, Australia

Emergency Consultant, Emergency Department, Caboolture Hospital, Australia

Integrative reviews within healthcare promote a holistic understanding of the research topic. Structure and a comprehensive approach within reviews are important to ensure the reliability in their findings.

This paper aims to provide a framework for novice nursing researchers undertaking integrative reviews.

Established methods to form a research question, search literature, extract data, critically appraise extracted data and analyse review findings are discussed and exemplified using the authors’ own review as a comprehensive and reliable approach for the novice nursing researcher undertaking an integrative literature review.

Providing a comprehensive audit trail that details how an integrative literature review has been conducted increases and ensures the results are reproducible. The use of established tools to structure the various components of an integrative review increases robustness and readers’ confidence in the review findings.

Implications for practice

Novice nursing researchers may increase the reliability of their results by employing a framework to guide them through the process of conducting an integrative review.

A literature review is a critical analysis of published research literature based on a specified topic ( Pluye et al., 2016 ). Literature reviews identify literature then examine its strengths and weaknesses to determine gaps in knowledge ( Pluye et al. 2016 ). Literature reviews are an integral aspect of research projects; indeed, many reviews constitute a publication in themselves ( Snyder, 2019 ). There are various types of literature reviews based largely on the type of literature sourced ( Cronin et al. 2008 ). These include systematic literature reviews, traditional, narrative and integrative literature reviews ( Snyder, 2019 ). Aveyard and Bradbury-Jones (2019) found more than 35 commonly used terms to describe literature reviews. Within healthcare, systematic literature reviews initially gained traction and widespread support because of their reproducibility and focus on arriving at evidence-based conclusions that could influence practice and policy development ( Boell and Cecez-Kecmanovic, 2015 ). Yet, it became apparent that healthcare-related treatment options needed to review broader spectrums of research for treatment options to be considered comprehensive, holistic and patient orientated ( Boell and Cecez-Kecmanovic, 2015 ). Stern et al. (2014) suggest that despite the focus in healthcare on quantitative research not all pertinent questions surrounding the provision of care can be answered from this approach. To devise solutions to multidimensional problems, all forms of trustworthy evidence need to be considered ( Stern et al. 2014 ).

Integrative reviews assimilate research data from various research designs to reach conclusions that are comprehensive and reliable ( Soares et al. 2014 ). For example, an integrative review considers both qualitative and quantitative research to reach its conclusions. This approach promotes the development of a comprehensive understanding of the topic from a synthesis of all forms of available evidence ( Russell, 2005 ; Torraco, 2005 ). The strengths of an integrative review include its capacity to analyse research literature, evaluate the quality of the evidence, identify knowledge gaps, amalgamate research from various research designs, generate research questions and develop theoretical frameworks ( Russell, 2005 ). Aveyard and Bradbury-Jones (2019) suggested that integrative reviews exhibit similar characteristics to systematic reviews and may therefore be regarded as rigorous.

Integrative reviews value both qualitative and quantitative research which are built upon differing epistemological paradigms. Both types of research are vital in developing the evidence base that guides healthcare provision ( Leppäkoski and Paavilainen, 2012 ). Therefore, integrative reviews may influence policy development as their conclusions have considered a broad range of appropriate literature ( Whittemore and Knafl, 2005 ). An integrative approach to evidence synthesis allows healthcare professionals to make better use of all available evidence and apply it to the clinical practice environment ( Souza et al. 2010 ). For example, Aveyard and Bradbury-Jones (2019) found in excess of 12 different types of reviews employed to guide healthcare practice. The healthcare profession requires both quantitative and qualitative forms of research to establish the robust evidence base that enables the provision of evidence-based patient-orientated healthcare.

Integrative reviews require a specific set of skills to identify and synthesise literature ( Boell and Cecez-Kecmanovic, 2010 ). There remains a paucity of literature that provides explicit guidance to novice nursing researchers on how to conduct an integrative review and importantly how to ensure the results and conclusions are both comprehensive and reliable. Furthermore, novice nursing researchers may receive little formal training to develop the skills required to generate a comprehensive integrative review ( Boote and Beile, 2005 ). Aveyard and Bradbury-Jones (2019) also emphasised the limited literature providing guidance surrounding integrative reviews. Therefore, novice nursing researchers need to rely on published guidance to assist them. In this regard this paper, using an integrative review conducted by the authors as a case study, aims to provide a framework for novice nursing researchers conducting integrative reviews.

Developing the framework

In conducting integrative reviews, the novice nursing researcher may need to employ a framework to ensure the findings are comprehensive and reliable ( Boell and Cecez-Kecmanovic, 2010 ; Snyder, 2019 ). A framework to guide novice nursing researchers in conducting integrative reviews has been adapted by the authors and will now be described and delineated. This framework used various published literature to guide its creation, namely works by Aveyard and Bradbury-Jones (2019) , Nelson (2014), Stern et al. (2014) , Whittemore and Knafl (2005) , Pluye et al. (2009) , Moher et al., (2009) and Attride-Stirling, (2001) . The suggested framework involves seven steps ( Figure 1 ).

Integrative review framework ( Cooke et al. 2012 ; Riva et al. 2012 ).

Step 1: Write the review question

The review question acts as a foundation for an integrative study ( Riva et al. 2012 ). Yet, a review question may be difficult to articulate for the novice nursing researcher as it needs to consider multiple factors specifically, the population or sample, the interventions or area under investigation, the research design and outcomes and any benefit to the treatment ( Riva et al. 2012 ). A well-written review question aids the researcher to develop their research protocol/design and is of vital importance when writing an integrative review.

To articulate a review question there are numerous tools available to the novice nursing researcher to employ. These tools include variations on the PICOTs template (PICOT, PICO, PIO), and the Spider template. The PICOTs template is an established tool for structuring a research question. Yet, the SPIDER template has gained acceptance despite the need for further research to determine its applicability to multiple research contexts ( Cooke et al., 2012 ). Templates are recommended to aid the novice nursing researcher in effectively delineating and deconstructing the various elements within their review question. Delineation aids the researcher to refine the question and produce more targeted results within a literature search. In the case study, the review question was to: identify, evaluate and synthesise current knowledge and healthcare approaches to women presenting due to intimate partner violence (IPV) within emergency departments (ED). This review objective is delineated in the review question templates shown in Table 1 .

Comparison of elements involved with a PICOTS and SPIDER review question.

( Cooke et al. 2012 ; Riva et al. 2012 ).

Step 2: Determine the search strategy

In determining a search strategy, it is important for the novice nursing researcher to consider the databases employed, the search terms, the Boolean operators, the use of truncation and the use of subject headings. Furthermore, Nelson (2014) suggests that a detailed description of the search strategy should be included within integrative reviews to ensure readers are able to reproduce the results.

The databases employed within a search strategy need to consider the research aim and the scope of information contained within the database. Many databases vary in their coverage of specific journals and associated literature, such as conference proceedings ( Boell and Cecez-Kecmanovic, 2010 ). Therefore, the novice nursing researcher should consult several databases when conducting their searches. For example, search strategies within the healthcare field may utilise databases such as Cumulative Index to Nursing and Allied Healthcare Literature (CINAHL), Cochrane Library, Science Direct, ProQuest, Web of Science, Scopus and PsychInfo ( Cronin et al. 2008 ). These databases among others are largely considered appropriate repositories of reliable data that novice researchers may utilise when researching within healthcare. The date in which the searches are undertaken should be within the search strategy as searches undertaken after this date may generate increased results in line with the publication of further studies.

Utilising an established template to generate a research question allows for the delineation of key elements within the question as seen above. These key elements may assist the novice nursing researcher in determining the search terms they employ. Furthermore, keywords on published papers may provide the novice nursing researcher with alternative search terms, synonyms and introduce the researcher to key terminology employed within their field ( Boell and Cecez-Kecmanovic, 2010 ). For example, within the case study undertaken the search terms included among others: ‘domestic violence’, ‘domestic abuse’, ‘intimate partner violence and/or abuse’. To refine the search to the correct healthcare environment the terms ‘emergency department’ and/or ‘emergency room’ were employed. To link search terms, the researcher should consider their use of Boolean operators ‘And’ ‘Or’ and ‘Not’ and their use of truncation ( Cronin et al. 2008 ). Truncation is the shortening of words which in literature searches may increase the number of search results. Medical subject headings (MeSH) or general subject headings should be employed where appropriate and within this case study the headings included ‘nursing’, ‘domestic violence’ and ‘intimate partner violence’.

Inclusion and exclusion criteria allow the novice nursing researcher to reduce and refine the search parameters and locate the specific data they seek. Appropriate use of inclusion and exclusion criteria permits relevant data to be sourced as wider searches can produce a large amount of disparate data, whereas a search that is too narrow may result in the omission of significant findings ( Boell and Cecez-Kecmanovic, 2010 ). The novice nursing researcher needs to be aware that generating a large volume of search results may not necessarily result in relevant data being identified. Within integrative reviews there is potential for a large volume of data to be sourced and therefore time and resources required to complete the review need to be considered ( Heyvaert et al. 2017 ). The analysis and refining of a large volume of data can become a labour-intensive exercise for the novice nursing researcher ( Boell and Cecez-Kecmanovic, 2010 ).

Stern et al. (2014) suggest various elements that should be considered within inclusion/exclusion criteria:

• the type of studies included;
• the topic under exploration;
• the outcomes;
• publication language;
• the time period; and
• the methods employed.

The use of limiters or exclusion criteria are an effective method to manage the amount of time it takes to undertake searches and limit the volume of research generated. Yet, exclusion criteria may introduce biases in the search results and should therefore be used with caution and to produce specific outcomes by the novice nursing researcher ( Hammerstrøm et al. 2017 ).

Whittemore and Knafl (2005) suggest that randomised controlled trials, prospective and retrospective cohort studies, case control studies, cross sectional studies, systematic reviews and meta-analyses should all be included within the search strategy. Therefore, there are no biases based on the type of publication sourced ( Hammerstrøm et al. 2017 ).

There should be no restriction on the sample size within the studies recognising that qualitative studies generally have smaller sample sizes, and to capture the breadth of research available. There was no restriction on the date of publication within the case study as quality literature was limited. Scoping widely is an important strategy within integrative reviews to produce comprehensive results. A manual citation search of the reference list of all sourced papers was also undertaken by a member of the research team.

Literature may be excluded if those papers were published in a language foreign to the researcher with no accepted translation available. Though limiting papers based on translation availability may introduce some bias, this does ensure the review remains free from translational errors and cultural misinterpretations. In the case study, research conducted in developing countries with a markedly different healthcare service and significant resource limitations were excluded due to their lack of generalisability and clinical relevance; though this may have introduced a degree of location bias ( Nelson, 2014 ).

A peer review of the search strategy by an individual who specialises in research data searches such as a research librarian may be a viable method in which the novice healthcare researcher can ensure the search strategy is appropriate and able to generate the required data. One such tool that a novice nurse may employ is the Peer Review of the Search Strategy (PRESS) checklist. A peer review of the caste study was undertaken by a research librarian. All recommendations were incorporated into the search strategy which included removing a full text limiter, and changes to the Boolean and proximity operators.

After the search strategy has been implemented the researcher removes duplicate results and screened the retrieved publications based on their titles and abstracts. A second screening was then undertaken based on the full text of retrieved publications to remove papers that were irrelevant to the research question. Full text copies should then be obtained for critical appraisal employing validated methods.

Step 3: Critical appraisal of search results

The papers identified within the search strategy should undergo a critical appraisal to determine if they are appropriate and of sufficient quality to be included within the review. This should be conducted or reviewed by a second member of the research team, which occurred within this case study. Any discrepancies were discussed until consensus was achieved. A critical appraisal allows the novice healthcare researcher to appraise the relevance and trustworthiness of a study and, therefore, determine its applicability to their research (CASP, 2013). There are several established tools a novice nurse can employ in which to structure their critical appraisal. These include the Scoring System for Mixed-Methods Research and Mixed Studies Reviews developed by Pluye et al. (2009) and the Critical Appraisal Skills Programme (CASP, 2018) Checklists.

The review undertaken by the authors employed the scoring system for mixed-methods research and mixed-studies reviews developed by Pluye et al. (2009) . This scoring system was specifically designed for reviews employing studies from various research designs and therefore was utilised with ease ( Table 2 ).

The scoring system for mixed-methods research and mixed-studies reviews ( Pluye et al. 2009 ).

Using the CASP checklist aids the novice nursing researcher to examine the methodology of identified papers to establish validity. This critical appraisal tool contains 10 items. These items are yes or no questions that assist the researcher to determine (a) if the results of the paper are valid, (b) what the results are and (c) if it is relevant in the context of their study. For example, the checklist asks the researcher to consider the presence of a clear statement surrounding the aims of the research, and to consider why and how the research is important in regard to their topic (CASP, 2013). This checklist supports the nurse researcher to assess the validity, results and significance of research, and therefore appropriately decide on its inclusion within the review ( Krainovich-Miller et al., 2009 ).

Step 4: Summarise the search results

A summary of the results generated by literature searches is important to exemplify how comprehensive the literature is or conversely to identify if there are gaps in research. This summary should include the number of, and type of papers included within the review post limiters, screening and critical appraisal of search results. For example, within the review detailed throughout this paper the search strategy resulted in the inclusion of 25 qualitative and six quantitative papers ( Bakon et al. 2019 ). Many papers provide a summary of their search results visually in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram ( Boell and Cecez-Kecmanovic, 2015 ). PRISMA is a method of reporting that enables readers to assess the robustness of the results ( Leclercq et al. 2019 ; Moher et al. 2009 ). PRISMA promotes the transparency of the search process by delineating various items within the search process ( Leclercq et al. 2019 ; Moher et al. 2009 ). Researchers may decide how rigorously they follow this process yet should provide a rationale for any deviations ( Leclercq et al. 2019 ; Moher et al, 2009 ). Figure 2 is an example of the PRISMA flow diagram as it was applied within the case study.

Example PRISMA flow diagram ( Bakon et al. 2019 ; Moher et al. 2009 ).

Step 5: Data extraction and reduction

Data can be extracted from the critically appraised papers identified through the search strategy employing extraction tables. Within the case study data were clearly delineated, as suggested by Boell and Cecez-Kecmanovic (2010) , into extraction or comparison tables ( Table 3 ). These tables specify the authors, the date of publication, year of publication, site where the research was conducted and the key findings. Setting out the data into tables facilitates the comparison of these variables and aids the researcher to determine the appropriateness of the papers’ inclusion or exclusion within the review ( Whittemore and Knafl, 2005 ).

Example of a data extraction table.

Step 6: Analysis

Thematic analysis is widely used in integrative research ( Attride-Stirling, 2001 ). In this section we will discuss the benefits of employing a structured approach to thematic analysis including the formation of a thematic network. A thematic network is a visual diagram or depiction of the themes displaying their interconnectivity. Thematic analysis with the development of a thematic network is a way of identifying themes at various levels and depicting the observed relationships and organisation of these themes ( Attride-Stirling, 2001 ). There are numerous methods and tools available in which to conduct a thematic analysis that may be of use to the novice healthcare researcher conducting an integrative review. The approach used in a thematic analysis is important though a cursory glance at many literature reviews will reveal that many authors do not delineate the methods they employ. This includes the thematic analysis approach suggested by Thomas and Harden (2008) and the approach to thematic networking suggested by Attride-Stirling (2001) .

Thomas and Harden (2008) espouse a three-step approach to thematic analysis which includes: (a) coding, (b) organisation of codes into descriptive themes, and (c) the amalgamation of descriptive themes into analytical themes. The benefit of this approach lies in its simplicity and the ease with which a novice nurse researcher can apply the required steps. In contrast, the benefit of the approach suggested by Attride-Stirling (2001) lies in its ability to move beyond analysis and generate a visual thematic network which facilitates a critical interpretation and synthesis of the data.

Thematic networks typically depict three levels: basic themes, organising themes and global themes ( Attride-Stirling, 2001 ). The thematic network can then be developed. A thematic network is a visual depiction that appears graphically as a web like design ( Attride-Stirling, 2001 ). Thematic networks emphasise the relationships and interconnectivity of the network. It is an illustrative tool that facilitates interpretation of the data ( Attride-Stirling, 2001 ).

The benefits of employing a thematic analysis and networking within integrative reviews is the flexibility inherent within the approach, which allows the novice nursing researcher to provide a comprehensive accounting of the data ( Nowell et al. 2017 ). Thematic analysis is also an easily grasped form of data analysis that is useful for exploring various perspectives on specific topics and highlighting knowledge gaps ( Nowell et al. 2017 ). Thematic analysis and networking is also useful as a method to summarise large or diversified data sets to produce insightful conclusions ( Attride-Stirling, 2001 ; Nowell et al. 2017 ). The ability to assimilate data from various seemingly disparate perspectives may be challenging for the novice nursing researcher conducting an integrative review yet this integration of data by thematic analysis and networking was is integral.

To ensure the trustworthiness of results, novice nursing researchers need to clearly articulate each stage within the chosen method of data analysis ( Attride-Stirling, 2001 ; Nowell et al. 2017 ). The method employed in data analysis needs to be precise and exhaustively delineated ( Attride-Stirling, 2001 ; Nowell et al. 2017 ). Attride-Stirling (2001) suggests six steps within her methods of thematic analysis and networking. These steps include:

• code material;
• identify themes;
• construct thematic network;
• describe and explore the thematic network;
• summarise thematic network findings; and
• interpret patterns to identify implications.

In employing the approach suggested by Attride-Stirling (2001) within the case study the coding of specific findings within the data permitted the development of various themes ( Table 4 ). Inclusion of both quantitative and qualitative findings within the themes facilitated integration of the data which identified patterns and generated insights into the current care provided to IPV victims within ED.

Coding and theme formation.

Step 7: Conclusions and implications

A conclusion is important to remind the reader why the research topic is important. The researcher can then follow advice by Higginbottom (2015) who suggests that in drawing and writing research conclusions the researcher has an opportunity to explain the significance of the findings. The researcher may also need to explain these conclusions in light of the study limitations and parameters. Higginbottom (2015) emphasises that a conclusion is not a summary or reiteration of the results but a section which details the broader implications of the research and translates this knowledge into a format that is of use to the reader. The implications of the review findings for healthcare practice, for healthcare education and research should be considered.

Employing this structured and comprehensive framework within the case study the authors were able to determine that there remains a marked barrier in the provision of healthcare within the ED to women presenting with IPV-related injury. By employing an integrative approach multiple forms of literature were reviewed, and a considerable gap was identified. Therefore, further research may need to focus on the developing a structured healthcare protocol to aid ED clinicians to meet the needs of this vulnerable patient population.

Integrative reviews can be conducted with success when they follow a structured approach. This paper proposes a framework that novice nursing researchers can employ. Applying our stepped framework within an integrative review will strengthen the robustness of the study and facilitate its translation into policy and practice. This framework was employed by the authors to identify, evaluate and synthesise current knowledge and approaches of health professionals surrounding the care provision of women presenting due to IPV within emergency departments. The recommendations from the case study are currently being translated and implemented into the practice environment.

Key points for policy, practice and/or research

• Integrative literature reviews are required within nursing to consider elements of care provision from a holistic perspective.
• There is currently limited literature providing explicit guidance on how to undertake an integrative literature review.
• Clear delineation of the integrative literature review process demonstrates how the knowledge base was understood, organised and analysed.
• Nurse researchers may utilise this guidance to ensure the reliability of their integrative review.

Shannon Dhollande is a Lecturer, registered nurse and researcher. Her research explores the provision of emergency care to vulnerable populations.

Annabel Taylor is a Professorial Research Fellow at CQ University who with her background in social work explores methods of addressing gendered violence such as domestic violence.

Silke Meyer is an Associate Professor in Criminology and the Deputy Director of the Gender and Family Violence Prevention Centre at Monash University.

Mark Scott is an Emergency Medical Consultant with a track record in advancing emergency healthcare through implementation of evidence-based healthcare.

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics: Due to the nature of this article this article did not require ethical approval.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

Shannon Dhollande https://orcid.org/0000-0003-3181-7606

Silke Meyer https://orcid.org/0000-0003-3964-042X

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Nursing: Literature Review

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Good Place to Start: Citation Databases

Interdisciplinary Citation Databases:

A good place to start your research  is to search a research citation database to view the scope of literature available on your topic.

TIP #1: SEED ARTICLE Begin your research with a "seed article" - an article that strongly supports your research topic.  Then use a citation database to follow the studies published by finding articles which have cited that article, either because they support it or because they disagree with it.

TIP #2: SNOWBALLING Snowballing is the process where researchers will begin with a select number of articles they have identified relevant/strongly supports their topic and then search each articles' references reviewing the studies cited to determine if they are relevant to your research.

BONUS POINTS: This process also helps identify key highly cited authors within a topic to help establish the "experts" in the field.

Begin by constructing a focused research question to help you then convert it into an effective search strategy.

• Identify keywords or synonyms
• Type of study/resources
• Which database(s) to search
• Asking a Good Question (PICO)
• PICO - AHRQ
• PICO - Worksheet
• What Is a PICOT Question?

Seminal Works: Search Key Indexing/Citation Databases

• Google Scholar
• Web of Science

TIP – How to Locate Seminal Works

• DO NOT: Limit by date range or you might overlook the seminal works
• DO: Look at highly cited references (Seminal articles are frequently referred to “cited” in the research)
• DO: Search citation databases like Scopus, Web of Science and Google Scholar

Web Resources

What is a literature review?

A literature review is a comprehensive and up-to-date overview of published information on a subject area. Conducting a literature review demands a careful examination of a body of literature that has been published that helps answer your research question (See PICO). Literature reviewed includes scholarly journals, scholarly books, authoritative databases, primary sources and grey literature.

A literature review attempts to answer the following:

• What is known about the subject?
• What is the chronology of knowledge about my subject?
• Are there any gaps in the literature?
• Is there a consensus/debate on issues?
• Create a clear research question/statement
• Define the scope of the review include limitations (i.e. gender, age, location, nationality...)
• Search existing literature including classic works on your topic and grey literature
• Evaluate results and the evidence (Avoid discounting information that contradicts your research)
• Track and organize references
• How to conduct an effective literature search.
• Social Work Literature Review Guidelines (OWL Purdue Online Writing Lab)

What is PICO?

The PICO model can help you formulate a good clinical question. Sometimes it's referred to as PICO-T, containing an optional 5th factor. 

Search Example

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Nursing: How to Write a Literature Review

• Traditional or Narrative Literature Review

Getting started

1. start with your research question, 2. search the literature, 3. read & evaluate, 4. finalize results, 5. write & revise, brainfuse online tutoring and writing review.

• RESEARCH HELP

The best way to approach your literature review is to break it down into steps.  Remember, research is an iterative process, not a linear one.  You will revisit steps and revise along the way.  Get started with the handout, information, and tips from various university Writing Centers below that provides an excellent overview.  Then move on to the specific steps recommended on this page.

• UNC- Chapel Hill Writing Center Literature Review Handout, from the University of North Carolina at Chapel Hill.
• University of Wisconsin-Madison Writing Center Learn how to write a review of literature, from the University of Wisconsin-Madison.
• University of Toronto-- Writing Advice The Literature Review: A few tips on conducting it, from the University of Toronto.
• Begin with a topic.
• Understand the topic. 
• Familiarize yourself with the terminology.  Note what words are being used and keep track of these for use as database search keywords. 
• See what research has been done on this topic before you commit to the topic.  Review articles can be helpful to understand what research has been done .
• Develop your research question.  (see handout below)
• How comprehensive should it be? 
• Is it for a course assignment or a dissertation? 
• How many years should it cover?
• Developing a good nursing research question Handout. Reviews PICO method and provides search tips.

Your next step is to construct a search strategy and then locate & retrieve articles.

•  There are often 2-4 key concepts in a research question.
• Search for primary sources (original research articles.)
• These are based on the key concepts in your research question.
• Remember to consider synonyms and related terms.
• Which databases to search?
• What limiters should be applied (peer-reviewed, publication date, geographic location, etc.)?

Review articles (secondary sources)

Use to identify literature on your topic, the way you would use a bibliography.  Then locate and retrieve the original studies discussed in the review article. Review articles are considered secondary sources.

• Once you have some relevant articles, review reference lists to see if there are any useful articles.
• Which articles were written later and have cited some of your useful articles?  Are these, in turn, articles that will be useful to you? 
• Keep track of what terms you used and what databases you searched. 
• Use database tools such as save search history in EBSCO to help.
• Keep track of the citations for the articles you will be using in your literature review. 
• Use RefWorks or another method of tracking this information. 
• Database Search Strategy Worksheet Handout. How to construct a search.
• TUTORIAL: How to do a search based on your research question This is a self-paced, interactive tutorial that reviews how to construct and perform a database search in CINAHL.

The next step is to read, review, and understand the articles.

• Start by reviewing abstracts. 
• Make sure you are selecting primary sources (original research articles).
• Note any keywords authors report using when searching for prior studies.
• You will need to evaluate and critique them and write a synthesis related to your research question.
• Consider using a matrix to organize and compare and contrast the articles . 
• Which authors are conducting research in this area?  Search by author.  
• Are there certain authors’ whose work is cited in many of your articles?  Did they write an early, seminal article that is often cited?
• Searching is a cyclical process where you will run searches, review results, modify searches, run again, review again, etc. 
• Critique articles.  Keep or exclude based on whether they are relevant to your research question.
• When you have done a thorough search using several databases plus Google Scholar, using appropriate keywords or subject terms, plus author’s names, and you begin to find the same articles over and over.
• Remember to consider the scope of your project and the length of your paper.  A dissertation will have a more exhaustive literature review than an 8 page paper, for example.
• What are common findings among each group or where do they disagree? 
• Identify common themes. Identify controversial or problematic areas in the research. 
• Use your matrix to organize this.
• Once you have read and re-read your articles and organized your findings, you are ready to begin the process of writing the literature review.

2. Synthesize.  (see handout below)

• Include a synthesis of the articles you have chosen for your literature review.
• A literature review is NOT a list or a summary of what has been written on a particular topic. 
• It analyzes the articles in terms of how they relate to your research question. 
• While reading, look for similarities and differences (compare and contrast) among the articles.  You will create your synthesis from this.
• Synthesis Examples Handout. Sample excerpts that illustrate synthesis.

Regis Online students have access to Brainfuse. Brainfuse is an online tutoring service available through a link in Moodle. Meet with a tutor in a live session or submit your paper for review.

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Literature Review Overview

What is a Literature Review? Why Are They Important?

A literature review is important because it presents the "state of the science" or accumulated knowledge on a specific topic. It summarizes, analyzes, and compares the available research, reporting study strengths and weaknesses, results, gaps in the research, conclusions, and authors’ interpretations.

Tips and techniques for conducting a literature review are described more fully in the subsequent boxes:

• Literature review steps
• Strategies for organizing the information for your review
• Literature reviews sections
• In-depth resources to assist in writing a literature review
• Templates to start your review
• Literature review examples

Literature Review Steps

Graphic used with permission: Torres, E. Librarian, Hawai'i Pacific University

1. Choose a topic and define your research question

• Try to choose a topic of interest. You will be working with this subject for several weeks to months.
• Ideas for topics can be found by scanning medical news sources (e.g MedPage Today), journals / magazines, work experiences, interesting patient cases, or family or personal health issues.
• Do a bit of background reading on topic ideas to familiarize yourself with terminology and issues. Note the words and terms that are used.
• Develop a focused research question using PICO(T) or other framework (FINER, SPICE, etc - there are many options) to help guide you.
• Run a few sample database searches to make sure your research question is not too broad or too narrow.
• If possible, discuss your topic with your professor. 

2. Determine the scope of your review

The scope of your review will be determined by your professor during your program. Check your assignment requirements for parameters for the Literature Review.

• How many studies will you need to include?
• How many years should it cover? (usually 5-7 depending on the professor)
• For the nurses, are you required to limit to nursing literature?

3. Develop a search plan

• Determine which databases to search. This will depend on your topic. If you are not sure, check your program specific library website (Physician Asst / Nursing / Health Services Admin) for recommendations.
• Create an initial search string using the main concepts from your research (PICO, etc) question. Include synonyms and related words connected by Boolean operators
• Contact your librarian for assistance, if needed.

4. Conduct searches and find relevant literature

• Keep notes as you search - tracking keywords and search strings used in each database in order to avoid wasting time duplicating a search that has already been tried
• Read abstracts and write down new terms to search as you find them
• Check MeSH or other subject headings listed in relevant articles for additional search terms
• Scan author provided keywords if available
• Check the references of relevant articles looking for other useful articles (ancestry searching)
• Check articles that have cited your relevant article for more useful articles (descendancy searching). Both PubMed and CINAHL offer Cited By links
• Revise the search to broaden or narrow your topic focus as you peruse the available literature
• Conducting a literature search is a repetitive process. Searches can be revised and re-run multiple times during the process.
• Track the citations for your relevant articles in a software citation manager such as RefWorks, Zotero, or Mendeley

5. Review the literature

• Read the full articles. Do not rely solely on the abstracts. Authors frequently cannot include all results within the confines of an abstract. Exclude articles that do not address your research question.
• While reading, note research findings relevant to your project and summarize. Are the findings conflicting? There are matrices available than can help with organization. See the Organizing Information box below.
• Critique / evaluate the quality of the articles, and record your findings in your matrix or summary table. Tools are available to prompt you what to look for. (See Resources for Appraising a Research Study box on the HSA, Nursing , and PA guides )
• You may need to revise your search and re-run it based on your findings.

6. Organize and synthesize

• Compile the findings and analysis from each resource into a single narrative.
• Using an outline can be helpful. Start broad, addressing the overall findings and then narrow, discussing each resource and how it relates to your question and to the other resources.
• Cite as you write to keep sources organized.
• Write in structured paragraphs using topic sentences and transition words to draw connections, comparisons, and contrasts.
• Don't present one study after another, but rather relate one study's findings to another. Speak to how the studies are connected and how they relate to your work.

Organizing Information

Options to assist in organizing sources and information :

1. Synthesis Matrix

• helps provide overview of the literature
• information from individual sources is entered into a grid to enable writers to discern patterns and themes
• article summary, analysis, or results
• thoughts, reflections, or issues
• each reference gets its own row
• mind maps, concept maps, flowcharts
• at top of page record PICO or research question
• record major concepts / themes from literature
• list concepts that branch out from major concepts underneath - keep going downward hierarchically, until most specific ideas are recorded
• enclose concepts in circles and connect the concept with lines - add brief explanation as needed

3. Summary Table

• information is recorded in a grid to help with recall and sorting information when writing
• allows comparing and contrasting individual studies easily
• purpose of study
• methodology (study population, data collection tool)

Efron, S. E., & Ravid, R. (2019). Writing the literature review : A practical guide . Guilford Press.

Literature Review Sections

• Lit reviews can be part of a larger paper / research study or they can be the focus of the paper
• Lit reviews focus on research studies to provide evidence
• New topics may not have much that has been published

* The sections included may depend on the purpose of the literature review (standalone paper or section within a research paper)

Standalone Literature Review (aka Narrative Review):

• presents your topic or PICO question
• includes the why of the literature review and your goals for the review.
• provides background for your the topic and previews the key points
• Narrative Reviews: tmay not have an explanation of methods.
• include where the search was conducted (which databases) what subject terms or keywords were used, and any limits or filters that were applied and why - this will help others re-create the search
• describe how studies were analyzed for inclusion or exclusion
• review the purpose and answer the research question
• thematically - using recurring themes in the literature
• chronologically - present the development of the topic over time
• methodological - compare and contrast findings based on various methodologies used to research the topic (e.g. qualitative vs quantitative, etc.)
• theoretical - organized content based on various theories
• provide an overview of the main points of each source then synthesize the findings into a coherent summary of the whole
• present common themes among the studies
• compare and contrast the various study results
• interpret the results and address the implications of the findings
• do the results support the original hypothesis or conflict with it
• provide your own analysis and interpretation (eg. discuss the significance of findings; evaluate the strengths and weaknesses of the studies, noting any problems)
• discuss common and unusual patterns and offer explanations
•  stay away from opinions, personal biases and unsupported recommendations
• summarize the key findings and relate them back to your PICO/research question
• note gaps in the research and suggest areas for further research
• this section should not contain "new" information that had not been previously discussed in one of the sections above
• provide a list of all the studies and other sources used in proper APA 7

Literature Review as Part of a Research Study Manuscript:

• Compares the study with other research and includes how a study fills a gap in the research.
• Focus on the body of the review which includes the synthesized Findings and Discussion

Literature Reviews vs Systematic Reviews

Systematic Reviews are NOT the same as a Literature Review:

Literature Reviews:

• Literature reviews may or may not follow strict systematic methods to find, select, and analyze articles, but rather they selectively and broadly review the literature on a topic
• Research included in a Literature Review can be "cherry-picked" and therefore, can be very subjective

Systematic Reviews:

• Systemic reviews are designed to provide a comprehensive summary of the evidence for a focused research question
• rigorous and strictly structured, using standardized reporting guidelines (e.g. PRISMA, see link below)
• uses exhaustive, systematic searches of all relevant databases
• best practice dictates search strategies are peer reviewed
• uses predetermined study inclusion and exclusion criteria in order to minimize bias
• aims to capture and synthesize all literature (including unpublished research - grey literature) that meet the predefined criteria on a focused topic resulting in high quality evidence

Literature Review Examples

• Breastfeeding initiation and support: A literature review of what women value and the impact of early discharge (2017). Women and Birth : Journal of the Australian College of Midwives
• Community-based participatory research to promote healthy diet and nutrition and prevent and control obesity among African-Americans: A literature review (2017). Journal of Racial and Ethnic Health Disparities

• Vitamin D deficiency in individuals with a spinal cord injury: A literature review (2017). Spinal Cord

Resources for Writing a Literature Review

These sources have been used in developing this guide.

Resources Used on This Page

Aveyard, H. (2010). Doing a literature review in health and social care : A practical guide . McGraw-Hill Education.

Purdue Online Writing Lab. (n.d.). Writing a literature review . Purdue University. https://owl.purdue.edu/owl/research_and_citation/conducting_research/writing_a_literature_review.html

Torres, E. (2021, October 21). Nursing - graduate studies research guide: Literature review. Hawai'i Pacific University Libraries. Retrieved January 27, 2022, from https://hpu.libguides.com/c.php?g=543891&p=3727230

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What is a Literature Review?

Key questions for a literature review, examples of literature reviews, useful links, evidence matrix for literature reviews.

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The Scholarly Conversation

A literature review provides an overview of previous research on a topic that critically evaluates, classifies, and compares what has already been published on a particular topic. It allows the author to synthesize and place into context the research and scholarly literature relevant to the topic. It helps map the different approaches to a given question and reveals patterns. It forms the foundation for the author’s subsequent research and justifies the significance of the new investigation.

A literature review can be a short introductory section of a research article or a report or policy paper that focuses on recent research. Or, in the case of dissertations, theses, and review articles, it can be an extensive review of all relevant research.

• The format is usually a bibliographic essay; sources are briefly cited within the body of the essay, with full bibliographic citations at the end.
• The introduction should define the topic and set the context for the literature review. It will include the author's perspective or point of view on the topic, how they have defined the scope of the topic (including what's not included), and how the review will be organized. It can point out overall trends, conflicts in methodology or conclusions, and gaps in the research.
• In the body of the review, the author should organize the research into major topics and subtopics. These groupings may be by subject, (e.g., globalization of clothing manufacturing), type of research (e.g., case studies), methodology (e.g., qualitative), genre, chronology, or other common characteristics. Within these groups, the author can then discuss the merits of each article and analyze and compare the importance of each article to similar ones.
• The conclusion will summarize the main findings, make clear how this review of the literature supports (or not) the research to follow, and may point the direction for further research.
• The list of references will include full citations for all of the items mentioned in the literature review.

A literature review should try to answer questions such as

• Who are the key researchers on this topic?
• What has been the focus of the research efforts so far and what is the current status?
• How have certain studies built on prior studies? Where are the connections? Are there new interpretations of the research?
• Have there been any controversies or debate about the research? Is there consensus? Are there any contradictions?
• Which areas have been identified as needing further research? Have any pathways been suggested?
• How will your topic uniquely contribute to this body of knowledge?
• Which methodologies have researchers used and which appear to be the most productive?
• What sources of information or data were identified that might be useful to you?
• How does your particular topic fit into the larger context of what has already been done?
• How has the research that has already been done help frame your current investigation ?

Example of a literature review at the beginning of an article: Forbes, C. C., Blanchard, C. M., Mummery, W. K., & Courneya, K. S. (2015, March). Prevalence and correlates of strength exercise among breast, prostate, and colorectal cancer survivors . Oncology Nursing Forum, 42(2), 118+. Retrieved from http://go.galegroup.com.sonoma.idm.oclc.org/ps/i.do?p=HRCA&sw=w&u=sonomacsu&v=2.1&it=r&id=GALE%7CA422059606&asid=27e45873fddc413ac1bebbc129f7649c Example of a comprehensive review of the literature: Wilson, J. L. (2016). An exploration of bullying behaviours in nursing: a review of the literature.   British Journal Of Nursing ,  25 (6), 303-306. For additional examples, see:

Galvan, J., Galvan, M., & ProQuest. (2017). Writing literature reviews: A guide for students of the social and behavioral sciences (Seventh ed.). [Electronic book]

Pan, M., & Lopez, M. (2008). Preparing literature reviews: Qualitative and quantitative approaches (3rd ed.). Glendale, CA: Pyrczak Pub. [ Q180.55.E9 P36 2008]

• Write a Literature Review (UCSC)
• Literature Reviews (Purdue)
• Literature Reviews: overview (UNC)
• Review of Literature (UW-Madison)

The  Evidence Matrix  can help you  organize your research  before writing your lit review.  Use it to  identify patterns  and commonalities in the articles you have found--similar methodologies ?  common  theoretical frameworks ? It helps you make sure that all your major concepts covered. It also helps you see how your research fits into the context  of the overall topic.

• Evidence Matrix Special thanks to Dr. Cindy Stearns, SSU Sociology Dept, for permission to use this Matrix as an example.
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How to Search

Need more articles, but can't seem to find the right ones? Try these techniques!

Backwards searching: Once you find a relevant article, check the reference list at the end of the article. This will help you find other pertinent articles. 

Forward searching : Once you find a relevant article, look at whether it has been cited in more-recent research. If a researcher cited it, it is likely that their paper will also relate to your topic. ResearchGate is a community for students and researchers. It lists where each of their publications have been cited, if at all. This can be found under the "citations" tab that pops up when you click on any publication. 

When stuck, ask yourself, "What else is related to my topic?"

Get creative! You might find useful literature that you did not initially anticipate.

Fonseca, M. (2013, November 4) 5 tips to write a great literature review. https://www.editage.com/insights/5-tips-to-write-a-great-literature-review?refer=scroll-to-1-article&refer-type=article

What is a Literature Review?

"A literature review is a critical summary of all the published works on a particular topic" (Fonseca, 2013). A literature review provides background for your paper by quickly bringing the reader up-to-date on relevant findings, controversies, and dilemmas. It is the author's chance to "set the scene" and demonstrate why their topic is of interest to academia. In your literature review, you will describe "where your project comes from and how it fits in with existing knowledge" (Lloyd, 2017-2018). Further, you will provide "an argument for why your project makes a valuable contribution" (Lloyd, 2017-2018).

References: 

Lloyd, C.(2017-2018). Literature reviews for sociology senior theses . [PowerPoint Slides]. https://socthesis.fas.harvard.edu/files/socseniorthesis/files/pres-litreview.pdf

Step One: Define Your Research Question

What are you trying to determine for your literature review? What specifically do you want to learn more about? Choose a topic that you are genuinely interested in. Next, conduct a broad search on it. Determine what trending and popular research is available, then narrow your topic down. You can refine it by one or more of the following:

• Geographic location
• Time period
• Discipline/field of study, etc.

Research terms will help define your question.

• A broad question might be something like: What is the homeless population like?
• A narrow and specific question may include: What social and political factors have affected the growth of the middle-aged homeless population in Toronto within the past five years?

Once you have determined an appropriate research question/topic, move on to planning your approach.

Dermody, K., Literature Reviews. (2020, January 23). Retrieved from https://learn.library.ryerson.ca/literaturereview.

Step Two: Plan Your Approach 

After you have landed a research question, ask yourself "Which specific terms will I use, and where am I going to begin?" Determine what kind of literature you want to look at, whether it be journal articles, books, electronic resources, newspapers, or even other literature reviews on similar topics.

Your keywords are the main concepts or ideas of your paper.  For example, the keywords for a paper on “youth employment in Canada” would be:

Use synonyms: Often there are multiple ways to express the same concept. Make sure to use synonyms in your research. For instance, "employment" can be researched as:

Lastly, use “ AND ” and “ OR .” By bridging your truncated keywords and synonyms with the capitalized search words “AND” and “OR” (known as Boolean operators), you can search for multiple concepts effectively. For more information, visit the "electronic resources" tab of this research guide. There is a box on Boolean operators. 

Step Four: Analyze Material

When searching for material, it is important to analyze your sources for credibility, accuracy, currency, and authenticity. Ask these questions when analyzing a source:

• What is the purpose of the work?
• How current is it?
• Who is the author? 
• What are the author's biases?
• Is this work peer reviewed? 
• How accurate is this information? What facts/empirical evidence support it?
• What time frame are you looking at for your literature review, and does the work fall within that range?

Step Five: Manage Your Results 

After analyzing your research and determining what sources you want to use, it's important to keep track of what you have looked through. Keep a list of the following:

• What searches you have completed.
• Which ones were successful and unsuccessful.
• What databases you used.
• What sources you want to use for your literature review.
• What else you may want to search for next.

You can do this using software such as Zotero , Mendeley , and EndNote .

Congratulations! You are making progress towards an exceptional literature review.

Literature Review vs. Annotated Bibliography  Both a literature review (A.K.A. literature synthesis) and an annotated bibliography summarize the existing body of knowledge on a given topic.

What is the difference between a literature review and an annotated bibliography?  Unlike literature reviews, annotated bibliographies summarize entire research articles. An annotated bibliography looks like this:

Annotated Bibliography

•    Summarizes each article separately.

o    First, students discuss article one, then two, etc.  o    Topic: Blood Donation

• Paragraph 1: Bonnie and Clyde (2019) wrote "this" on blood donation.
• Paragraph 2: Rose and Jack (1997) wrote "this" on blood donation.
• Paragraph 3: Mary-Kate and Ashley (2001) wrote "this" on blood donation.
• Result: Multiple summaries of individual research articles (Lloyd, 2017-2018).

•    Describes the existing body of knowledge by integrating and synthesizing the literature to create something new.

o     Topic: Blood Donation

• Paragraph 1: Information/research findings on red blood cells pulled from multiple sources.
• Paragraph 2: Information/research findings on platelets pulled from multiple sources.
• Paragraph 3: Information/research findings on white blood cells pulled from multiple sources.
• Paragraph 4: Information/research findings on the drawbacks of donating blood from multiple sources (Lloyd, 2017-2018).
• Result: The author points out "themes, concepts, gaps and disagreements" between articles (Hofer, Hanick & Townsend, 2019, p. 216). Students use these to describe the existing body of knowledge on their topic one concept at a time. 

References:

Hofer, A. R., Hanick S. L., & Townsend, L. (2019). Designing activities for conceptual teaching. Transforming information literacy instruction: Threshold concepts in theory and practice. (p. 209-224). Libraries Unlimited.

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What are Systematic Reviews? (3 minutes, 24 second YouTube Video)

Systematic Literature Reviews: Steps & Resources

These steps for conducting a systematic literature review are listed below . 

Also see subpages for more information about:

• The different types of literature reviews, including systematic reviews and other evidence synthesis methods
• Tools & Tutorials

Literature Review & Systematic Review Steps

• Develop a Focused Question
• Scope the Literature  (Initial Search)
• Refine & Expand the Search
• Limit the Results
• Download Citations
• Abstract & Analyze
• Create Flow Diagram
• Synthesize & Report Results

1. Develop a Focused   Question 

Consider the PICO Format: Population/Problem, Intervention, Comparison, Outcome

Focus on defining the Population or Problem and Intervention (don't narrow by Comparison or Outcome just yet!)

"What are the effects of the Pilates method for patients with low back pain?"

Tools & Additional Resources:

• PICO Question Help
• Stillwell, Susan B., DNP, RN, CNE; Fineout-Overholt, Ellen, PhD, RN, FNAP, FAAN; Melnyk, Bernadette Mazurek, PhD, RN, CPNP/PMHNP, FNAP, FAAN; Williamson, Kathleen M., PhD, RN Evidence-Based Practice, Step by Step: Asking the Clinical Question, AJN The American Journal of Nursing : March 2010 - Volume 110 - Issue 3 - p 58-61 doi: 10.1097/01.NAJ.0000368959.11129.79

2. Scope the Literature

A "scoping search" investigates the breadth and/or depth of the initial question or may identify a gap in the literature. 

Eligible studies may be located by searching in:

• Background sources (books, point-of-care tools)
• Article databases
• Trial registries
• Grey literature
• Cited references
• Reference lists

When searching, if possible, translate terms to controlled vocabulary of the database. Use text word searching when necessary.

Use Boolean operators to connect search terms:

• Combine separate concepts with AND  (resulting in a narrower search)
• Connecting synonyms with OR  (resulting in an expanded search)

Search:  pilates AND ("low back pain"  OR  backache )

Video Tutorials - Translating PICO Questions into Search Queries

• Translate Your PICO Into a Search in PubMed (YouTube, Carrie Price, 5:11) 
• Translate Your PICO Into a Search in CINAHL (YouTube, Carrie Price, 4:56)

3. Refine & Expand Your Search

Expand your search strategy with synonymous search terms harvested from:

• database thesauri
• reference lists
• relevant studies

Example: 

(pilates OR exercise movement techniques) AND ("low back pain" OR backache* OR sciatica OR lumbago OR spondylosis)

As you develop a final, reproducible strategy for each database, save your strategies in a:

• a personal database account (e.g., MyNCBI for PubMed)
• Log in with your NYU credentials
• Open and "Make a Copy" to create your own tracker for your literature search strategies

4. Limit Your Results

Use database filters to limit your results based on your defined inclusion/exclusion criteria.  In addition to relying on the databases' categorical filters, you may also need to manually screen results.  

• Limit to Article type, e.g.,:  "randomized controlled trial" OR multicenter study
• Limit by publication years, age groups, language, etc.

NOTE: Many databases allow you to filter to "Full Text Only".  This filter is  not recommended . It excludes articles if their full text is not available in that particular database (CINAHL, PubMed, etc), but if the article is relevant, it is important that you are able to read its title and abstract, regardless of 'full text' status. The full text is likely to be accessible through another source (a different database, or Interlibrary Loan).  

• Filters in PubMed
• CINAHL Advanced Searching Tutorial

5. Download Citations

Selected citations and/or entire sets of search results can be downloaded from the database into a citation management tool. If you are conducting a systematic review that will require reporting according to PRISMA standards, a citation manager can help you keep track of the number of articles that came from each database, as well as the number of duplicate records.

In Zotero, you can create a Collection for the combined results set, and sub-collections for the results from each database you search.  You can then use Zotero's 'Duplicate Items" function to find and merge duplicate records.

• Citation Managers - General Guide

6. Abstract and Analyze

• Migrate citations to data collection/extraction tool
• Screen Title/Abstracts for inclusion/exclusion
• Screen and appraise full text for relevance, methods, 
• Resolve disagreements by consensus

Covidence is a web-based tool that enables you to work with a team to screen titles/abstracts and full text for inclusion in your review, as well as extract data from the included studies.

• Covidence Support
• Critical Appraisal Tools
• Data Extraction Tools

7. Create Flow Diagram

The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) flow diagram is a visual representation of the flow of records through different phases of a systematic review.  It depicts the number of records identified, included and excluded.  It is best used in conjunction with the PRISMA checklist .

Example from: Stotz, S. A., McNealy, K., Begay, R. L., DeSanto, K., Manson, S. M., & Moore, K. R. (2021). Multi-level diabetes prevention and treatment interventions for Native people in the USA and Canada: A scoping review. Current Diabetes Reports, 2 (11), 46. https://doi.org/10.1007/s11892-021-01414-3

• PRISMA Flow Diagram Generator (ShinyApp.io, Haddaway et al. )
• PRISMA Diagram Templates  (Word and PDF)
• Make a copy of the file to fill out the template
• Image can be downloaded as PDF, PNG, JPG, or SVG
• Covidence generates a PRISMA diagram that is automatically updated as records move through the review phases

8. Synthesize & Report Results

There are a number of reporting guideline available to guide the synthesis and reporting of results in systematic literature reviews.

It is common to organize findings in a matrix, also known as a Table of Evidence (ToE).

• Reporting Guidelines for Systematic Reviews
• Download a sample template of a health sciences review matrix  (GoogleSheets)

Steps modified from: 

Cook, D. A., & West, C. P. (2012). Conducting systematic reviews in medical education: a stepwise approach.   Medical Education , 46 (10), 943–952.

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What is a literature review?

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• Go to LibrarySearch This link opens in a new window

So you have been asked to complete a literature review, but what is a literature review?

A literature review is a piece of research which aims to address a specific research question. It is a comprehensive summary and analysis of existing literature. The literature itself should be the main topic of discussion in your review. You want the results and themes to speak for themselves to avoid any bias.

The first step is to decide on a topic. Here are some elements to consider when deciding upon a topic:

• Choose a topic which you are interested in, you will be looking at a lot of research surrounding that area so you want to ensure it is something that interests you. 
• Draw on your own experiences, think about your placement or your workplace.
• Think about why the topic is worth investigating.  

Once you have decided on a topic, it is a good practice to carry out an initial scoping search.

This requires you to do a quick search using  LibrarySearch  or  Google Scholar  to ensure that there is research on your topic. This is a preliminary step to your search to check what literature is available before deciding on your question. 

The research question framework elements can also be used as keywords.

• Think about who the population/ sample group. Are you looking for a particular age group, ethnicity, cultural background, gender, health issue etc.
• What is the intervention/issue you want to know more about? This could be a particular type of medication, education, therapeutic technique etc. 
• Do you have a particular context in mind? This could relate to a community setting, hospital, ward etc. 

It is important to remember that databases will only ever search for the exact term you put in, so don't panic if you are not getting the results you hoped for. Think about alternative words that could be used for each keyword to build upon your search. 

Build your search by thinking about about synonyms, specialist language, spellings, acronyms, abbreviations for each keyword that you have.

Inclusion & Exclusion Criteria

Your inclusion and exclusion criteria is also an important step in the literature review process. It allows you to be transparent in how you have  ended up with your final articles. 

Your inclusion/exclusion criteria is completely dependent on your chosen topic. Use your inclusion and exclusion criteria to select your articles, it is important not to cherry pick but to have a reason as to why you have selected that particular article. 

• Search Planning Template Use this template to plan your search strategy.

Once you have thought about your keywords and alternative keywords, it is time to think about how to combine them to form your search strategy. Boolean operators instruct the database how your terms should interact with one another. 

Boolean Operators

• OR can be used to combine your keywords and alternative terms. For example "Social Media OR Twitter". When using OR we are informing the database to bring articles continuing either of those terms as they are both relevant so we don't mind which appears in our article. 
• AND can be used to combine two or more concepts. For example "Social Media AND Anxiety". When using AND we are informing the database that we need both of the terms in our article in order for it to be relevant.
• Truncation can be used when there are multiple possible word endings. For example Nurs* will find Nurse, Nurses and Nursing. 
• Double quotation marks can be used to allow for phrase searching. This means that if you have two or more words that belong together as a phrase the database will search for that exact phrase rather than words separately.  For example "Social Media"

Don't forget the more ORs you use the broader your search becomes, the more ANDs you use the narrower your search becomes. 

One of the databases you will be using is EBSCOHost Research Databases. This is a platform which searches through multiple databases so allows for a comprehensive search. The short video below covers how to access and use EBSCO. 

A reference management software will save you a lot of time especially when you are looking at lots of different articles. 

We provide support for EndNote and Mendeley. The video below covers how to install and use Mendeley. 

Consider using a research question framework. A framework will ensure that your question is specific and answerable.

There are different frameworks available depending on what type of research you are interested in.

Population - Who is the question focussed on? This could relate to staff, patients, an age group, an ethnicity etc.

Intervention - What is the question focussed on? This could be a certain type of medication, therapeutic technique etc. 

Comparison/Context - This may be with our without the intervention or it may be concerned with the context for example where is the setting of your question? The hospital, ward, community etc?

Outcome - What do you hope to accomplish or improve etc.

Sample - as this is qualitative research sample is preferred over patient so that it is not generalised. 

Phenomenon of Interest - reasons for behaviour, attitudes, beliefs and decisions.

Design - the form of research used. 

Evaluation - the outcomes.

Research type -qualitative, quantitative or mixed methods.  

All frameworks help you to be specific, but don't worry if your question doesn't fit exactly into a framework. 

There are many critical appraisal tools or books you can use to assess the credibility of a research paper but these are a few we would recommend in the library. Your tutor may be able to advise you of others or some that are more suitable for your topic.

Critical Appraisal Skills Programme (CASP)

CASP is a well-known critical appraisal website that has checklists for a wide variety of study types. You will see it frequently used by practitioners.

Understanding Health Research

This is a brand-new, interactive resource that guides you through appraising a research paper, highlighting key areas you should consider when appraising evidence.

Greenhalgh, T. (2014) How to read a paper: The basics of evidence-based medicine . 5 th edn. Chichester: Wiley

Greenhalgh’s book is a classic in critical appraisal. Whilst you don’t need to read this book cover-to-cover, it can be useful to refer to its specific chapters on how to assess different types of research papers. We have copies available in the library!

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Literature Review

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A literature review is an essay or part of an essay that summarizes and analyzes research in a particular discipline. It assess the literature by reviewing a large body of studies on a given subject matter. It summarizes by pointing out the main findings, linking together the numerous studies and explaining how they fit into the overall academic discussion on that subject. It critically analyzes the literature by pointing out the areas of weakness, expansion, and contention. 

Literature Review Sections:

• Introduction: indicates the general state of the literature on a given subject.
• Methodology: states  where (databases), how (what subject terms used on searches), and what (parameters of studies that were included); so others may recreate the searches and explain the reasoning behind the selection of those studies.
• Findings: summary of the major findings in that subject.
• Discussion: a general progression from broader studies to more focused studies.
• Conclusion: for each major section that again notes the overall state of the research, albeit with a focus on the major synthesized conclusions, problems in the research, and even possible avenues for further research.
• References: a list of all the studies using proper citation style. 

Literature Review Tips:

• Beware of stating your own opinions or personal recommendations (unless you have evidence to support such claims).
• Provide proper references to research studies.
• Focus on research studies to provide evidence and the primary purpose of the literature review.
• Connect research studies with the overall conversation on the subject.
• Have a search strategy planner and log to keep you focused.

Literature reviews are not a book reports or commentaries; make sure to stay focused, organized, and free of personal biases or unsubstantiated recommendations.

Literature Review Examples:

• Lemetti, T., Stolt, M., Rickard, N., & Suhonen, R. (2015). Collaboration between hospital and primary care nurses: a literature review. International Nursing Review , 62 (2), 248-266. doi:10.1111/inr.12147  

1. Choose a topic and define your research question.

Your literature review should be guided by a focus research question.   Consider PICO and FINER criteria for developing a research question.

• Make sure your research question is not too broad or too narrow. Do a couple of pre-searches to see what information is out there and determine if it is a manageable topic.
• Identify the main concepts of your research question and write down terms that are related to them. Keep a list of  terms that you can use when searching.
• If possible, discuss your topic with your professor. 

2. Decide on the scope of your review.

Check with your assignment requirements and your professor for parameters of the Literature Review.

• How many studies are you considering?
• How comprehensive will your literature review be?
• How many years should it cover? 

3. Select appropriate databases to search.

Make a list of the databases you will search. 

• Don't forget to look at books, dissertations or other specialized databases .
• Contact your librarian to make sure you are not missing any vital databases for that topic.

4. Conduct searches and find relevant literature.

As you are searching in databases is important to keep track and notes as you uncover information.

• Read the abstracts of research studies carefully instead of just downloading articles that have good titles.
• Write down the searches you conduct in each database so that you may duplicate or avoid unsuccessful searches again.
• Look at the bibliographies and references of research studies you find to locate others .
• Look for subject terms or MeSH terms that are associated with the  research studies you find and use those terms in more searches.
• Use a citation manager such as Zotero or Endnote Basic to keep track of your research citations.

5. Review the literature. 

As you are reading the full articles ask the following questions when assessing studies:

• What is the research question of the study?
• Who are the author(s)? What are their credentials and how are they viewed in their field?
• Has this study been cited?; if so, how has it been analyzed?
• Was the research funded by a source that could influence the findings?
• What were the research methodologies? Analyze its literature review, the samples and variables used, the results, and the conclusions.  Does the research seem to be complete?  What further questions does it raise?
• Are there any conflicting studies; if so why?

Throughout the process keep careful notes of your searches and findings so it is easier to put it together when it comes to the writing part.

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What is a Literature Review?

The Scholarly Conversation

A literature review provides an overview of previous research on a topic  that critically evaluates, classifies, and compares what has already been published on a particular topic. It allows the author to synthesize and place into context the research and scholarly literature relevant to the topic. It helps  map the different approaches to a given question and reveals  patterns.  It  forms the foundation for the author’s subsequent research and justifies the significance of the new investigation.

A literature review can be a short introductory section of a research article or a report or policy paper that focuses on recent research. Or, in the case of dissertations, theses, and review articles, it can be an extensive review of all relevant research.

• The  format  is usually a bibliographic essay; sources are briefly cited within the body of the essay, with full bibliographic citations at the end.
• The  introduction  should define the topic and set the context for the literature review. It will include the author's perspective or point of view on the topic, how they have defined the scope of the topic (including what's not included), and how the review will be organized. It can point out overall trends, conflicts in methodology or conclusions, and gaps in the research.
• In the  body of the review , the author should organize the research into major topics and subtopics. These groupings may be by subject, (e.g., globalization of clothing manufacturing), type of research (e.g., case studies), methodology (e.g., qualitative), genre, chronology, or other common characteristics. Within these groups, the author can then discuss the merits of each article and analyze and compare the importance of each article to similar ones.
• The  conclusion  will summarize the main findings, make clear how this review of the literature supports (or not) the research to follow, and may point the direction for further research.
• The  list of references  will include full citations for all of the items mentioned in the literature review.

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What is a Literature Review?

A literature review is an essay that surveys, summarizes, links together, and assesses research in a given field. It surveys the literature by reviewing a large body of work on a subject; it summarizes by noting the main conclusions and findings of the research; it links together works in the literature by showing how the information fits into the overall academic discussion and how the information relates to one another; it assesses the literature by noting areas of weakness, expansion, and contention. This is the essentials of literature review construction by discussing the major sectional elements, their purpose, how they are constructed, and how they all fit together.

All literature reviews have major sections:

• Introduction: that indicates the general state of the literature on a given topic;
• Methodology: an overview of how, where, and what subject terms used to conducted your search so it may be reproducable
• Findings: a summary of the major findings in that field;
• Discussion: a general progression from wider studies to smaller, more specifically-focused studies;
• Conclusion: for each major section that again notes the overall state of the research, albeit with a focus on the major synthesized conclusions, problems in the research, and even possible avenues of further research.

In Literature Reviews, it is Not Appropriate to:

• State your own opinions on the subject (unless you have evidence to support such claims).  
• State what you think nurses should do (unless you have evidence to support such claims).
• Provide long descriptive accounts of your subject with no reference to research studies.
• Provide numerous definitions, signs/symptoms, treatment and complications of a particular illness without focusing on research studies to provide evidence and the primary purpose of the literature review.
• Discuss research studies in isolation from each other.

Remember, a literature review is not a book report. A literature review is focus, succinct, organized, and is free of personal beliefs or unsubstantiated tidbits.

• Types of Literature Reviews A detailed explanation of the different types of reviews and required citation retrieval numbers

Outline of a Literture Review

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100+ Current Nursing literature review topics + Examples to Write About

• Carla Johnson
• August 18, 2023
• Nursing Care Plan , Nursing Topics and Ideas , Writing Guides for MSN students

Nursing literature review is an important part of the nursing profession. It allows nurses to learn from the best studies and research on a particular topic. In this article, we will provide you with 100 good nursing literature review topics that you can use to help you write your nursing literature review.

Current Nursing literature review topics to Write About – topics for literature review in nursing

Nursing literature review is an essential component of any nursing program. Nurses need to have a comprehensive understanding of the latest nursing research in order to provide optimal care for their patients .

Here are current nursing literature review topics that you can explore:

• The Role of Nursing Research in Clinical Practice
• Enhancing Patient Outcomes through Nursing Research
• Applications of evidence-based Practice in Nursing
• The Relationship between Nursing Theory and Practice
• Issues in Implementation and Translation of Research Evidence into Clinical Practice
• Cultural Competence in Nursing: Perspectives from the Global South
• Nursing Perspective on Genetics and Genetics in Nursing
• Advances in Geriatric Nursing: From Theory to Practice
• Transforming Pediatric Nursing Care through EvidenceBased Practice
• Health Technology Assessment: A Critical Appraisal from a Nursing Perspective
• Promoting Collaborative Care through Effective Communication Practices within the Health System
• Nurses, Technology, and Innovation: Implications for Quality Improvement and Patient Safety
• Nursing Ethics: A Multidisciplinary Perspective
• Nursing in an Era of Health Care Reform
• The Role of Nursing Research in Evaluating Nursing Practice
• Nursing Research and Quality Improvement: Strategies for conducting systematic reviews
• Collaborative Care in Nursing: Theory, Research, and Practice
• The Impact of Nursing on Patient Safety
• The Role of Nursing Ethics in Patient Safety
• Nursing Informatics: A Critical Appraisal
• What Nurses Should Know About the National Minimum Data Set (NMDS)
• Assessing Electronic Health Records: Challenges and Opportunities
• Nursing in the Era of the Affordable Care Act
• The Influence of Nursing on Patient Outcomes
• The Effects of Culture on Nursing Practice
• Nursing in a Time of Economic Turmoil
• Challenges Facing Nursing Education in the Context of Healthcare Reform
• The Use of Technology by Nurses in the Delivery of Nursing Care
• Creating an Effective Learning Environment for Nursing Students

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20 Mental health nursing literature review topics

• Introduction to mental health nursing literature review: This literature review will introduce the reader to the field of mental health nursing and provide an overview of 20 different mental health nursing literature review topics.
• Psychiatric assessment: This literature review will focus on the psychiatric assessment process, including topics such as history taking and diagnostic procedures.
• Assessing for suicide risk: This literature review will discuss methods for assessing for suicide risk in patients, including coding criteria and risk assessment tools.
• Cultural competency in mental health nursing: This literature review will explore ways to be culturally competent when providing care to patients with mental illness, such as understanding cultural norms and beliefs.
• Therapeutic interventions for depression: This literature review will focus on therapeutic interventions for treating depression, such as pharmacological and psychological treatments.
• Psychotherapy for anxiety disorders: This literature review will discuss psychotherapy options for treating anxiety disorders, including cognitive-behavioral therapy and group therapies.
• Psychosocial rehabilitation interventions for addiction: This literature review will focus on psychosocial rehabilitation interventions designed to help patients recovering from addiction. Topics covered include relapse prevention and counseling techniques.
• Care of childrenand adolescents with mental health issues: This literature review will discuss the care of children and adolescents with mental health issues, including pediatric mental health disorders and psychosocial interventions for children and adolescents.
• Care of older adults with mental illness: This literature review will focus on the care of older adults with mental illness, including interventions for dementia-related psychosis and falls prevention.
• Complementary and alternative medicine in mental health nursing: This literature review will explore complementary and alternative medicine (CAM) therapies used to treat mental illness, such as acupuncture and meditation.
• Ethics in mental health nursing: This literature review will discuss ethical considerations in providing care to patients with mental illness, such as cross-cultural competency and ensuring patient safety.
• Mental health literacy: This literature review will focus on how to improve mental health literacy among nurses, including teaching strategies and clinical applications.
• Research methods in mental health nursing: This literature review will discuss research methods used in the study of mental health Nursing, including qualitative methods and quantitative methods.
• The role of nursing research in advancing mental health nursing: This literature review will discuss the role of nursing research in advancing the field of mentalhealth nursing, including the importance of randomized controlled trials.
• The role of advocacy in mental health nursing: This literature review will discuss the role of advocacy in mental health nursing, including advocacy for better access to mental health care and insurance coverage for mental health services.
• Patient safety in mental health nursing: This literature review will discuss patient safety issues in mental health nursing , including safe practices for handling psychiatric medications and preventing falls in elderly patients with dementia.
• The role of social work in mental health nursing: This literature review will discuss the role of social work in mental health nursing, including providing support to patients and their families.
• Geriatric psychiatry: This literature review will focus on the impact of aging on the brain and psychiatric disorders, including geriatric bipolar disorder and dementia-related psychosis.
• Rehabilitation interventions for people with mental illness: This literature review will focus on rehabilitation interventions designed to help people with mental illness recover from their illnesses. Topics covered include cognitive-behavioral therapy and peer support groups.
• Future research in mental health nursing: This literature review will discuss future research directions in mental health nursing, including innovative treatments and new approaches to understanding psychiatric disorders.

Here’s the process of Evaluating sources for a nursing literature review | Guide

List of 7 Nursing Literature Review Examples

• Here’s a  sample Capstone project
• Make use of this  Nursing Literature Review Sample | Benchmark – Part B: Literature Review
• More resources for your study  Capstone Literature Review
• Here’s the best  Capstone Project Literature Review – Solved Example
• Working with a PICOT question, here’s a  Literature Review For The PICOT Question – Solved Essay
• Make use of this  Grand Canyon Literature Review PICOT Statement Paper
• Taking MSN, here’s a sample nursing literature review example that you should read  Literature Review: The Use Of Clinical Systems To Improve Outcomes And Efficiencies

40 Ideas for nursing literature review topics

Nursing literature review is an important practice that nurses use to learn about new concepts and research studies. It can also be used to evaluate the quality of nursing care.

Here are forty ideas for nursing literature review topics:

• Nursing care of patients with dementia
• Effect of bed rest on nurses’ health
• Use of complementary and alternative medicine in nursing care
• Impact of technology on nurses’ work
• Role of nurses in disaster preparedness
• Effectiveness of patient safety programs
• Assessment and management of chronic diseases in the elderly
• Developing culturally competent nursing care plans
• Care of hospitalized pediatric patients
• Nursing interventions for preventing falls in the elderly
• Effectiveness of home health services for persons with disabilities
• Strategies to improve communication between nurses and patients with dementia
• Health promotion in hospitals: an evidence-based approach
• Nursing care for critically ill patients
• Promoting safe sleep for children
• A qualitative exploration into transitional learning experiences in nursing
• The intersection of race, ethnicity, and gender with nursing
• Ethics education for nurses
• Nurses’ experience working with migrant patients
• The impact of social media on nurses’ work
• Nurses’ perceptions of work stress and burnout
• Nursing management of chronic pain in adults
• Implementation and evaluation of nurse-led interventions for promoting oral health in older adults
• The role of nurses in the transition to palliative care
• Assessment and management of postoperative pain in adults
• Effects of sleep deprivation on nurses’ performance
• Nurse-led interventions for preventing falls in the elderly: a systematic review
• Nursing care in intensive care units: an overview
• Psychiatric nursing: an introduction
• Impact of burnout on nurses’ quality of life
• Nursing research: a critical perspective
• The influence of culture on maternal nursing
• Assessment and management of chronic diseases in children
• Caregiving trajectories among migrant mothers in Canada
• Development and evaluation of an evidence-based electronic health record for pediatric patients with chronic conditions (CHILD-EHR)
• Research methods for studying nursing practices: a qualitative exploration
• Cultural competency among hospital workers: implications for patient safety
• Nursing interventions for managing postoperative pain
• The role of nurses in disaster preparedness
• A qualitative exploration of the experience of work-life balance in nurses

Pediatric nursing literature review topics

There are many nursing literature review topics that could be covered when studying pediatric nursing. A few possible topics include:

• Acute care of the pediatric patient
• Assessment and diagnosis of pediatric patients
• Vital signs in pediatric patients
• Nutrition in the pediatric patient
• Pharmacology in the pediatric patient
• Palliative care of the pediatric patient
• Sleep patterns in the pediatric patient
• Infectious diseases of the pediatric population
• Child abuse and neglect in the pediatric population
• Medications and their effects in pediatrics

Nursing dissertation topics literature review

Nursing dissertation topics can be incredibly diverse, and there are many different ways to approach them. Below is a list of thirty possible topics that could be used as a starting point for your literature review. This is by no means an exhaustive list – you may want to explore additional topics that you feel would be relevant to your project.

• Care of the Elderly
• Care of Patients with Chronic Conditions
• Care of Pregnant Women
• Developmental Nursing
• Geriatric Nursing
• Healthcare Ethics
• Healthcare Leadership and Management
• Industrial/Organizational Nursing
• Neonatal/Pediatric Nursing
• Patient Safety and Welfare
• Primary Health care nursing
• Public Health nursing
• Women’s health nursing
• Youth health nursing
• Nursing Research Methods
• Nursing Care of Children with Special Health Needs
• Nursing Care of Patients with Developmental Disabilities
• Nursing Care of the Elderly with Memory Loss
• Nursing Research on Pediatric Populations
• Nursing Research on Chronic Illness
• Nursing Care of the Obese Patient
• Nursing Research on Palliative Care
• Nurse Anesthetists
• Nurse Midwives
• Nurse Practitioners
• Nurses in Critical Care Settings
• Nurses in Psychiatric Settings
• Nurses in Geriatric Settings
• Advanced Practice Registered Nurses
• Collaborative Practice

Other Nursing Dissertation Topic Areas include

• The impact of technology on nursing
• Global health nursing
• Nursing care in the aged population
• Geriatric psychiatry
• Nursing research methods Nursing care of developmental disabilities
• Nursing research with multicultural populations
• Palliative care in nursing
• Nursing leadership
• Nursing care of hospitalized patients
• Nursing research on pediatric populations
• Nursing care of patients with chronic conditions
• Nursing care for pediatric cancer patients
• Nursing research on chronic illness
• Nursing care of the obese patient
• Nursing research on geriatric populations
• Nursing care of the medically ill patient
• Nursing care of the chronically ill patient
• Nursing care of the postoperative patient
• Nursing care of the pediatric patient in critical condition
• Nursing research on perinatal and neonatal patients
• Nursing care of the pediatric patient with cerebral palsy
• Nursing research on palliative care

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How to write DNP capstone project Methodology Chapter

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List of Literature review topics for nursing students

Nursing students need to be familiar with a wide variety of literature review topics in order to become well-rounded professionals . Here are fifty of the most common nursing literature review topics.

• Nursing care of people with disabilities
• Advanced practice nurse practitioner roles and responsibilities
• Infectious diseases in nurses and patients
• Collaborative care: working together as a team in healthcare settings
• Leadership concepts in nursing: decision making, planning, organizing, goal setting, communication, delegation, and problem solving
• Nursing research: methods and applications in population-based studies
• Violence against nurses:prevention, intervention and response
• Nursing care of patients with chronic diseases
• Health assessment in the clinical setting
• Care of the elderly patient: principles and practice
• Nursing care of persons with diabetes mellitus
• Nursing care of the HIV-infected patient
• Cardiovascular nursing
• Advanced practice nurse roles in pediatric health nursing
• Nursing care of the post-operative patient
• Geriatric mental health nursing: a framework for practice
• Critical care transport nursing
• Community pharmacists in healthcare
• Pediatric advanced practice nurse roles and responsibilities
• Environmental health nursing
• Nurse case managers: integrating evidence-based interventions into clinical practice
• Mental health assessment tools for nurses
• Acute renal failure: diagnosis and management
• Nurses & social work collaboration in long-term care settings
• Care of the homeless patient
• Nursing care of the elderly at home
• Palliative care for pediatric patients
• Nursing care of older adults in assisted living facilities
• Nurses & pharmacists: drug therapy interactions
• Nursing care of cancer patients
• Patient assessment
• Care of the critically ill patient
• Nursing interventions for acute care
• Palliative care
• Nursing assistantship and leadership development
• Pharmacology for nursing students
• Human growth and development
• Community health nursing
• Research methods in nursing
• Nursing leadership and management
• Mental health nursing
• Nutrition for nurses
• Psychiatric rehabilitation nursing
• Nurse-midwife collaboration in obstetrics and gynecology
• Pediatric infection control and prevention
• Geriatric health teaching: a systematic approach
• Palliative care for children and adolescents
• Critical incident stress debriefing

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Top Tips for doing your literature review!

07 September, 2010 By NT Contributor

Many undergraduates and qualified nurses who have returned to study do a literature review as the final part of their degree. Helen Aveyard’s advice will ease the process and make it more enjoyable

Many undergraduate students and qualified nurses who have returned to study embark on a literature review as the final dissertation component of their degree. If this applies to you then there are various things that you can do and people you can see to make this process easier, more rewarding and even enjoyable!

The following tips will guide you through the literature review process:

Choose a topic that interests you. This might sound obvious but it does make all the difference in keeping your interest and motivation.From this topic, identify a specific question that you can answer from the literature. The key is to find a question that is not too broad.

Discuss this topic with everyone who will listen to you! This way you will mull over and refine your question until you feel you have a useful question that you can answer.

Work out what literature you need to answer your question . Not everything relating to your question will be relevant and some information will be more relevant than others… be selective.

Most questions need to be answered using primary research . In general terms, if your question involves measuring or evaluating care or an intervention then you will probably need to use quantitative research. If your question is more explorative, then qualitative research is likely to be most relevant. However this is not absolute. Remember that identifying which literature you need is one of the most important aspects of doing your literature review and it is useful to discuss in detail your approach with your supervisor. Think carefully about the type of literature that is likely to be most useful to you. Once you know what you are looking for, you can start to think about how to search for it!

Go and see your subject librarian . Most academic libraries offer drop in sessions for dissertation students. These will enable you to work out how to search for literature on your topic.

Identify key words and search terms . Think laterally about this and don’t forget to use words that are less common or have become outdated. This is because relevant articles might have been indexed using these words and you will miss them if you do not include them in your list of key words.

Now consider which databases you will search through . Go to your academic library website and read through the descriptions of each database and what each holds and select those databases that seem most relevant to your topic.

You are now ready to start searching . Remember to familiarise yourself with the basic functions of the database you are using, remembering that each database is slightly different from another. Take advantage of the Boolean operators (AND/OR/NOT) which allow you to narrow or broaden a search. It is always a good idea to supplement electronic searching with additional searching strategies, for example hand searching relevant journals or reference lists. This is because some key articles might be missed through electronic searching due to the way the paper is indexed.

Look at the abstracts of the articles you come across . It is usually possible to identify from the abstract whether the paper is useful for your review.

Start getting hold of the articles that seem relevant . Sometimes you will need an inter-library loan to do this. At this stage you need to be ruthless. If the article is not relevant to your review, then do not include it. However anything that might be relevant must be looked at.

Collect together all the articles that address your research question . At undergraduate level, if you have around 10 articles, then this is ideal. Significantly more will mean that you are not able to refer to the articles in sufficient detail and too few will not give you enough data to write your review.

Be pragmatic! If needs be, refine your review question to fit the articles that you have. If you have too many articles, try limiting the focus of your question somehow. Can you restrict the focus to the UK only? or a particular nursing speciality?

The next step is to consider the quality of the articles you have . You might have a paper that is directly relevant to your research question but if the quality of the paper is poor it may not help you as much as you think. It is generally a good idea to use a critical appraisal tool that is specific to the research design of your given paper. This might mean that you need to use a few different critical appraisal tools if your literature review question requires you to access a wide range of literature. Discuss this with your supervisor. Using the critical appraisal tool, consider the strengths and limitations of the literature you have identified and consider how much impact each paper has in addressing your research question.

Bring all the papers together and provide an answer for your research question . It is often useful to make a chart of key themes that arise in the papers, the authors of the papers, when they were written and their strengths and weaknesses. You can then see at a glance which other papers identify similar (or different) themes.

As you do this, you will begin to see patterns emerging in the literature and will be able to form an answer to your question. Remember that your answer may well be incomplete. It is quite permissible to say ‘there is some evidence that…’ rather than to provide a definitive answer. What is not permissible is to make out that you have a clear answer when in fact the literature does not support this. In this case, honesty really is the best policy.

Above all remember to answer the question!

Finally remember to put your literature review on your CV and be prepared to discuss at interview. It is a strong selling point when you apply for your first job or a new job.

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• Case report
• Open access
• Published: 24 August 2024

Benign pyloric adenomyoma presented as gastric outlet obstruction: a case report and review of the literature

• Ammar Albostani   ORCID: orcid.org/0000-0002-7213-7722 1 ,
• Sedra Sheikh Debs   ORCID: orcid.org/0009-0008-3257-3424 1 ,
• Salma M. Omar   ORCID: orcid.org/0000-0002-3147-3041 1 ,
• Nour Dadoush   ORCID: orcid.org/0000-0002-8052-874X 2 ,
• Linda Alkhouri   ORCID: orcid.org/0009-0002-5515-4296 3 ,
• Rama Alyousfi   ORCID: orcid.org/0000-0003-1498-2001 4 &
• Nihad Mahli 2  

Journal of Medical Case Reports volume  18 , Article number:  397 ( 2024 ) Cite this article

Metrics details

Gastric adenomyoma is a rare benign tumor composed of glandular structures and smooth muscle fibers. While some classify gastric adenomyoma as a hamartoma, others view it as an abortive form of heterotopic pancreas. Despite its benign nature, there is a risk of malignant transformation. Predominantly found in the antrum, gastric adenomyoma affects all ages but is most common in adults aged 40–60 years. Symptoms are nonspecific, and its similarity to other lesions complicates diagnosis. This paper aims to provide a review of medical literature on gastric adenomyoma and its diagnosis and treatment methods, along with presenting an additional case report on the same topic.

Case presentation

We present the case of a 55-year-old Syrian man who experienced vomiting, weight loss, and chronic partial constipation. An obstructing mass in the pylorus was detected, and then an open surgery was performed to excise the lesion. A biopsy of the resected mass was obtained for histopathological examination. The final diagnosis of the lesion was pyloric-region adenomyoma with severe pyloric stenosis. After the successful surgery, the patient recovered without any recurrence or complications.

Conclusions

Several diagnostic approaches are available, including radiological studies, endoscopic examination, and fine needle aspiration guided by endoscopic ultrasonography. Treatment options involve endoscopic submucosal dissection and complete laparotomy resection. Further studies and thorough reviews are recommended to better understand the best clinical practices. Practitioners should consider gastric adenomyoma when encountering a mural gastric lesion.

Peer Review reports

Introduction

Gastric adenomyoma (GA) is classified by the World Health Organization as a rare benign tumor of the stomach, characterized by a unique histological composition of glands and cysts lined by columnar or squamous epithelium, embedded with a prominent smooth muscle stroma [ 1 , 2 , 3 ]. On the one hand, some authors categorized gastric adenomyoma as hamartoma. On the other hand, some suggested defining it as an abortive variant of heterotopic pancreas [ 4 ]. Despite its benign classification, a possibility of malignant transformation still exists [ 4 ]. Although GAs are predominantly found in the gallbladder, sporadic cases in the stomach have been documented, with the majority (85%) occurring in the antrum, and the rest (15%) have been reported in the pylorus [ 1 , 4 ].

Gastric adenomyoma ranges in size from 0.6 to 4.5 cm and can affect individuals across a wide range of age, from infancy to advanced age, with the highest occurrence observed in adults between the fourth and sixth decades of life [ 4 , 5 ]. Clinical presentation varies widely; nonspecific symptoms such as nausea, vomiting, epigastric pain, hematemesis, melena, and hematemesis are repeatedly noticed [ 4 ]. GA poses a diagnostic challenge due to its resemblance to other gastrointestinal lesions, for instance, gastrointestinal stromal tumors (GISTs), leiomyoma, or leiomyosarcoma [ 3 ]. This confusion can lead to a misdiagnosis and inappropriate management strategies.

Herein, we report a rare case of gastric adenomyoma that caused stomach outlet obstruction that had been suspected to be a malignant tumor before histopathological examination was performed. It is worth noting that this is one of the first case reports of gastric outlet obstruction due to pyloric adenomyoma in an adult patient. In this paper, we have also briefly conducted a review of the medical literature for similar case reports.

A 55-year-old Syrian man from rural areas near Aleppo City presented to the gastrointestinal department with a chief complaint of chronic vomiting of food remnants persisting for 4 years and a weight loss of 34 kg during the last month before presentation. The patient also experienced chronic partial constipation. During gastrointestinal endoscopy at our hospital, an enlarged food-filled stomach and severe pyloric edema were observed that obstructed the gastric outlet and stopped further passage of the endoscope toward the duodenum. The primary diagnosis was gastric outlet obstruction due to pyloric stenosis. To assess the extent and cause of the obstruction, a computed tomography (CT) scan of the abdomen was performed, revealing a severely dilated stomach with a 4 cm mass in the pylorus and 1 cm thickening of the pyloric wall (Fig.  1 ).

Computed tomography scan revealing the mass in the pyloric region of the stomach. White arrows point at the lesion

Based on these findings, open surgery was performed to resect the mass that was initially suspected to be a malignant tumor causing the obstruction (Fig.  2 ). During surgery, multiple enlarged lymph nodes were found surrounding a 4 × 3 cm mass in the pylorus. The mass and surrounding lymph nodes were excised via distal partial gastrectomy with free surgical margins. The resected mass was sent for histopathologic examination. The normal reactive lymph nodes excised from the lesser and greater omentum indicated the absence of metastatic disease.

White arrows point at the mass of lesion located in the pyloric region of the stomach during surgery before its resection later

Histopathological analysis revealed normal gastric epithelium, with well-differentiated glands showing some areas of dilation lined by columnar to cuboidal cells in the muscularis propria and submuscular layer. No atypia or mitotic activity was observed, and the proliferative glands were surrounded by smooth muscle bundles (Fig.  3 ). The final diagnosis of the obstructing lesion was pyloric-region adenomyoma with severe pyloric stenosis. The patient’s condition improved gradually after the successful surgery, and he was discharged home after the fourth day of hospitalization. After 1 year of follow-up, our patient experienced neither recurrence nor complications related to the surgery.

Pathohistological examination of the gastric adenomyoma lesion. A Normal gastric epithelium. B , D Islands of epithelial ducts and glands surrounded by smooth muscle bundles. C No presence of atypia or mitosis in the proliferative ducts

Gastric adenomyoma was initially described in 1903 by Magnus-Alsleben. Subsequently, Anand et al. [ 6 ] mentioned that only 52 case reports were published in medical literature until the year 2017. Later on, and according to the review of Barré et al. [ 3 ], nine cases of gastric adenomyoma have been reported and published during 2017 and 2020. In this paper, we have reviewed the Medline-indexed literature published after 2020 via PubMed using the search strategy “(adenomyoma) AND (gastric OR stomach)” with applying (Case Reports) filter to the results. Only eight articles were reached, and of them, merely four papers reported patients with GA [ 7 , 8 , 9 , 10 ]. Therefore, we claim, to our knowledge, that a total of approximately 65 articles have reported GA in the medical literature until the date of publishing this current case report, making our article the 66th.

Of these cases, very few presented with symptoms resembling gastric duplication cysts or pyloric stenosis, or manifested as gastric outlet obstruction [ 3 ]. Takeyama et al. [ 5 ] reported a case of GA causing obstruction in a 1-month-old girl. Similarly, Rhim et al. [ 11 ] reported a case of GA causing obstruction in a 1-week-old boy, emphasizing the importance of considering GA in the differential diagnosis of gastric outlet obstruction in infants, particularly when radiological features deviate from those typical of hypertrophic pyloric stenosis. Notably, cases of GA presenting as gastric outlet obstruction are more commonly reported in pediatrics, and building on the findings of the review by Barré et al. [ 3 ], the presentation of obstruction is more common when lesions are located closer to the gastric outlet (that is, cases with GA in the pylorus usually manifest as stomach outlet blockage).

Symptoms are either absent or nonspecific in the majority of adult cases, which may introduce a reason why GA is considered a low-occurrence lesion [ 2 , 8 ]. Usual manifestations include epigastric pain and/or discomfort, hematemesis, dyspepsia, vomiting, anemia, melena, and occasionally peritonitis due to perforation [ 4 , 8 ]. In pediatrics, intussusceptions are the most frequent complications [ 5 ]. Our patient had chronic food emesis for 4 years and 34 kg weight loss, which made us concerned for malignancy; after performing endoscopy and discovering the pyloric stenosis and stomach outlet blockage, we immediately decided to carry out laparotomy.

Preoperative diagnosis of GA is challenging as doctors are unfamiliar with it [ 12 ]. Radiological diagnosis for gastric adenomyoma encompasses barium meal X-ray, CT scan, ultrasonography, gastrointestinal endoscopic ultrasound, and occasionally magnetic resonance imaging (MRI) [ 8 ]. However, several authors, including Vandelli et al. [ 13 ] and Zhu et al. [ 2 ], argued that endoscopic examination alone may be insufficient for diagnosing GA due to the limitations of superficial biopsies as they do not provide accurate representative tissue samples. Moreover, they highlighted that endoscopic features are not definitive for distinguishing adenomyoma from tumors that may present as antral umbilicated submucosal masses [ 2 , 4 , 8 ]. They advocated for resection followed by histological studies and immunohistochemical stains for definitive diagnosis, and recommended the intraoperative diagnosis via frozen section to avoid excessive surgical procedures [ 2 ].

In contrast, Barré et al. [ 3 ] presented a unique perspective and proposed a novel approach by utilizing the endoscopic ultrasonographic-directed fine needle aspiration (EUS-FNA) to diagnose mural-based lesions, aiming to reduce the need for surgical intervention, particularly in asymptomatic cases. We recommend their diagnostic algorithm, which initially distinguishes between mural or luminal gastric lesions, and then, if the lesion is luminal as in the case of gastric cancer, alternative diagnostic methods should be considered. Accordingly, Kagawa et al. [ 12 ] considered EUS the most useful approach to provide diagnostic details for gastric wall lesions. However, diagnosing GA relies entirely on histological studies, which involves identifying heterotopic tissues, the lesion’s architectural pattern, its relationship with the adjacent tissues, and the exclusion of malignancy. The key information provided by EUS is the precise location of the tumor within the gastric wall and the identification of suitable physicians for endoscopic removal of the lesion [ 4 ]. GA should be distinguished from both gastritis cystica profunda and high-grade adenocarcinoma [ 2 ], and despite being an uncommon tumor, gastric adenomyoma needs to be considered when a gastrointestinal stromal tumor or another mural gastric lesion is suspected [ 1 ].

In this present case, we opted for distal partial gastrectomy following endoscopy due to the previously mentioned reasons. A suspicion of malignancy existed since the nature of the symptoms was misleading. To better assess the size and location of the lesion, we chose to perform a CT scan. Furthermore, our definitive diagnosis was only confirmed through complete resection and subsequent pathohistological studies. Heretofore, no GA typical treatment has been stated [ 8 ]. In a retrospective study by Wang et al. [ 14 ] on 15 patients with GA, endoscopic submucosal dissection (ESD) resulted in successful clinical outcomes. They stated that ESD has been repeatedly used in treating small gastrointestinal tract neoplastic lesions as this procedure recorded minimal preoperative pain and trauma, concise period of hospital stays, and low disease recurrence rate. Usually, gastric lesions that cause thickness in the antral and/or pylorus wall are managed with laparoscopic wedge resection [ 9 ]. All in all, medical literature included multiple successful surgical methods to treat GA such as endoscopic mass resection, laparoscopic mass resection, complete laparotomy resection (that is, partial gastrectomy), subtotal gastrectomy, or total gastrectomy based on the patient’s condition and the severity of the lesion [ 8 ].

Gastric adenomyoma is a rare lesion that can be misdiagnosed as it presents with nonspecific symptoms. Multiple approaches of diagnosis are reported such as radiological studies, endoscopic examination, and endoscopic ultrasonographic directed fine needle aspiration. Treatment options include endoscopic submucosal dissection and complete laparotomy resection. We highly recommend further studies, research, and thorough reviews on this lesion to achieve better knowledge and understanding of the best clinical choices. We also advice practitioners to consider gastric adenomyoma when a mural gastric lesion is discovered.

Availability of data and materials

Not applicable.

Abbreviations

• Gastric adenomyoma

Gastrointestinal stromal tumors

Computed tomography

Magnetic resonance imaging

Endoscopic ultrasonographic-directed fine needle aspiration

Endoscopic submucosal dissection

Yoon KH, Eun DY, Kim JH, Lee SO, Kim HS, Lee DW. Gastric adenomyoma in the stomach body: a case report. J Med Case Rep. 2014. https://doi.org/10.1186/1752-1947-8-385 .

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Acknowledgements

We would like to express our sincere gratitude to Qumrah Research Lab team for their invaluable support and significant contribution to this research project. Their unwavering commitment and generous backing have played a pivotal role in the successful completion of this scientific paper. Their important notes and suggestions were critical in shaping the content, and we are grateful for their expertise and guidance throughout the project. Also, we are very thankful to Dr. Imad Mohandes and his laboratory team for their important efforts and guidance in the pathological studies and diagnosis of this case.

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Ammar Albostani, Sedra Sheikh Debs & Salma M. Omar

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AA designed the work concept, drafted the manuscript, and guided the teamwork. SSD participated in academic writing. SMO assisted in academic writing and literature search. ND helped in academic writing and literature search. LA participated in academic writing and extracted the references. RA performed the histopathological examination and collected the patient’s data. NM conducted the surgery and documented the patient’s follow-up. All authors read and approved the final manuscript.

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Albostani, A., Sheikh Debs, S., Omar, S.M. et al. Benign pyloric adenomyoma presented as gastric outlet obstruction: a case report and review of the literature. J Med Case Reports 18 , 397 (2024). https://doi.org/10.1186/s13256-024-04741-7

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Nursing Literature Review Topics And Examples

Nursing is one of the careers that call for significant and up-to-date research. This profession primarily necessitates qualitative, up-to-date research that discusses in depth the aspects influencing the behavior of a particular disease. Research is the only method by which experts can find a cure for an ailment. Researchers and students, therefore, must find the appropriate nursing literature review topics.

A nursing literature review can focus on the behavioral or physical part of the condition. It is crucial to have a competent mentor in nursing literature reviews to select the correct topic for your research.

Here you’ll find some nursing literature review topics to help you narrow down your search.

Top Tips for doing your literature review

Choose a fascinating topic.

Choosing fascinating topics for a literature review in nursing might sound quite obvious but it helps make a massive difference in keeping you motivated and interested in writing your literature review. In the nursing area you are interested in, select a specific question that you will seek to answer.

Choose a topic other people will be interested to learn about. This way, you will research and refrain from other irrelevant questions and form an appealing and intriguing question you can provide answers to.

Be selective

Do not just pick any piece of literature out there related to your nursing literature review topic. Not every data available, although related to your case, is relevant. Only select more information pertinent to your selected literature review on nursing topics.

9/10 nursing literature review questions can be answered by conducting simple research. If the question is about evaluating a treatment approach, then the viable option should be quantitive research. Qualitative research could be more appropriate in cases where the question is quite explorative.

You always remember that understanding the type of literature you need to use is crucial in writing your literature review. It will be wise to discuss the details with your instructor. Carefully examine the type of literature that will be most useful to your literature review. Once you understand what you should look for exactly, you will be good to go.

Make the library your friend

Schedule frequent library sessions and learn more about the subject, particularly your chosen topics for literature review in nursing. Most institutions have sections for students’ thesis and dissertations, which should be easier to find.

Identify the publications you will research. You can visit the academic library website and skim through the different sections and discover the most relevant ones to the topics you are interested in.

At this point, you are almost ready to get started. You should now know where to source the relevant databases both online and in the library. The rule of thumb is to use offline and online research publications to write your nursing literature review paper. Sometimes, some key details might be missing in the online databases and vice versa.

Go through the abstracts of relevant articles that have been published before

Only review the relevant articles since this will save you time and energy in the long run. When going through the abstracts, note the articles you deem relevant. Remember to be conscientious about the kind of articles you take note of. Ditch any papers that are not relevant, no matter how well-written they might seem. The same goes for relevant articles. You must review them.

Have a list of the article you deem relevant to your nursing literature review topic. If you are an undergraduate, ten articles should be good to get you started. A higher number of articles will mean that you won’t get into many details of the articles, and fewer articles translate to inadequate research.

If you have no other choice, then you will need to improvise. You can refine the nursing paper topics to match the articles you have collected. When you have a long list of articles, you can always reduce the scope of your nursing literature review question. For example, you can limit your focus to only one country or even one state.

The next step is to assess the quality of the content of the articles you have. Sometimes a paper can be relevant to your nursing literature review topic or question, but it might be of poor quality. That is why you should employ a critical appraisal method that is unique to the research design of your paper. This could mean that you will have to use other essential appraisal methods if your literature review question requires you to access a wide variety of literature.

You can talk to your instructor. Using the critical appraisal method, you can see the limitations and strengths of the data you have collected and the level of influence each article has had on your final literature review paper.

Review all the articles together and list down the answers to your question

A pro tip is to create a chart of the main topics you come across as you read through the articles, the authors, and the strengths and weaknesses. You will then see what issues are recurrent in most of the articles.

By doing this, you will notice the clear picture and pattern in the literature, and you will be able to formulate an answer to your question quickly. That does not mean that the answer will always be perfect. You might need to make further adjustments.

Whatever final answer you come up with, make sure it is supported by the evidence collected. you should not have a solution that none of the facts you collected in the literature is answering

Community Nursing literature review Topics

Writing about community services is quite a tricky task. You might need help from an expert to help you nail your nursing literature review. Here are community nursing literature review topics.

• Patient Documentation Discussion
• Digital Healthcare Surveys Rehabilitation of Sexual Abuse Victims
• Innovative Methods
• Innovative Care Planning
• Immigration Aid
• Rural Population Healthcare Demands
• Scotland’s Culture
• Volunteer Nursing Work
• Stress Treatment

Top Nursing Literature Review Topics

• Impact of health promotion initiatives on public health Collaborative roles of nurses, policymakers, social workers, and primary care physicians
• How gardening therapy reduces anxiety in the elderly
• facets of healthcare development, strategy, and research strategies
• Teenage binge drinking and alcoholism are a growing problem.
• National Health Services’ efficiency and effectiveness in providing services to the elderly
• Family therapy’s effect on adolescents.
• Guidelines to improve healthcare quality
• Ethics and leadership demonstrated
• Evidence-based disease management
• Effective methods for working with a variety of patients with mental health difficulties
• Mental health issues related to substandard housing
• Management difficulties in the care of elderly patients
• Public health strategies in Great Britain
• Improving pregnancy and care outcomes
• Understanding food labels to prevent obesity and poor health
• Positive results of laughter therapy
• World Health Organization approaches and policies concerning child development
• Community nursing’s role in enhancing senior health
• Community nurse health promotion practice
• AIDS: Social repercussions
• Knowledge management employing evidence
• Spouses of people living with Alzheimer’s may experience psychological difficulties.
• epidemiological trends concerning cardiovascular hazards
• Can a patient and nurse bond aid in a patient’s recovery?
• Principal dangers in clinical management
• Hearing the hallucinations of schizophrenia patients
• Evidence-based practice as both a pragmatic and theoretical strategy
• repercussions of community service and elderly patient care
• Implications of music therapy on individuals with depression
• How to properly manage drunk patients
• Developing a welcoming atmosphere in the waiting room
• Influence of nursing on parents who refuse to vaccinate their children
• Improved nurse-patient connections. How essential are they?
• Patients who refuse care must be treated.
• The significance of mental health nursing to patient outcomes
• What can a nurse do to administer initial care?
• Aiding the elderly patients in their everyday activities and providing nursing care
• The influence of nursing practice on future nurses
• Nursing precautions against infectious diseases
• Nursing schools and the practical application of academic knowledge
• The nursing aspect of child care. Assisting youngsters to have no fear of physicians.
• The uniform colors of nurses and their utility in the hospital
• What nurses must know to improve their knowledge
• Assisting the person in need: The significance of triage nurses
• Why are male nurses necessary, and why are there more of them than ever before?
• How to approach patients with medical procedure phobias
• Application of practical expertise in nursing interventions
• The advancements in patient care and nursing approaches
• How can nurses make patients feel secure?
• How may a patient’s relationship with a nurse aid in their recovery?
• Recognize the signs of abuse promptly.
• Nursing role in the prevention of pressure ulcers in bedridden individuals
• Treatment of patients with mental disorders
• Nursing ethics and how to respect the preferences of the patient
• Recognizing potentially dangerous patients and what to do if you encounter one Doctor–nurse relationship enhancement strategies
• Reducing nurses’ working hours and the possible benefits of doing so
• Are nurses treated differently than other hospital employees?
• Nursing duties in various patient wards

Health Organizations’ nursing literature review topics

Here are a few good nursing literature review topics about health organizations

• Rural Conflicts in New Healthcare Developments
• Television Healthcare Advertising
• Inequality in Healthcare Delivery in the United Kingdom Training Remote-care Help
• Racism in Emergency Department
• Electronic Administration
• School Screening Methodologies
• Work Opportunity Availability
• Rehabilitation of Children in School Facilities

Elderly Personsnursing literature review Topics

• What characteristics enable a nurse to recognize an old patient who has been abused in the past?
• Are you in agreement that community-based social innovations have facilitated healthy aging?
• Is it permissible to conduct clinical studies on elderly patients?
• Home is the most pleasing environment for aging. How much do you concur?
• What is the required minimum level of education for nurses, and how may it be enhanced?
• Does mealtime help aid the elderly in monitoring their protein and vitamin intake?
• Should the families of geriatric patients be held accountable for progressing the patients’ treatment?
• What significant challenges do elderly patients face?
• Explain the aging trend and the concept of global health.
• How should the healthcare system be modified to guarantee that the elderly receive quality care?
• What are the most effective medical methods for managing stress and information surcharge?

Healthcare Management Nursing Literature Review Topics

• Challenges that may be encountered during the contracting process in health care.
• What legal concerns may non-native patients encounter?
• What are the primary tenets of marijuana management?
• How do you establish a private medical practice?
• Regarding medical decisions and apology legislation.
• Exists discrimination based on gender in the nursing profession?
• The advantages and disadvantages of Medicare.
• Principal provisions of the nursing uniform code.
• What is the cause of the shortage of males in the healthcare industry?
• Home healthcare services.

Geriatric Nursing Literature review Topics

• Malnutrition’s impact on the organ system.
• What effect does aging have on the immune system?
• How should sepsis be treated in critically unwell elderly patients?
• How can a lengthy hospital stay contribute to complications among critically ill patients?
• What are the causes and risks of depression in later life?
• How effective is a healthy diet at lowering the risk of osteoporosis?
• What role do registered nurses play in advance care planning?
• Several methods for preventing delirium in older individuals.
• The diagnosis and risk factors for urinary tract infections in older adults.
• Discuss essential care techniques for older individuals with hip fractures of fragility.
• What molecular mechanisms and preventative strategies exist against Alzheimer’s disease in adults?
• Can nutrition pose a dementia risk?
• How can elderly individuals maintain dental hygiene?
• Age-related effects on the cardiovascular system.
• Elderly dehydration: causes, symptoms, prevention, and therapy.
• The changes in the elderly’s nerve system and cognitive senses.
• Essential care strategies for older adults with alcohol use problems.
• What medical emergencies are faced by elderly cancer patients?
• Available treatments for heart failure in the elderly.

Pediatric Nursing literature review topics

• Leukemia Cells And Children’s Immune Systems
• How has the pandemic affected the mental health of children?
• Strategies To Reduce The Risk Of Blindness In Children Receiving Oxygen Therapy Using Pragmatic Language Patterns For Children With Autism
• Acute Leukemia in Children and Reducing Painful Treatment and Diagnosis
• Student And Youngsters Depression And Psychological Health Vulnerability
• Congenital Heart Disease In Children And Their Psychological Problems
• Enhancing Language Acquisition For Children With Developmental Disabilities
• Optimizing Childhood Cancer Treatment
• Childhood Obesity: An Issue of Public Health
• Ethical issues preventing nurses from providing care to younger patients

Quantitative Nursing literature review Topics

• Describe and assess nursing critical care.
• Methods for treating pressure ulcers in hip fracture patients.
• Present a critical evaluation of assisted suicide and the associated ethics.
• What roles do nurses have in teaching and encouraging self-care?
• Compare and contrast nursing facilities and home care.
• What are the most common causes of heart attacks?
• What are the hurdles involved in managing chronic diseases?
• Describe the benefits of a healthy diet.
• The most effective cardiovascular disease treatments.
• Discuss assisted suicide and its ethical implications.

Child Nursing Literature Review Topics

• What are the requirements of Pediatric Critical Care?
• Examine the leading causes of child mortality in the United Kingdom.
• Strategies for addressing childhood malnutrition
• Causes and treatment of Tourette syndrome in children.
• The optimal treatments for autistic people.
• How can children’s meningitis be prevented?
• Examine the development of newborn care.
• The pathogenesis and management of opportunistic fungal infections.
• Dietary Health and Childhood Obesity
• Adolescent Practices in Medicine.
• Discuss childhood Neuroblastoma and Metabolic Syndrome.
• Pediatric asthma and monitoring approach.
• Explain why youngsters are resistant to antibiotics.
• Antibiotic resistance in preschoolers.
• The impact of social media on children’s eating habits.

Nursing Careers literature review Topics

• Clinical guidelines and nursing principles
• Stress management training for night shift workers.
• Critical care nursing administration
• Training to make prudent medical decisions
• The clinical nurse functions
• Guidelines for primary gynecological education
• Diversity within the healthcare industry
• Between occupation and service to others
• The best method to force seniors to consume.
• The digital age and nursing’s future
• Exercise to guarantee no drug errors
• Nursing professionals
• Remote concerns about intensive care unit
• Superior nursing procedures
• What are the best leadership skills for nurses?
• Morality and homelessness treatment
• The nurse’s role in managing anxiety
• Works of nursing theorists

The Bottom Line

Nursing is a serious occupation, and you need to be as professional as possible. ​Nursing literature review ideas​ can be pretty challenging to come up with. Writing a nursing literature review is simple but not easy. It all begins by selecting appropriate nursing literature review topics and getting down to relevant and accurate research.

Choose ​nursing literature review topics​ that you are familiar with, as this will ensure that you will spend less time doing the research and more time writing. The tips and comprehensive list of nursing literature review topics should get you started. You can even modify them so that they fit you perfectly. Should you get stuck with writing your nursing literature review, do not fret. You can always get help from professional nursing literature review experts.

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Exploring the factors driving AI adoption in production: a systematic literature review and future research agenda

• Open access
• Published: 23 August 2024

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• Heidi Heimberger   ORCID: orcid.org/0000-0003-3390-0219 1 , 2 ,
• Djerdj Horvat   ORCID: orcid.org/0000-0003-3747-3402 1 &
• Frank Schultmann   ORCID: orcid.org/0000-0001-6405-9763 1  

Our paper analyzes the current state of research on artificial intelligence (AI) adoption from a production perspective. We represent a holistic view on the topic which is necessary to get a first understanding of AI in a production-context and to build a comprehensive view on the different dimensions as well as factors influencing its adoption. We review the scientific literature published between 2010 and May 2024 to analyze the current state of research on AI in production. Following a systematic approach to select relevant studies, our literature review is based on a sample of articles that contribute to production-specific AI adoption. Our results reveal that the topic has been emerging within the last years and that AI adoption research in production is to date still in an early stage. We are able to systematize and explain 35 factors with a significant role for AI adoption in production and classify the results in a framework. Based on the factor analysis, we establish a future research agenda that serves as a basis for future research and addresses open questions. Our paper provides an overview of the current state of the research on the adoption of AI in a production-specific context, which forms a basis for further studies as well as a starting point for a better understanding of the implementation of AI in practice.

Explore related subjects

• Artificial Intelligence

Avoid common mistakes on your manuscript.

1 Introduction

The technological change resulting from deep digitisation and the increasing use of digital technologies has reached and transformed many sectors [ 1 ]. In manufacturing, the development of a new industrial age, characterized by extensive automation and digitisation of processes [ 2 ], is changing the sector’s ‘technological reality’ [ 3 ] by integrating a wide range of information and communication technologies (such as Industry 4.0-related technologies) into production processes [ 4 ].

Although the evolution of AI traces back to the year 1956 (as part of the Dartmouth Conference) [ 5 ], its development has progressed rapidly, especially since the 2010s [ 6 ]. Driven by improvements, such as the fast and low-cost development of smart hardware, the enhancement of algorithms as well as the capability to manage big data [ 7 ], there is an increasing number of AI applications available for implementation today [ 8 ]. The integration of AI into production processes promises to boost the productivity, efficiency as well as automation of processes [ 9 ], but is currently still in its infancy [ 10 ] and manufacturing firms seem to still be hesitant to adopt AI in a production-context. This appears to be driven by the high complexity of AI combined with the lack of practical knowledge about its implementation in production and several other influencing factors [ 11 , 12 ].

In the literature, many contributions analyze AI from a technological perspective, mainly addressing underlying models, algorithms, and developments of AI tools. Various authors characterise both machine learning and deep learning as key technologies of AI [ 8 , 13 ], which are often applied in combination with other AI technologies, such as natural language recognition. While promising areas for AI application already exist in various domains such as marketing [ 14 ], procurement [ 15 ], supply chain management [ 16 ] or innovation management [ 17 ], the integration of AI into production processes also provides significant performance potentials, particularly in the areas of maintenance [ 18 ], quality control [ 19 ] and production planning and management [ 20 ]. However, AI adoption requires important technological foundations, such as the provision of data and the necessary infrastructure, which must be ensured [ 11 , 12 , 21 ]. Although the state of the art literature provides important insights into possible fields of application of AI in production, the question remains: To what extent are these versatile applications already in use and what is required for their successful adoption?

Besides the technology perspective of AI, a more human-oriented field of discussion is debated in scientific literature [ 22 ]. While new technologies play an essential role in driving business growth in the digital transformation of the production industry, the increasing interaction between humans and intelligent machines (also referred to as ‘augmentation’) creates stress challenges [ 23 ] and impacts work [ 24 ], which thus creates managerial challenges in organizations [ 25 , 26 ]. One of the widely discussed topics in this context is the fear of AI threatening jobs (including production jobs), which was triggered by e.g. a study of Frey, Osborne [ 27 ]. Another issue associated to the fear of machines replacing humans is the lack of acceptance resulting from the mistrust of technologies [ 28 , 29 ]. This can also be linked to the various ethical challenges involved in working with AI [ 22 ]. This perspective, which focuses on the interplay between AI and humans [ 30 ], reveals the tension triggered by AI. Although this is discussed from different angles, the question remains how these aspects influence the adoption of AI in production.

Another thematic stream of current literature can be observed in a series of contributions on the organizational aspects of the technology. In comparison to the two research areas discussed above, the number of publications in this area seems to be smaller. This perspective focuses on issues to implement AI, such as the importance of a profound management structure [ 31 , 32 ], leadership [ 33 ], implications on the organizational culture [ 34 ] as well as the need for digital capabilities and special organizational skills [ 33 ]. Although some studies on the general adoption of AI without a sectoral focus have already been conducted (such as by Chen, Tajdini [ 35 ] or Kinkel, Baumgartner, Cherubini [ 36 ]) and hence, some initial factors influencing the adoption of AI can be derived, the contributions from this perspective are still scarce, are usually not specifically analyzed in the context of production or lack a comprehensive view on the organization in AI adoption.

While non-industry specific AI issues have been researched in recent years, the current literature misses a production-specific analysis of AI adoption, providing an understanding of the possibilities and issues related to integrating AI into the production context. Moreover, the existing literature tells us little about relevant mechanisms and factors underlying the adoption of AI in production processes, which include both technical, human-centered as well as organizational issues. As organizational understanding of AI in a business context is currently still in its early stages, it is difficult to find an aggregate view on the factors that can support companies in implementing AI initiatives in production [ 37 , 38 ]. Addressing this gap, we aim to systematise the current scientific knowledge on AI adoption, with a focus on production. By drawing on a systematic literature review (SLR), we examine existing studies on AI adoption in production and explore the main issues regarding adoption that are covered in the analyzed articles. Building on these findings, we conduct a comprehensive analysis of the existing studies with the aim of systematically investigating the key factors influencing the adoption of AI in production. This systematic approach paves the way for the formulation of a future research agenda.

Our SLR addresses three research questions (RQs). RQ1: What are the statistical characteristics of existing research on AI adoption in production? To answer this RQ, we conduct descriptive statistics of the analyzed studies and provide information on time trends, methods used in the research, and country specifications. RQ2: What factors influence the adoption of AI in production? RQ2 specifies the adoption factors and forms the core component of our analysis. By adoption factors, we mean the factors that influence the use of AI in production (both positively and negatively) and that must therefore be analyzed and taken into account. RQ3: What research topics are of importance to advance the research field of AI adoption in production? We address this RQ by using the analyzed literature as well as the key factors of AI adoption as a starting point to derive RQs that are not addressed and thus provide an outlook on the topic.

2 Methodology

In order to create a sound information base for both policy makers and practitioners on the topic of AI adoption in production, this paper follows the systematic approach of a SLR. For many fields, including management research, a SLR is an important tool to capture the diversity of existing knowledge on a specific topic for a scientific investigation [ 39 ]. The investigator often pursues multiple goals, such as capturing and assessing the existing environment and advancing the existing body of knowledge with a proprietary RQ [ 39 ] or identifying key research topics [ 40 ].

Our SLR aims to select, analyze, and synthesize findings from the existing literature on AI adoption in production over the past 24 years. In order to identify relevant data for our literature synthesis, we follow the systematic approach of the Preferred Reporting Items for Systematic reviews (PRISMA) [ 41 ]. In evaluating the findings, we draw on a mixed-methods approach, combining some quantitative analyses, especially on the descriptive aspects of the selected publications, as well as qualitative analyses aimed at evaluating and comparing the contents of the papers. Figure  1 graphically summarizes the methodological approach that guides the content of the following sub-chapters.

Methodical procedure of our SLR following PRISMA [ 41 ]

2.1 Data identification

Following the development of the specific RQs, we searched for suitable publications. To locate relevant studies, we chose to conduct a publication analysis in the databases Scopus, Web of Science and ScienceDirect as these databases primarily contain international scientific articles and provide a broad overview of the interdisciplinary research field and its findings. To align the search with the RQs [ 42 ], we applied predefined key words to search the titles, abstracts, and keywords of Scopus, Web of Science and ScienceDirect articles. Our research team conducted several pre-tests to determine the final search commands for which the test results were on target and increased the efficiency of the search [ 42 ]. Using the combination of Boolean operators, we covered the three topics of AI, production, and adoption by searching combinations of ‘Artificial Intelligence’ AND ‘production or manufacturing’ AND ‘adopt*’ in the three scientific databases. Although ‘manufacturing’ tends to stand for the whole sector and ‘production’ refers to the process, the two terms are often used to describe the same context. We also follow the view of Burbidge, Falster, Riis, Svendsen [ 43 ] and use the terms synonymously in this paper and therefore also include both terms as keywords in the study location as well as in the analysis.

AI research has been credited with a resurgence since 2010 [ 6 ], which is the reason for our choice of time horizon. Due to the increase in publications within the last years, we selected articles published online from 2010 to May 8, 2024 for our analysis. As document types, we included conference papers, articles, reviews, book chapters, conference reviews as well as books, focusing exclusively on contributions in English in the final publication stage. The result of the study location is a list of 3,833 documents whose titles, abstracts, and keywords meet the search criteria and are therefore included in the next step of the analysis.

2.2 Data analysis

For these 3,833 documents, we then conducted an abstract analysis, ‘us[ing] a set of explicit selection criteria to assess the relevance of each study found to see if it actually does address the research question’ [ 42 ]. For this step, we again conducted double-blind screenings (including a minimum of two reviewers) as pilot searches so that all reviewers have the same understanding of the decision rules and make equal decisions regarding their inclusion for further analysis.

To ensure the paper’s focus on all three topics regarded in our research (AI, production, and adoption), we followed clearly defined rules of inclusion and exclusion that all reviewers had to follow in the review process. As a first requirement for inclusion, AI must be the technology in focus that is analysed in the publication. If AI was only mentioned and not further specified, we excluded the publication. With a second requirement, we checked the papers for the context of analysis, which in our case must be production. If the core focus is beyond production, the publication was also excluded from further analysis. The third prerequisite for further consideration of the publication is the analysis of the adoption of a technology in the paper. If technology adoption is not addressed or adoption factors are not considered, we excluded the paper. An article was only selected for full-text analysis if, after analyzing the titles, abstracts, and keywords, a clear focus on all three research areas was visible and the inclusion criteria were met for all three contexts.

By using this tripartite inclusion analysis, we were able to analyse the publications in a structured way and to reduce the 3,833 selected documents in our double-blind approach to 300 articles that were chosen for the full-text analysis. In the process of finding full versions of these publications, we had to exclude three papers as we could not access them. For the rest of the 297 articles we obtained full access and thus included them for further analysis. After a thorough examination of the full texts, we again had to exclude 249 publications because they did not meet our content-related inclusion criteria mentioned above, although the abstract analysis gave indications that they did. As a result, we finally obtained 47 selected papers on which we base the literature analysis and synthesis (see Fig.  1 ).

2.3 Descriptive analysis

Figure  2 summarises the results of the descriptive analysis on the selected literature regarding AI adoption in production that we analyse in our SLR. From Fig.  2 a), which illustrates annual publication trends (2010–2024), the increase in publications on AI adoption in production over the past 5 years is evident, yet slightly declining after a peak in 2022. After a steady increase until 2022, in which 11 articles are included in the final analysis, 2023 features ten articles, followed by three articles for 2024 until the cut-off date in May 2024. Of the 47 papers identified through our search, the majority (n = 33) are peer-reviewed journal articles and the remaining thirteen contributions conference proceedings and one book chapter (see Fig.  2 b)).

Descriptive analyses of the selected articles addressing AI adoption in production

The identified contributions reveal some additional characteristics in terms of the authors country base (Fig.  2 c)) and research methods used (Fig.  2 d)). Almost four out of ten of the publications were written in collaboration with authors from several countries (n = 19). Six of the papers were published by authors from the United States, five from Germany and four from India. In terms of the applied research methods used by the researchers, a wide range of methods is used (see Fig.  2 c), with qualitative methods (n = 22) being the most frequently used.

2.4 Factor analysis

In order to derive a comprehensive list of factors that influence the use of AI in production at different levels, we follow a qualitative content analysis. It is based on inductive category development, avoiding prefabricated categories in order to allow new categories to emerge based on the content at hand [ 44 , 45 ]. To do this, we first read the entire text to gain an understanding of the content and then derive codes [ 46 ] that seem to capture key ideas [ 45 ]. The codes are subsequently sorted into distinct categories, each of which is clearly defined and establishes meaningful connections between different codes. Based on an iterative process with feedback loops, the assigned categories are continuously reviewed and updated as revisions are made [ 44 ].

Various factors at different levels are of significance to AI and influence technology adoption [ 47 , 48 ]. To identify the specific factors that are of importance for AI adoption in production, we analyze the selected contributions in terms of the factors considered, compare them with each other and consequently obtain a list of factors through a bottom-up approach. While some of the factors are based on empirical findings, others are expected factors that result from the research findings of the respective studies. Through our analysis, a list of 35 factors emerges that influence AI adoption in production which occur with varying frequency in the studies analyzed by our SLR. Table 1 visualizes each factor in the respective contributions sorted by the frequency of occurrence.

The presence of skills is considered a particularly important factor in AI adoption in the studies analyzed (n = 35). The availability of data (n = 25) as well as the need for ethical guidelines (n = 24) are also seen as key drivers of AI adoption, as data is seen as the basis for the implementation of AI and ethical issues must be addressed in handling such an advanced technology. As such, these three factors make up the accelerants of AI adoption in production that are most frequently cited in the studies analyzed.

Also of importance are issues of managerial support (n = 22), as well as performance measures and IT infrastructure (n = 20). Some factors were also mentioned, but only addressed by one study at a time: government support, industrial sector, product complexity, batch size, and R&D Intensity. These factors are often used as quantitatively measurable adoption factors, especially in empirical surveys, such the study by Kinkel, Baumgartner, Cherubini [ 36 ].

3 Factors influencing AI adoption

The 35 factors presented characteristically in Sect.  2.4 serve as the basis for our in-depth analysis and for developing a framework of influences on AI adoption in production which are grouped into supercategories. A supercategory describes a cluster of topics to which various factors of AI adoption in production can be assigned. We were able to define seven categories that influence AI adoption in production: the internal influences of ‘business and structure’, ‘organizational effectiveness’, ‘technology and system’, ‘data management’ as well as the external influences of the ‘regulatory environment’, ‘business environment’ and ‘economic environment’ (see Fig.  3 ). The factors that were mentioned most frequently (occurrence in at least half of the papers analyzed) are marked accordingly (*) in Fig.  3 .

Framework of factors influencing AI adoption in production

3.1 Internal Environment

The internal influences on AI adoption in production refer to factors that an organization carries internally and that thus also influence adoption from within. Such factors can usually be influenced and clearly controlled by the organization itself.

3.1.1 Business and structure

The supercategory ‘business and structure’ includes the various factors and characteristics that impact a company’s performance, operations, and strategic decision-making. By considering and analyzing these business variables when implementing AI in production processes, companies can develop effective strategies to optimize their performance, increase their competitiveness, and adapt to changes in the business environment.

To understand and grasp the benefits in the use of AI, quantitative performance measures for the current and potential use of AI in industrial production systems help to clarify the value and potential benefits of AI use [ 49 , 54 , 74 , 79 , 91 ]. Assessing possible risks [ 77 ] as well as the monetary expected benefits for AI (e.g. Return on Investment (ROI)) in production plays an important role for adoption decisions in market-oriented companies [ 57 , 58 , 63 , 65 , 78 ]. Due to financial constraints, managers behave cautiously in their investments [ 78 ], so they need to evaluate AI adoption as financially viable to want to make the investment [ 61 , 63 , 93 ] and also drive acceptance [ 60 ]. AI systems can significantly improve cost–benefit structures in manufacturing, thereby increasing the profitability of production systems [ 73 ] and making companies more resilient [ 75 ]. However, in most cases, the adoption of AI requires high investments and the allocation of resources (s.a. personnel or financial) for this purpose [ 50 , 51 , 57 , 80 , 94 ]. Consequently, a lack of budgets and high expected transition costs often hinder the implementation of smart concepts [ 56 , 62 , 67 , 82 , 84 , 92 ]. It is up to management to provide necessary funding for AI adoption [ 53 , 59 , 79 ], which is required, for example, for skill development of employees [ 59 , 61 , 63 ], IT adaptation [ 62 , 66 ], AI development [ 74 ] or hardware deployment [ 68 ]. In their empirical study, Kinkel, Baumgartner, Cherubini [ 36 ] confirm a positive correlation between company size and the intensity in the use of AI technologies. Large companies generally stand out with a higher propensity to adopt [ 53 ] as they have less difficulties in comparison to small firms regarding the availability of resources [ 69 ], such as know-how, budget [ 68 , 84 ] and general data organization [ 68 ]. Others argue that small companies tend to be more open to change and are characterized by faster decision-making processes [ 68 , 93 ]. Product complexity also influences a company’s propensity for AI. Companies that produce rather simple products are more likely to digitize, which in turn offers good starting points for AI adoption. On the other hand, complex product manufacturers (often characterized by small batch sizes) are often less able to standardize and automate [ 36 ]. The company’s produced batch size has a similar influence on AI adoption. Small and medium batch sizes in particular hinder the integration of intelligent technologies, as less automation often prevails here as well. Nevertheless, even small and medium lot sizes can benefit economically from AI [ 36 ]. Since a high R&D intensity indicates a high innovation capability of a company, it is assumed to have a positive influence on AI adoption, as companies with a high R&D intensity already invest heavily in and use new innovations. This in turn speaks for existing competencies, know how and structures [ 36 ].

3.1.2 Organizational effectiveness

This supercategory focuses on the broader aspects that contribute to the effectiveness, development, and success of an organization when implementing AI in a production context. As the factors are interconnected and influence each other, decision makers should consider them carefully.

Users´ trust in AI is an essential factor to enable successful AI adoption and use in production [ 52 , 68 , 78 , 79 , 88 , 90 ]. From the users´ perspective, AI often exhibits the characteristics of a black box because its inherent processes are not fully understood [ 50 , 90 ] which can lead individuals to develop a fear towards the unknown [ 71 ]. Because of this lack of understanding, successful interaction between humans and AI is not guaranteed [ 90 ], as trust is a foundation for decisions that machines are intended to make autonomously [ 52 , 91 ]. To strengthen faith in AI systems [ 76 , 80 ], AI users can be involved in AI design processes in order to understand appropriate tools [ 54 , 90 ]. In this context, trust is also discussed in close connection with transparency and regulation [ 79 ]. User resistance is considered a barrier to implementing new information technologies, as adoption requires change [ 53 , 62 , 92 ]. Ignorance, as a kind of resistance to change, is a main obstacle to successful digital transformation [ 51 , 56 , 65 ]. Some employees may resist the change brought about by AI because they fear losing their jobs [ 52 ] or have other concerns [ 78 ]. Overcoming resistance to technology adoption requires organizational change and is critical for the success of adoption [ 50 , 51 , 62 , 67 , 71 , 80 ]. Therefore, change management is important to create awareness of the importance of AI adoption and increase acceptance of the workforce [ 66 , 68 , 74 , 83 ]. Management commitment is seen as a significant driver of technology adoption [ 53 , 59 , 81 , 82 , 86 ] and a lack of commitment can negatively impact user adoption and workforce trust and lead to skepticism towards technology [ 86 ]. The top management’s understanding and support for the benefits of the adopted technology [ 53 , 56 , 67 , 78 , 93 , 94 ] enhances AI adoption, can prioritize its implementation and also affects the performance of the AI-enabled application [ 55 , 60 , 83 ]. Preparing, enabling, and thus empowering the workforce, are considered the management’s responsibility in the adoption of digital technologies [ 59 , 75 ]. This requires intelligent leadership [ 52 ] as decision makers need to integrate their workforce into decision-making processes [ 75 ]. Guidelines can support managers by providing access to best practices that help in the adoption of AI [ 50 ]. Critical measures to manage organizational change include the empowerment of visionaries or appointed AI champions leading the change and the collaborative development of digital roadmaps [ 54 , 62 ]. To demonstrate management commitment, managers can create such a dedicated role, consisting of an individual or a small group that is actively and enthusiastically committed to AI adoption in production. This body is considered the adoption manager, point of contact and internal driver of adoption [ 62 , 74 , 80 ]. AI initiatives in production do not necessarily have to be initiated by management. Although management support is essential for successful AI adoption, employees can also actively drive integration initially and thus realize pilot projects or initial trials [ 66 , 80 ]. The development of strategies as well as roadmaps is considered another enabling and necessary factor for the adoption of AI in production [ 50 , 53 , 54 , 62 , 71 , 93 ]. While many major AI strategies already exist at country level to further promote research and development of AI [ 87 ], strategy development is also important at the firm level [ 76 , 77 , 81 ]. In this context, strategies should not be delegated top-down, but be developed in a collaborative manner, i.e. by engaging the workforce [ 75 ] and be in alignment with clear visions [ 91 , 94 ]. Roadmaps are used to improve planning, support implementation, facilitate the adoption of smart technologies in manufacturing [ 93 ] and should be integrated into both business and IT strategy [ 62 , 66 ]. In practice, clear adoption roadmaps that provide approaches on how to effectively integrate AI into existing strategies and businesses are often lacking [ 56 , 87 ]. The need for AI-related skills in organizations is a widely discussed topic in AI adoption analyses [ 79 ]. In this context, the literature points both at the need for specific skills in the development and design of AI applications [ 57 , 71 , 72 , 73 , 76 , 93 ] as well as the skills in using the technology [ 53 , 65 , 73 , 74 , 75 , 84 , 93 ] which availability in the firm is not always given [ 49 ]. AI requires new digital skills [ 36 , 50 , 52 , 55 , 56 , 59 , 61 , 63 , 66 , 78 , 80 ], where e.g. advanced analytics [ 64 , 75 , 81 ], programming skills [ 68 ] and cybersecurity skills [ 78 , 93 ] gain importance. The lack of skills required for AI is seen as a major challenge of digital transformation, as a skilled workforce is considered a key resource for companies [ 51 , 54 , 56 , 60 , 62 , 67 , 69 , 70 , 82 , 93 ]. This lack of a necessary skillset hinders the adoption of AI tools in production systems [ 58 , 77 ]. Closely related to skills is the need for new training concepts, which organizations need to consider when integrating digital technologies [ 49 , 50 , 51 , 56 , 59 , 63 , 71 , 74 , 75 ]. Firms must invest in qualification in order to create necessary competences [ 73 , 78 , 80 , 81 , 92 ]. Additionally, education must target and further develop the skills required for effectively integrating intelligent technologies into manufacturing processes [ 54 , 61 , 62 , 83 ]. Regarding this issue, academic institutions must develop fitting curricula for data driven manufacturing engineering [ 64 ]. Another driving factor of AI adoption is the innovation culture of an organization, which is influenced by various drivers. For example, companies that operate in an environment with high innovation rates, facing intense competitive pressures are considered more likely to see smart technologies as a tool for strategic change [ 83 , 91 , 93 ]. These firms often invest in more expensive and advanced smart technologies as the pressure and resulting competition forces them to innovate [ 93 ]. Another way of approach this is that innovation capability can also be supported and complemented by AI, for example by intelligent systems supporting humans in innovation or even innovating on their own [ 52 ].The entrepreneurial orientation of a firm is characterized in particular by innovativeness [ 66 ], productivity [ 63 ], risk-taking [ 86 ] as well as continuous improvement [ 50 ]. Such characteristics of an innovating culture are considered essential for companies to recognise dynamic changes in the market and make adoption decisions [ 51 , 71 , 81 , 84 , 86 , 94 ]. The prevalence of a digital mindset in companies is important for technology adoption, as digital transformation affects the entire organizational culture and behavior [ 59 , 80 , 92 ] and a lack of a digital culture [ 50 , 65 ] as well as a ‘passive mindset’ [ 78 ] can hinder the digital transformation of firms. Organizations need to develop a corresponding culture [ 66 , 67 , 71 ], also referred to as ‘AI-ready-culture’ [ 54 ], that promotes development and encourages people and data through the incorporation of technology [ 71 , 75 ]. With the increasing adoption of smart technologies, a ‘new digital normal’ is emerging, characterized by hybrid work models, more human–machine interactions and an increased use of digital technologies [ 75 , 83 ].

3.1.3 Technology and System

The ‘technology and system’ supercategory focuses on the broader issues related to the technology and infrastructure that support organizational operations and provide the technical foundation for AI deployment.

By IT infrastructure we refer to issues regarding the foundational systems and IT needed for AI adoption in production. Industrial firms and their IT systems must achieve a mature technological readiness in order to enable successful AI adoption [ 51 , 60 , 67 , 69 , 83 ]. A lack of appropriate IT infrastructure [ 68 , 71 , 78 , 91 ] or small maturity of Internet of Things (IoT) technologies [ 70 ]) hinders the efficient use of data in production firms [ 56 ] which is why firms must update their foundational information systems for successful AI adoption [ 53 , 54 , 62 , 66 , 72 , 75 ]. IT and data security are fundamental for AI adoption and must be provided [ 50 , 51 , 68 , 82 ]. This requires necessary developments that can ensure security during AI implementation while complying with legal requirements [ 52 , 72 , 78 ]. Generally, security concerns are common when implementing AI innovations [ 72 , 79 , 91 , 94 ]. This fear of a lack of security can also prevent the release of (e.g. customer) data in a production environment [ 56 ]. Additionally, as industrial production systems are vulnerable to failures as well as cyberattacks, companies need to address security and cybersecurity measures [ 49 , 76 , 88 , 89 ]. Developing user-friendly AI solutions can facilitate the adoption of smart solutions by increasing user understanding and making systems easy to use by employees as well as quick to integrate [ 50 , 72 , 84 ]. When developing user-friendly solutions which satisfy user needs [ 76 ], it is particularly important to understand and integrate the user perspective in the development process [ 90 ]. If employees find technical solutions easy to use, they are more confident in its use and perceived usefulness increases [ 53 , 67 , 68 ]. The compatibility of AI with a firm and its existing systems, i.e., the extent to which AI matches existing processes, structures, and infrastructures [ 53 , 54 , 56 , 60 , 78 , 80 , 82 , 83 , 93 , 94 ], is considered an important requirement for the adoption of AI in IT systems [ 91 ]. Along with compatibility also comes connectivity, which is intended to ensure the links within the overall network and avoid silo thinking [ 59 ]. Connectivity and interoperability of AI-based processes within the company’s IT manufacturing systems must be ensured at different system levels and are considered key factors in the development of AI applications for production [ 50 , 72 , 89 ]. The design of modular AI solutions can increase system compatibility [ 84 ]. Firms deciding for AI adoption must address safety issues [ 51 , 54 , 59 , 72 , 73 , 78 ]. This includes both safety in the use and operation of AI [ 60 , 69 ]. In order to address safety concerns of integrating AI solutions in industrial systems [ 49 ], systems must secure high reliability [ 71 ]. AI can also be integrated as a safety enabler, for example, by providing technologies to monitor health and safety in the workplace to prevent fatigue and injury [ 75 ].

3.1.4 Data management

Since AI adoption in the organization is strongly data-driven, the ‘data management’ supercategory is dedicated to the comprehensive aspects related to the effective and responsible management of data within the organization.

Data privacy must be guaranteed when creating AI applications based on industrial production data [ 49 , 58 , 59 , 60 , 72 , 76 , 78 , 79 , 82 , 88 , 89 , 91 , 94 ] as ‘[M]anufacturing industries generate large volumes of unstructured and sensitive data during their daily operations’ [ 89 ]. Closely related to this is the need for anonymization and confidentiality of data [ 61 , 69 , 70 , 78 ]. The availability of large, heterogeneous data sets is essential for the digital transformation of organizations [ 52 , 59 , 78 , 80 , 88 , 89 ] and is considered one of the key drivers of AI innovation [ 62 , 68 , 72 , 86 ]. In production systems, lack of data availability is often a barrier to AI adoption [ 58 , 70 , 77 ]. In order to enable AI to establish relationships between data, the availability of large input data that is critical [ 62 , 76 , 81 ]. New AI models are trained with this data and can adapt as well as improve as they receive new data [ 59 , 62 ]. Big data can thus significantly improve the quality of AI applications [ 59 , 71 ]. As more and more data is generated in manufacturing [ 85 ], AI opens up new opportunities for companies to make use of it [ 62 ]. However, operational data are often unstructured, as they come from different sources and exist in diverse formats [ 85 , 87 ]. This challenges data processing, as data quality and origin are key factors in the management of data [ 78 , 79 , 80 , 88 , 89 , 91 ]. To make production data valuable and usable for AI, consistency of data and thus data integrity is required across manufacturing systems [ 50 , 62 , 77 , 84 ]. Another key prerequisites for AI adoption is data governance [ 56 , 59 , 67 , 68 , 71 , 78 , 88 ] which is an important asset to make use of data in production [ 50 ] and ensure the complex management of heterogenous data sets [ 89 ]. The interoperability of data and thus the foundation for the compatibility of AI with existing systems, i.e., the extent to which AI matches existing processes, structures, and infrastructures [ 53 , 56 , 84 , 93 ], is considered another important requirement for the adoption of AI in IT systems. Data interoperability in production systems can be hindered by missing data standards as different machines use different formats [ 87 ]. Data processing refers to techniques used to preparing data for analysis which is essential to obtain consistent results from data analytics in production [ 58 , 72 , 80 , 81 , 84 ]. In this process, the numerous, heterogeneous data from different sensors are processed in such a way that they can be used for further analyses [ 87 ]. The capability of production firms to process data and information is thus important to enable AI adoption [ 77 , 86 , 93 ]. With the increasing data generation in the smart and connected factory, the strategic relevance of data analytics is gaining importance [ 55 , 69 , 78 ], as it is essential for AI systems in performing advanced data analyses [ 49 , 67 , 72 , 86 , 88 ]. Using analytics, valuable insights can be gained from the production data obtained using AI systems [ 58 , 77 , 87 ]. In order to enable the processing of big data, a profound data infrastructure is necessary [ 65 , 75 , 87 ]. Facilities must be equipped with sensors, that collect data and model information, which requires investments from firms [ 72 ]. In addition, production firms must build the necessary skills, culture and capabilities for data analytics [ 54 , 75 , 87 , 93 ]. Data storage, one of the foundations and prerequisites for smart manufacturing [ 54 , 68 , 71 , 74 ], must be ensured in order to manage the larg amounts of data and thus realize the adoption of intelligent technologies in production [ 50 , 59 , 72 , 78 , 84 , 87 , 88 , 89 ].

3.2 External environment

The external drivers of AI adoption in production influence the organization through conditions and events from outside the firm and are therefore difficult to control by the organization itself.

3.2.1 Regulatory environment

This supercategory captures the broader concept of establishing rules, standards, and frameworks that guide the behavior, actions, and operations of individuals, organizations, and societies when implementing AI.

AI adoption in production faces many ethical challenges [ 70 , 72 , 79 ]. AI applications must be compliant with the requirements of organizational ethical standards and laws [ 49 , 50 , 59 , 60 , 62 , 75 ] which is why certain issues must be examined in AI adoption and AI design [ 62 , 73 , 82 , 91 ] so that fairness and justice are guaranteed [ 78 , 79 , 92 ]. Social rights, cultural values and norms must not be violated in the process [ 49 , 52 , 53 , 81 ]. In this context, the explainability and transparency of AI decisions also plays an important role [ 50 , 54 , 58 , 70 , 78 , 89 ] and can address the characteristic of AI of a black box [ 90 ]. In addition, AI applications must be compliant with legal and regulatory requirements [ 51 , 52 , 59 , 77 , 81 , 82 , 91 ] and be developed accordingly [ 49 , 76 ] in order to make organization processes using AI clear and effective [ 65 ]. At present, policies and regulation of AI are still in its infancy [ 49 ] and missing federal regulatory guidelines, standards as well as incentives hinder the adoption of AI [ 67 ] which should be expanded simultaneously to the expansion of AI technology [ 60 ]. This also includes regulations on the handling of data (e.g. anonymization of data) [ 61 , 72 ].

3.2.2 Business environment

The factors in the ‘business environment’ supercategory refer to the external conditions and influences that affect the operations, decision making, and performance of the company seeking to implement AI in a production context.

Cooperation and collaboration can influence the success of digital technology adoption [ 52 , 53 , 59 , 72 ], which is why partnerships are important for adoption [ 53 , 59 ] and can positively influence its future success [ 52 , 67 ]. Both intraorganizational and interorganizational knowledge sharing can positively influence AI adoption [ 49 ]. In collaborations, companies can use a shared knowledge base where data and process sharing [ 51 , 59 , 94 ] as well as social support systems strengthen feedback loops between departments [ 79 , 80 ]. With regard to AI adoption in firms, vendors as well as service providers need to collaborate closely to improve the compatibility and operational capability of smart technologies across different industries [ 82 , 93 ]. Without external IT support, companies can rarely integrate AI into their production processes [ 66 ], which is why thorough support from vendors can significantly facilitate the integration of AI into existing manufacturing processes [ 80 , 91 ]. Public–private collaborations can also add value and governments can target AI dissemination [ 60 , 74 ]. The support of the government also positively influences AI adoption. This includes investing in research projects and policies, building a regulatory setting as well as creating a collaborative environment [ 60 ]. Production companies are constantly exposed to changing conditions, which is why the dynamics of the environment is another factor influencing the adoption of AI [ 52 , 63 , 72 , 86 ]. Environmental dynamics influence the operational performance of firms and can favor an entrepreneurial orientation of firms [ 86 ]. In order to respond to dynamics, companies need to develop certain capabilities and resources (i.e. dynamic capabilities) [ 86 ]. This requires the development of transparency, agility, as well as resilience to unpredictable changes, which was important in the case of the COVID-19 pandemic, for example, where companies had to adapt quickly to changing environments [ 75 ]. A firm’s environment (e.g. governments, partners or customers) can also pressure companies to adopt digital technologies [ 53 , 67 , 82 , 91 ]. Companies facing intense competition are considered more likely to invest in smart technologies, as rivalry pushes them to innovate and they hope to gain competitive advantages from adoption [ 36 , 66 , 82 , 93 ].

3.2.3 Economic environment

By considering both the industrial sector and country within the subcategory ‘economic environment’, production firms can analyze the interplay between the two and understand how drivers can influence the AI adoption process in their industrial sector’s performance within a particular country.

The industrial sector of a firm influences AI adoption in production from a structural perspective, as it indicates variations in product characteristics, governmental support, the general digitalization status, the production environment as well as the use of AI technologies within the sector [ 36 ]. Another factor that influences AI adoption is the country in which a company is located. This influences not only cultural aspects, the availability of know-how and technology orientation, but also regulations, laws, standards and subsidies [ 36 ]. From another perspective, AI can also contribute to the wider socio-economic growth of economies by making new opportunities easily available and thus equipping e.g. more rural areas with advanced capabilities [ 78 ].

3.3 Future research directions

The analysis of AI adoption in production requires a comprehensive analysis of the various factors that influence the introduction of the innovation. As discussed by Kinkel, Baumgartner, Cherubini [ 36 ], our research also concludes that organizational factors have a particularly important role to play. After evaluating the individual drivers of AI adoption in production in detail in this qualitative synthesis, we draw a conclusion from the results and derive a research agenda from the analysis to serve as a basis for future research. The RQs emerged from the analyzed factors and are presented in Table  2 . We developed the questions based on the literature review and identified research gaps for every factor that was most frequently mentioned. From the factors analyzed and RQs developed, the internal environment has a strong influence on AI adoption in production, and organizational factors play a major role here.

Looking at the supercategory ‘business and environment’, performance indicators and investments are considered drivers of AI adoption in production. Indicators to measure the performance of AI innovations are necessary here so that managers can perform cost–benefit analyses and make the right decision for their company. There is a need for research here to support possible calculations and show managers a comprehensive view of the costs and benefits of technology in production. In terms of budget, it should be noted that AI adoption involves a considerable financial outlay that must be carefully weighed and some capital must be available to carry out the necessary implementation efforts (e.g., staffing costs, machine retrofits, change management, and external IT service costs). Since AI adoption is a complex process and turnkey solutions can seldom be implemented easily and quickly, but require many changes (not only technologically but also on an organizational level), it is currently difficult to estimate the necessary budgets and thus make them available. Especially the factors of the supercategory ‘organizational effectiveness’ drive AI adoption in production. Trust of the workforce is considered an important driver, which must be created in order to successfully implement AI. This requires measures that can support management in building trust. Closely related to this are the necessary change management processes that must be initiated to accompany the changes in a targeted manner. Management itself must also play a clear role in the introduction of AI and communicate its support, as this also influences the adoption. The development of clear processes and measures can help here. Developing roadmaps for AI adoption can facilitate the adoption process and promote strategic integration with existing IT and business strategy. Here, best practice roadmaps and necessary action steps can be helpful for companies. Skills are considered the most important driver for AI adoption in manufacturing. Here, there is a lack of clear approaches that support companies in identifying the range of necessary skills and, associated with this, also opportunities to further develop these skills in the existing workforce. Also, building a culture of innovation requires closer research that can help companies foster a conducive environment for AI adoption and the integration of other smart technologies. Steps for developing a positive mindset require further research that can provide approaches for necessary action steps and measures in creating a positive digital culture. With regard to ‘technology and system’, the factors of IT infrastructure and security in particular are driving AI adoption in production. Existing IT systems must reach a certain maturity to enable AI adoption on a technical level. This calls for clear requirements that visualize for companies which systems and standards are in place and where developments are needed. Security must be continuously ensured, for which certain standards and action catalogs must be developed. With regard to the supercategory ‘data management’, the availability of data is considered the basis for successful AI adoption, as no AI can be successfully deployed without data. In the production context in particular, this requires developments that support companies in the provision of data, which usually arises from very heterogeneous sources and forms. Data analytics must also be closely examined, and production companies usually need external support in doing so. The multitude of data also requires big data storage capabilities. Here, groundwork is needed to show companies options about the possibilities of different storage options (e.g., on premis vs. cloud-based).

In the ‘regulatory environment’, ethics in particular is considered a driver of AI adoption in production. Here, fundamental ethical factors and frameworks need to be developed that companies can use as a guideline to ensure ethical standards throughout the process. Cooperations and environmental dynamism drive the supercategory ‘business environment’. Collaborations are necessary to successfully implement AI adoption and action is needed to create the necessary contact facilitation bodies. In a competitive environment, companies have to make quick decisions under strong pressure, which also affects AI adoption. Here, guidelines and also best practice approaches can help to simplify decisions and quickly demonstrate the advantage of the solutions. There is a need for research in this context.

4 Conclusions

The use of AI technologies in production continues to gain momentum as managers hope to increase efficiency, productivity and reduce costs [ 9 , 13 , 20 ]. Although the benefits of AI adoption speak for themselves, implementing AI is a complex decision that requires a lot of knowledge, capital and change [ 95 ] and is influenced by various internal and external factors. Therefore, managers are still cautious about implementing the technology in a production context. Our SLR seeks to examine the emergent phenomenon of AI in production with the precise aim of understanding the factors influencing AI adoption and the key topics discussed in the literature when analyzing AI in a production context. For this purpose, we use the current state of research and examine the existing studies based on the methodology of a systematic literature analysis and respond to three RQs.

We answer RQ1 by closely analyzing the literature selected in our SLR to identify trends in current research on AI adoption in production. In this process, it becomes clear that the topic is gaining importance and that research has increased over the last few years. In the field of production, AI is being examined from various angles and current research addresses aspects from a business, human and technical perspective. In our response to RQ2 we synthesized the existing literature to derive 35 factors that influence AI adoption in production at different levels from inside or outside the organization. In doing so, we find that AI adoption in production poses particularly significant challenges to organizational effectiveness compared to other digital technologies and that the relevance of data management takes on a new dimension. Production companies often operate more traditionally and are sometimes rigid when it comes to change [ 96 , 97 ], which can pose organizational challenges when adopting AI. In addition, the existing machines and systems are typically rather heterogeneous and are subject to different digitalization standards, which in turn can hinder the availability of the necessary data for AI implementation [ 98 , 99 ]. We address RQ3 by deriving a research agenda, which lays a foundation for further scientific research and deepening the understanding of AI adoption in production. The results of our analysis can further help managers to better understand AI adoption and to pay attention to the different factors that influence the adoption of this complex technology.

4.1 Contributions

Our paper takes the first step towards analysing the current state of the research on AI adoption from a production perspective. We represent a holistic view on the topic, which is necessary to get a better understanding of AI in a production-context and build a comprehensive view on the different dimensions as well as factors influencing its adoption. To the best of our knowledge, this is the first contribution that systematises research about the adoption of AI in production. As such, it makes an important contribution to current AI and production research, which is threefold:

First, we highlight the characteristics of studies conducted in recent years on the topic of AI adoption in production, from which several features and developments can be deduced. Our results confirm the topicality of the issue and the increasing relevance of research in the field.

Having laid the foundations for understanding AI in production, we focused our research on the identification and systematization of the most relevant factors influencing AI adoption in production at different levels. This brings us to the second contribution, our comprehensive factor analysis of AI adoption in production provides a framework for further research as well as a potential basis for managers to draw upon when adopting AI. By systematizing the relevant factors influencing AI adoption in production, we derived a set of 35 researched factors associated with AI adoption in production. These factors can be clustered in two areas of analysis and seven respective supercategories. The internal environment area includes four levels of analysis: ‘business and structure’ (focusing on financial aspects and firm characteristics), ‘organizational effectiveness’ (focusing on human-centred factors), ‘technology and system’ (based on the IT infrastructure and systems) as well as ‘data management’ (including all data related factors). Three categories are assigned to the external environment: the ‘regulatory environment’ (such as ethics and the regulatory forms), the ‘business environment’ (focused on cooperation activities and dynamics in the firm environment) and the ‘economic environment’ (related to sectoral and country specifics).

Third, the developed research plan as outlined in Table  2 serves as an additional outcome of the SLR, identifying key RQs in the analyzed areas that can serve as a foundation for researchers to expand the research area of AI adoption in production. These RQs are related to the mostly cited factors analyzed in our SLR and aim to broaden the understanding on the emerging topic.

The resulting insights can serve as the basis for strategic decisions by production companies looking to integrate AI into their processes. Our findings on the factors influencing AI adoption as well as the developed research agenda enhance the practical understanding of a production-specific adoption. Hence, they can serve as the basis for strategic decisions for companies on the path to an effective AI adoption. Managers can, for example, analyse the individual factors in light of their company as well as take necessary steps to develop further aspects in a targeted manner. Researchers, on the other hand, can use the future research agenda in order to assess open RQs and can expand the state of research on AI adoption in production.

4.2 Limitations

Since a literature review must be restricted in its scope in order to make the analyses feasible, our study provides a starting point for further research. Hence, there is a need for further qualitative and quantitative empirical research on the heterogeneous nature of how firms configure their AI adoption process. Along these lines, the following aspects would be of particular interest for future research to improve and further validate the analytical power of the proposed framework.

First, the lack of research on AI adoption in production leads to a limited number of papers included in this SLR. As visualized in Fig.  2 , the number of publications related to the adoption of AI in production has been increasing since 2018 but is, to date, still at an early stage. For this reason, only 47 papers published until May 2024 addressing the production-specific adoption of AI were identified and therefore included in our analysis for in-depth investigation. This rather small number of papers included in the full-text analysis gives a limited view on AI adoption in production but allows a more detailed analysis. As the number of publications in this research field increases, there seems to be a lot of research happening in this field which is why new findings might be constantly added and developed as relevant in the future [ 39 ]. Moreover, in order to research AI adoption from a more practical perspective and thus to build up a broader, continuously updated view on AI adoption in production, future literature analyses could include other publication formats, e.g. study reports of research institutions and companies, as well discussion papers.

Second, the scope of the application areas of AI in production has been increasing rapidly. Even though our overview of the three main areas covered in the recent literature serves as a good basis for identifying the most dominant fields for AI adoption in production, a more detailed analysis could provide a better overview of possibilities for manufacturing companies. Hence, a further systematisation as well as evaluation of application areas for AI in production can provide managers with the information needed to decide where AI applications might be of interest for the specific company needs.

Third, the systematisation of the 35 factors influencing AI adoption in production serve as a good ground for identifying relevant areas influenced by and in turn influencing the adoption of AI. Further analyses should be conducted in order to extend this view and extend the framework. For example, our review could be combined with explorative research methods (such as case studies in production firms) in order to add the practical insights from firms adopting AI. This integration of practical experiences can also help exploit and monitor more AI-specific factors by observing AI adoption processes. In enriching the factors through in-depth analyses, the results of the identified AI adoption factors could also be examined in light of theoretical contributions like the technology-organization-environment (TOE) framework [ 47 ] and other adoption theories.

Fourth, in order to examine the special relevance of identified factors for AI adoption process and thus to distinguish it from the common factors influencing the adoption of more general digital technologies, there is a further need for more in-depth (ethnographic) research into their impacts on the adoption processes, particularly in the production context. Similarly, further research could use the framework introduced in this paper as a basis to develop new indicators and measurement concepts as well as to examine their impacts on production performance using quantitative methods.

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Heimberger, H., Horvat, D. & Schultmann, F. Exploring the factors driving AI adoption in production: a systematic literature review and future research agenda. Inf Technol Manag (2024). https://doi.org/10.1007/s10799-024-00436-z

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DOI : https://doi.org/10.1007/s10799-024-00436-z

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Nursing Literature Review Topics and Examples

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Nursing Literature Review Topics and Example– 49 Effective Topic Ideas to Get Your Creative Juices Flowing!

Are you a medical student brainstorming for his final literature review nursing topics, have you run out of ideas then let us inspire you again.

Nursing is one of the professions that need a lot of research and investigation to make sure that the experiments are updated. This profession mostly requires that the studies be current and qualitative which can discuss in detail the factors that influence a particular disease and its behaviors.

This is the only way an ailment can research its cure. This is the reason why it is so important for researchers to find the right nursing literature review topics example for them.

A nursing literature review can cater to the behavioral aspect of the ailment or the physical one but it is important to get a good mentorship in nursing a literature review so that you may choose the right theme for your study.

Below mentioned are some nursing literature review Topics examples that will help you select the right topic for your study.

Keep in mind that just because you are studying nursing does not mean that your nursing literature review topics must strictly be related to the field. It can range from hospital management to the cure of an ailment.

• Pain management in critically ill patients
• Clinical outcomes of evidence-based practice in nursing
• Impact of sleep deprivation on nurses and patient care
• The effectiveness of telehealth in nursing practice
• The role of the nurse in end-of-life care
• Ethical considerations in nursing research
• The impact of mindfulness on stress reduction in nurses
• The importance of cultural competence in nursing practice
• The impact of technology on nursing education and practice
• The role of the nurse in preventing healthcare-associated infections
• The effects of workplace violence on nurses
• The impact of nurse-to-patient ratios on patient outcomes
• The effects of sleep deprivation and fatigue on medical errors in nursing
• The impact of burnout on job satisfaction and turnover in nurses
• The impact of organizational culture on nurse satisfaction and retention
• The use of simulation in nursing education
• The effects of shift work on the physical and mental health of nurses
• The impact of leadership styles on nurse engagement and job satisfaction
• The use of telemedicine in rural healthcare
• The role of the nurse in promoting healthy lifestyles and preventing chronic diseases
• Major risks in the clinical management of patients with cancer
• Management problems faced in the care of elderly patients
• Knowledge management in clinical practice and use of evidence
• Disease management with the use of evidence-based medicine
• Leadership and ethics in evidence-based nursing practice
• Evidence-based guidelines in promoting quality healthcare
• Evidence-based practice as a theoretical and practical approach. nursing interventions
• Evaluating the impact of health-promoting interventions on public health in the UK
• AIDS and its social impact: A study in public health
• Exercise habits and their relation with the epidemiological patterns of cardiovascular risks
• Improving pregnancy outcomes and care with the help of midwives
• The role of community nursing in improving the quality of life of the elderly
• Health promotion through community nursing practice
• The collaborative roles of GPs, nurses, social workers, and policymakers in a community nursing center
• The growing problem of alcoholism and binge drinking among teenagers is an issue in public health
• The focus on public health policies in the UK as delineated by the Department of Health
• The policies and approaches of the World Health Organization in understanding child development
• Effectiveness and efficiency of the National Health Service in providing services to the elderly
• Factors in research, development, and strategic policies toward healthcare

Another great idea to come up with a research topic for you is to search the Internet for a current illness that has not been studied as frequently. Then take that up as your topic and conduct a study on the same. This will ensure that your nursing research is current and significant.

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Check out our other related posts for nursing dissertation topics and critical care nursing research topics .

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