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Research Methodology and Scientific Writing pp 93–133 Cite as

Experimental Research

• C. George Thomas 2  
• First Online: 25 February 2021

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Experiments are part of the scientific method that helps to decide the fate of two or more competing hypotheses or explanations on a phenomenon. The term ‘experiment’ arises from Latin, Experiri, which means, ‘to try’. The knowledge accrues from experiments differs from other types of knowledge in that it is always shaped upon observation or experience. In other words, experiments generate empirical knowledge. In fact, the emphasis on experimentation in the sixteenth and seventeenth centuries for establishing causal relationships for various phenomena happening in nature heralded the resurgence of modern science from its roots in ancient philosophy spearheaded by great Greek philosophers such as Aristotle.

The strongest arguments prove nothing so long as the conclusions are not verified by experience. Experimental science is the queen of sciences and the goal of all speculation . Roger Bacon (1214–1294)

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Thomas, C.G. (2021). Experimental Research. In: Research Methodology and Scientific Writing . Springer, Cham. https://doi.org/10.1007/978-3-030-64865-7_5

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Title: sv3d: novel multi-view synthesis and 3d generation from a single image using latent video diffusion.

Abstract: We present Stable Video 3D (SV3D) -- a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D generation propose techniques to adapt 2D generative models for novel view synthesis (NVS) and 3D optimization. However, these methods have several disadvantages due to either limited views or inconsistent NVS, thereby affecting the performance of 3D object generation. In this work, we propose SV3D that adapts image-to-video diffusion model for novel multi-view synthesis and 3D generation, thereby leveraging the generalization and multi-view consistency of the video models, while further adding explicit camera control for NVS. We also propose improved 3D optimization techniques to use SV3D and its NVS outputs for image-to-3D generation. Extensive experimental results on multiple datasets with 2D and 3D metrics as well as user study demonstrate SV3D's state-of-the-art performance on NVS as well as 3D reconstruction compared to prior works.

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• Published: 31 January 2024

Top-predator recovery abates geomorphic decline of a coastal ecosystem

• Brent B. Hughes   ORCID: orcid.org/0000-0002-2263-1554 1 , 2 ,
• Kathryn M. Beheshti 3 , 4 ,
• M. Tim Tinker 3 , 5 ,
• Christine Angelini 6 ,
• Charlie Endris 7 ,
• Lee Murai 8 ,
• Sean C. Anderson 9 , 10 ,
• Sarah Espinosa 3 ,
• Michelle Staedler   ORCID: orcid.org/0000-0002-1101-6580 11 ,
• Joseph A. Tomoleoni 12 ,
• Madeline Sanchez 1 &
• Brian R. Silliman 2  

Nature volume  626 ,  pages 111–118 ( 2024 ) Cite this article

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• Conservation biology
• Ecological modelling
• Ecosystem ecology

The recovery of top predators is thought to have cascading effects on vegetated ecosystems and their geomorphology 1 , 2 , but the evidence for this remains correlational and intensely debated 3 , 4 . Here we combine observational and experimental data to reveal that recolonization of sea otters in a US estuary generates a trophic cascade that facilitates coastal wetland plant biomass and suppresses the erosion of marsh edges—a process that otherwise leads to the severe loss of habitats and ecosystem services 5 , 6 . Monitoring of the Elkhorn Slough estuary over several decades suggested top-down control in the system, because the erosion of salt marsh edges has generally slowed with increasing sea otter abundance, despite the consistently increasing physical stress in the system (that is, nutrient loading, sea-level rise and tidal scour 7 , 8 , 9 ). Predator-exclusion experiments in five marsh creeks revealed that sea otters suppress the abundance of burrowing crabs, a top-down effect that cascades to both increase marsh edge strength and reduce marsh erosion. Multi-creek surveys comparing marsh creeks pre- and post-sea otter colonization confirmed the presence of an interaction between the keystone sea otter, burrowing crabs and marsh creeks, demonstrating the spatial generality of predator control of ecosystem edge processes: densities of burrowing crabs and edge erosion have declined markedly in creeks that have high levels of sea otter recolonization. These results show that trophic downgrading could be a strong but underappreciated contributor to the loss of coastal wetlands, and suggest that restoring top predators can help to re-establish geomorphic stability.

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Acknowledgements

B.B.H. was funded through the David H. Smith Research Conservation Fellowship and Cedar Tree Foundation and the Rebecca and Steve Sooy Fellowship in Marine Mammals; C.A. was supported by an NSF CAREER award (1652628); and B.R.S. was supported by the Stolarz Foundation, the Lenfest Ocean Program, Foundation of the Carolinas and an NSF CAREER award. We thank P. Daleo and M. Hensel for constructive comments on this manuscript. We also thank the staff and volunteers of the Monterey Bay Aquarium Sea Otter Program and Elkhorn Slough National Estuarine Research Reserve who contributed to sea otter abundance and foraging-data collection and experimental data collection. We dedicate this paper to J. Estes, whose pioneering career and mentorship were crucial to developing this research.

Author information

Authors and affiliations.

Department of Biology, Sonoma State University, Rohnert Park, CA, USA

Brent B. Hughes & Madeline Sanchez

Division of Marine Science and Conservation, Nicholas School of the Environment, Duke University, Beaufort, NC, USA

Brent B. Hughes & Brian R. Silliman

Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA

Kathryn M. Beheshti, M. Tim Tinker & Sarah Espinosa

Marine Science Institute, University of California Santa Barbara, Santa Barbara, CA, USA

Kathryn M. Beheshti

Nhydra Ecological Research, Head of St Margarets Bay, Nova Scotia, Canada

M. Tim Tinker

Department of Environmental Engineering Sciences, Engineering School for Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL, USA

Christine Angelini

Moss Landing Marine Laboratories, Geological Oceanography Lab, Moss Landing, CA, USA

Charlie Endris

Division of Regional Assistance, California Department of Water Resources, West Sacramento, CA, USA

Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, British Columbia, Canada

Sean C. Anderson

Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada

Monterey Bay Aquarium, Monterey, CA, USA

Michelle Staedler

Western Ecological Research Center, U.S. Geological Survey, Santa Cruz, CA, USA

Joseph A. Tomoleoni

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Contributions

B.B.H. conceived the idea, which was enhanced by discussions with B.R.S. B.B.H., B.R.S., K.M.B. and C.A. designed salt marsh and crab surveys and experiments. B.B.H. and K.M.B. collected salt marsh and crab data. C.E. and L.M. collected and analysed data for salt marsh and creek aerial data. M.T.T., M. Sanchez, M. Staedler, S.E. and J.A.T. designed and collected sea otter monitoring data. B.B.H., M.T.T. and S.C.A. analysed sea otter data. B.B.H. ran all other statistical analysis with guidance from B.R.S., S.C.A. and C.A. All authors contributed to editing and writing.

Corresponding author

Correspondence to Brent B. Hughes .

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Extended data figures and tables

Extended data fig. 1 results from a three-year sea otter-exclusion experiment testing the effects of otters and shore crabs on salt marsh vegetation..

a – d , Response variables measured are crab burrow density ( a ), bulk density (ww = wet weight) ( b ), sediment accretion (dw = dry weight) ( c ), and crab burrows ( d ). Crab densities (Extended Data Figs. 1 and 2 ) were sampled over three years (measured in number of shore crab per 2 m 2 ), the other response variables were sampled in year 2. The bars represent the mean, points are the data, and lines represent the differences in paired blocks (with the exception of d , which compares crab burrows in procedural controls and plots ( n  = 5) within the same creek, but are not paired). * P  < 0.05 for cage treatments using linear mixed models (continuous response data) and generalized linear mixed models (count response data) with assigning paired experimental plots (block) and site ( n  = 5) as random factors. NS, not significant.

Extended Data Fig. 2 Changes in shore crab densities when compared to the first survey in May 2014.

a , Open circles represent counts for individual plots and lines connect the same plots through time. Solid circles and vertical line segments represent the estimated mean and 95% CI for each sampling event. There was a small but significantly greater change in density of shore crab in No Otter plots compared to Otter plots when accounting for time ( P  = 0.047). b , c , Smoothers for day since start ( b ) and month used in the GAMM ( c ). Note: Final shore crab densities were analysed in December 2016 (see Extended Data Fig. 1a ).

Extended Data Fig. 3 Example of camera-trap data.

Here a sea otter is consuming a shore crab from our Procedural Control plots in one of the experimental creeks (top white box). The bottom image is a zoomed-in screenshot of the same foraging bout highlighted in the box with the sea otter floating over the Procedural Control. Shore crabs are the only known prey item for sea otters in pickleweed marshes. Photo credit: M. Sanchez.

Extended Data Fig. 4 Results of a shore crab feeding experiment on pickleweed aboveground and belowground biomass.

Each point represents a measurement of single-crab consumption (in fresh weight, fw) over a 72-h period. Controls had vegetation without crabs. Letters indicate significant differences ( P  < 0.05) using independent samples t -tests.

Extended Data Fig. 5 Results of a survey examining the relationship between shore crabs and sea otters in tidal creeks, and leverage analysis between sea otter crab consumption and erosion.

a , Results from a 2015 survey of crab densities on the marsh edge. Sea otter density was estimated using survey data from 2013−2015 in each replicate creek. Each point represents a mean along 100-m transects ( n  = 5 plots per creek) from 13 tidal creeks; grey areas represent ±95% CI, * P  < 0.05. b , Leverage analysis comparing the influence of each creek on the slope of the relationship between sea otter crab consumption and erosion.

Extended Data Fig. 6 Modelling erosion rates.

Left, erosion rate modelled as a function of time with a GAM. Individual lines represent 200 samples from the posterior distribution. Right, each posterior sample is converted to a starting creek width value of 1. The vertical lines indicate the year the second-stage model started (1992).

Extended Data Fig. 7 Illustration of the modelled reduction in the base rate of creek erosion as the number of otters increases.

The shape follows a Gompertz curve defined as implied by (1 − exp(− b O )), in which O represents the number of sea otters and b represents an estimated parameter. The line and ribbon indicate the median and 95% credible interval.

Extended Data Fig. 8 Posterior parameter distributions from modelling relative creek width as a function of a base rate of widening and an adjustment given the abundance of sea otters.

This model is referred to as the ‘second-stage model’ in the Methods. In this figure, the model is fitted to mean values from the first-stage model (that is, not propagating uncertainty) as an illustration. The full model used for inference is fitted to 200 samples from the first-stage model. Histograms on the diagonal show the distribution for an individual parameter and the off-diagonals show the bivariate distribution for pairs of parameters. The parameter ‘r’ is the base rate of widening, ‘a’ is the relative channel width in the first year, ‘b’ is the maximum reduction in widening per otter and ‘sigma’ is the lognormal observation error standard deviation.

Extended Data Fig. 9 Histograms of b and r posterior distributions from the second-stage model (while propagating uncertainty from the first model).

The parameter b represents the maximum reduction in widening per otter and r represents the base rate of widening.

Extended Data Fig. 10 Model outputs describing creek changes in width relative to the starting year and erosion accounting for sea otters.

Left, values of \({\hat{W}}_{t}\) (relative creek width) from the first-stage model (blue dots = means; blue line segments = 95% credible intervals) and predicted values μ t (black line = median; grey ribbon = 95% CI) from the second-stage model. Year increments start with year 1 as 1992. Right, the effective annual rate of erosion accounting for sea otters ( r eff ) through time as determined by the estimates of r (base rate of widening), b (maximum reduction in widening per sea otter) and the number of sea otters. Line and ribbon indicate median and 95% credible interval.

Supplementary information

Reporting summary, supplementary table 1.

Camera trapping of sea otter behaviour. Camera trap data collected in 2020 from two experimental sites documenting sea otter behaviours and foraging around experiment and non-experimental locations.

Supplementary Table 2

Summary of all datasets used in the study. This includes information about time period, spatial scale, sample frequency, sample size, the method and purpose for data collection, the response reported, the corresponding figure, and the file name as it appears on the data repository: https://github.com/bbhughes/otters-erosion .

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Hughes, B.B., Beheshti, K.M., Tinker, M.T. et al. Top-predator recovery abates geomorphic decline of a coastal ecosystem. Nature 626 , 111–118 (2024). https://doi.org/10.1038/s41586-023-06959-9

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Clinical Trials and Clinical Research: A Comprehensive Review

Venkataramana kandi.

1 Clinical Microbiology, Prathima Institute of Medical Sciences, Karimnagar, IND

Sabitha Vadakedath

2 Biochemistry, Prathima Institute of Medical Sciences, Karimnagar, IND

Clinical research is an alternative terminology used to describe medical research. Clinical research involves people, and it is generally carried out to evaluate the efficacy of a therapeutic drug, a medical/surgical procedure, or a device as a part of treatment and patient management. Moreover, any research that evaluates the aspects of a disease like the symptoms, risk factors, and pathophysiology, among others may be termed clinical research. However, clinical trials are those studies that assess the potential of a therapeutic drug/device in the management, control, and prevention of disease. In view of the increasing incidences of both communicable and non-communicable diseases, and especially after the effects that Coronavirus Disease-19 (COVID-19) had on public health worldwide, the emphasis on clinical research assumes extremely essential. The knowledge of clinical research will facilitate the discovery of drugs, devices, and vaccines, thereby improving preparedness during public health emergencies. Therefore, in this review, we comprehensively describe the critical elements of clinical research that include clinical trial phases, types, and designs of clinical trials, operations of trial, audit, and management, and ethical concerns.

Introduction and background

A clinical trial is a systematic process that is intended to find out the safety and efficacy of a drug/device in treating/preventing/diagnosing a disease or a medical condition [ 1 , 2 ]. Clinical trial includes various phases that include phase 0 (micro-dosing studies), phase 1, phase 2, phase 3, and phase 4 [ 3 ]. Phase 0 and phase 2 are called exploratory trial phases, phase 1 is termed the non-therapeutic phase, phase 3 is known as the therapeutic confirmatory phase, and phase 4 is called the post-approval or the post-marketing surveillance phase. Phase 0, also called the micro-dosing phase, was previously done in animals but now it is carried out in human volunteers to understand the dose tolerability (pharmacokinetics) before being administered as a part of the phase 1 trial among healthy individuals. The details of the clinical trial phases are shown in Table ​ Table1 1 .

This table has been created by the authors.

MTD: maximum tolerated dose; SAD: single ascending dose; MAD: multiple ascending doses; NDA: new drug application; FDA: food and drug administration

Clinical research design has two major types that include non-interventional/observational and interventional/experimental studies. The non-interventional studies may have a comparator group (analytical studies like case-control and cohort studies), or without it (descriptive study). The experimental studies may be either randomized or non-randomized. Clinical trial designs are of several types that include parallel design, crossover design, factorial design, randomized withdrawal approach, adaptive design, superiority design, and non-inferiority design. The advantages and disadvantages of clinical trial designs are depicted in Table ​ Table2 2 .

There are different types of clinical trials that include those which are conducted for treatment, prevention, early detection/screening, and diagnosis. These studies address the activities of an investigational drug on a disease and its outcomes [ 4 ]. They assess whether the drug is able to prevent the disease/condition, the ability of a device to detect/screen the disease, and the efficacy of a medical test to diagnose the disease/condition. The pictorial representation of a disease diagnosis, treatment, and prevention is depicted in Figure ​ Figure1 1 .

This figure has been created by the authors.

The clinical trial designs could be improvised to make sure that the study's validity is maintained/retained. The adaptive designs facilitate researchers to improvise during the clinical trial without interfering with the integrity and validity of the results. Moreover, it allows flexibility during the conduction of trials and the collection of data. Despite these advantages, adaptive designs have not been universally accepted among clinical researchers. This could be attributed to the low familiarity of such designs in the research community. The adaptive designs have been applied during various phases of clinical trials and for different clinical conditions [ 5 , 6 ]. The adaptive designs applied during different phases are depicted in Figure ​ Figure2 2 .

The Bayesian adaptive trial design has gained popularity, especially during the Coronavirus Disease-19 (COVID-19) pandemic. Such designs could operate under a single master protocol. It operates as a platform trial wherein multiple treatments can be tested on different patient groups suffering from disease [ 7 ].

In this review, we comprehensively discuss the essential elements of clinical research that include the principles of clinical research, planning clinical trials, practical aspects of clinical trial operations, essentials of clinical trial applications, monitoring, and audit, clinical trial data analysis, regulatory audits, and project management, clinical trial operations at the investigation site, the essentials of clinical trial experiments involving epidemiological, and genetic studies, and ethical considerations in clinical research/trials.

A clinical trial involves the study of the effect of an investigational drug/any other intervention in a defined population/participant. The clinical research includes a treatment group and a placebo wherein each group is evaluated for the efficacy of the intervention (improved/not improved) [ 8 ].

Clinical trials are broadly classified into controlled and uncontrolled trials. The uncontrolled trials are potentially biased, and the results of such research are not considered as equally as the controlled studies. Randomized controlled trials (RCTs) are considered the most effective clinical trials wherein the bias is minimized, and the results are considered reliable. There are different types of randomizations and each one has clearly defined functions as elaborated in Table ​ Table3 3 .

Principles of clinical trial/research

Clinical trials or clinical research are conducted to improve the understanding of the unknown, test a hypothesis, and perform public health-related research [ 2 , 3 ]. This is majorly carried out by collecting the data and analyzing it to derive conclusions. There are various types of clinical trials that are majorly grouped as analytical, observational, and experimental research. Clinical research can also be classified into non-directed data capture, directed data capture, and drug trials. Clinical research could be prospective or retrospective. It may also be a case-control study or a cohort study. Clinical trials may be initiated to find treatment, prevent, observe, and diagnose a disease or a medical condition.

Among the various types of clinical research, observational research using a cross-sectional study design is the most frequently performed clinical research. This type of research is undertaken to analyze the presence or absence of a disease/condition, potential risk factors, and prevalence and incidence rates in a defined population. Clinical trials may be therapeutic or non-therapeutic type depending on the type of intervention. The therapeutic type of clinical trial uses a drug that may be beneficial to the patient. Whereas in a non-therapeutic clinical trial, the participant does not benefit from the drug. The non-therapeutic trials provide additional knowledge of the drug for future improvements. Different terminologies of clinical trials are delineated in Table ​ Table4 4 .

In view of the increased cost of the drug discovery process, developing, and low-income countries depend on the production of generic drugs. The generic drugs are similar in composition to the patented/branded drug. Once the patent period is expired generic drugs can be manufactured which have a similar quality, strength, and safety as the patented drug [ 9 ]. The regulatory requirements and the drug production process are almost the same for the branded and the generic drug according to the Food and Drug Administration (FDA), United States of America (USA).

The bioequivalence (BE) studies review the absorption, distribution, metabolism, and excretion (ADME) of the generic drug. These studies compare the concentration of the drug at the desired location in the human body, called the peak concentration of the drug (Cmax). The extent of absorption of the drug is measured using the area under the receiver operating characteristic curve (AUC), wherein the generic drug is supposed to demonstrate similar ADME activities as the branded drug. The BE studies may be undertaken in vitro (fasting, non-fasting, sprinkled fasting) or in vivo studies (clinical, bioanalytical, and statistical) [ 9 ].

Planning clinical trial/research

The clinical trial process involves protocol development, designing a case record/report form (CRF), and functioning of institutional review boards (IRBs). It also includes data management and the monitoring of clinical trial site activities. The CRF is the most significant document in a clinical study. It contains the information collected by the investigator about each subject participating in a clinical study/trial. According to the International Council for Harmonisation (ICH), the CRF can be printed, optical, or an electronic document that is used to record the safety and efficacy of the pharmaceutical drug/product in the test subjects. This information is intended for the sponsor who initiates the clinical study [ 10 ].

The CRF is designed as per the protocol and later it is thoroughly reviewed for its correctness (appropriate and structured questions) and finalized. The CRF then proceeds toward the print taking the language of the participating subjects into consideration. Once the CRF is printed, it is distributed to the investigation sites where it is filled with the details of the participating subjects by the investigator/nurse/subject/guardian of the subject/technician/consultant/monitors/pharmacist/pharmacokinetics/contract house staff. The filled CRFs are checked for their completeness and transported to the sponsor [ 11 ].

Effective planning and implementation of a clinical study/trial will influence its success. The clinical study majorly includes the collection and distribution of the trial data, which is done by the clinical data management section. The project manager is crucial to effectively plan, organize, and use the best processes to control and monitor the clinical study [ 10 , 11 ].

The clinical study is conducted by a sponsor or a clinical research organization (CRO). A perfect protocol, time limits, and regulatory requirements assume significance while planning a clinical trial. What, when, how, and who are clearly planned before the initiation of a study trial. Regular review of the project using the bar and Gantt charts, and maintaining the timelines assume increased significance for success with the product (study report, statistical report, database) [ 10 , 11 ].

The steps critical to planning a clinical trial include the idea, review of the available literature, identifying a problem, formulating the hypothesis, writing a synopsis, identifying the investigators, writing a protocol, finding a source of funding, designing a patient consent form, forming ethics boards, identifying an organization, preparing manuals for procedures, quality assurance, investigator training and initiation of the trial by recruiting the participants [ 10 ].

The two most important points to consider before the initiation of the clinical trial include whether there is a need for a clinical trial, if there is a need, then one must make sure that the study design and methodology are strong for the results to be reliable to the people [ 11 ].

For clinical research to envisage high-quality results, the study design, implementation of the study, quality assurance in data collection, and alleviation of bias and confounding factors must be robust [ 12 ]. Another important aspect of conducting a clinical trial is improved management of various elements of clinical research that include human and financial resources. The role of a trial manager to make a successful clinical trial was previously reported. The trial manager could play a key role in planning, coordinating, and successfully executing the trial. Some qualities of a trial manager include better communication and motivation, leadership, and strategic, tactical, and operational skills [ 13 ].

Practical aspects of a clinical trial operations

There are different types of clinical research. Research in the development of a novel drug could be initiated by nationally funded research, industry-sponsored research, and clinical research initiated by individuals/investigators. According to the documents 21 code of federal regulations (CFR) 312.3 and ICH E-6 Good Clinical Practice (GCP) 1.54, an investigator is an individual who initiates and conducts clinical research [ 14 ]. The investigator plan, design, conduct, monitor, manage data, compile reports, and supervise research-related regulatory and ethical issues. To manage a successful clinical trial project, it is essential for an investigator to give the letter of intent, write a proposal, set a timeline, develop a protocol and related documents like the case record forms, define the budget, and identify the funding sources.

Other major steps of clinical research include the approval of IRBs, conduction and supervision of the research, data review, and analysis. Successful clinical research includes various essential elements like a letter of intent which is the evidence that supports the interest of the researcher to conduct drug research, timeline, funding source, supplier, and participant characters.

Quality assurance, according to the ICH and GCP guidelines, is necessary to be implemented during clinical research to generate quality and accurate data. Each element of the clinical research must have been carried out according to the standard operating procedure (SOP), which is written/determined before the initiation of the study and during the preparation of the protocol [ 15 ].

The audit team (quality assurance group) is instrumental in determining the authenticity of the clinical research. The audit, according to the ICH and GCP, is an independent and external team that examines the process (recording the CRF, analysis of data, and interpretation of data) of clinical research. The quality assurance personnel are adequately trained, become trainers if needed, should be good communicators, and must handle any kind of situation. The audits can be at the investigator sites evaluating the CRF data, the protocol, and the personnel involved in clinical research (source data verification, monitors) [ 16 ].

Clinical trial operations are governed by legal and regulatory requirements, based on GCPs, and the application of science, technology, and interpersonal skills [ 17 ]. Clinical trial operations are complex, time and resource-specific that requires extensive planning and coordination, especially for the research which is conducted at multiple trial centers [ 18 ].

Recruiting the clinical trial participants/subjects is the most significant aspect of clinical trial operations. Previous research had noted that most clinical trials do not meet the participant numbers as decided in the protocol. Therefore, it is important to identify the potential barriers to patient recruitment [ 19 ].

Most clinical trials demand huge costs, increased timelines, and resources. Randomized clinical trial studies from Switzerland were analyzed for their costs which revealed approximately 72000 USD for a clinical trial to be completed. This study emphasized the need for increased transparency with respect to the costs associated with the clinical trial and improved collaboration between collaborators and stakeholders [ 20 ].

Clinical trial applications, monitoring, and audit

Among the most significant aspects of a clinical trial is the audit. An audit is a systematic process of evaluating the clinical trial operations at the site. The audit ensures that the clinical trial process is conducted according to the protocol, and predefined quality system procedures, following GCP guidelines, and according to the requirements of regulatory authorities [ 21 ].

The auditors are supposed to be independent and work without the involvement of the sponsors, CROs, or personnel at the trial site. The auditors ensure that the trial is conducted by designated professionally qualified, adequately trained personnel, with predefined responsibilities. The auditors also ensure the validity of the investigational drug, and the composition, and functioning of institutional review/ethics committees. The availability and correctness of the documents like the investigational broacher, informed consent forms, CRFs, approval letters of the regulatory authorities, and accreditation of the trial labs/sites [ 21 ].

The data management systems, the data collection software, data backup, recovery, and contingency plans, alternative data recording methods, security of the data, personnel training in data entry, and the statistical methods used to analyze the results of the trial are other important responsibilities of the auditor [ 21 , 22 ].

According to the ICH-GCP Sec 1.29 guidelines the inspection may be described as an act by the regulatory authorities to conduct an official review of the clinical trial-related documents, personnel (sponsor, investigator), and the trial site [ 21 , 22 ]. The summary report of the observations of the inspectors is performed using various forms as listed in Table ​ Table5 5 .

FDA: Food and Drug Administration; IND: investigational new drug; NDA: new drug application; IRB: institutional review board; CFR: code of federal regulations

Because protecting data integrity, the rights, safety, and well-being of the study participants are more significant while conducting a clinical trial, regular monitoring and audit of the process appear crucial. Also, the quality of the clinical trial greatly depends on the approach of the trial personnel which includes the sponsors and investigators [ 21 ].

The responsibility of monitoring lies in different hands, and it depends on the clinical trial site. When the trial is initiated by a pharmaceutical industry, the responsibility of trial monitoring depends on the company or the sponsor, and when the trial is conducted by an academic organization, the responsibility lies with the principal investigator [ 21 ].

An audit is a process conducted by an independent body to ensure the quality of the study. Basically, an audit is a quality assurance process that determines if a study is carried out by following the SPOs, in compliance with the GCPs recommended by regulatory bodies like the ICH, FDA, and other local bodies [ 21 ].

An audit is performed to review all the available documents related to the IRB approval, investigational drug, and the documents related to the patient care/case record forms. Other documents that are audited include the protocol (date, sign, treatment, compliance), informed consent form, treatment response/outcome, toxic response/adverse event recording, and the accuracy of data entry [ 22 ].

Clinical trial data analysis, regulatory audits, and project management

The essential elements of clinical trial management systems (CDMS) include the management of the study, the site, staff, subject, contracts, data, and document management, patient diary integration, medical coding, monitoring, adverse event reporting, supplier management, lab data, external interfaces, and randomization. The CDMS involves setting a defined start and finishing time, defining study objectives, setting enrolment and termination criteria, commenting, and managing the study design [ 23 ].

Among the various key application areas of clinical trial systems, the data analysis assumes increased significance. The clinical trial data collected at the site in the form of case record form is stored in the CDMS ensuring the errors with respect to the double data entry are minimized.

Clinical trial data management uses medical coding, which uses terminologies with respect to the medications and adverse events/serious adverse events that need to be entered into the CDMS. The project undertaken to conduct the clinical trial must be predetermined with timelines and milestones. Timelines are usually set for the preparation of protocol, designing the CRF, planning the project, identifying the first subject, and timelines for recording the patient’s data for the first visit.

The timelines also are set for the last subject to be recruited in the study, the CRF of the last subject, and the locked period after the last subject entry. The planning of the project also includes the modes of collection of the data, the methods of the transport of the CRFs, patient diaries, and records of severe adverse events, to the central data management sites (fax, scan, courier, etc.) [ 24 ].

The preparation of SOPs and the type and timing of the quality control (QC) procedures are also included in the project planning before the start of a clinical study. Review (budget, resources, quality of process, assessment), measure (turnaround times, training issues), and control (CRF collection and delivery, incentives, revising the process) are the three important aspects of the implementation of a clinical research project.

In view of the increasing complexity related to the conduct of clinical trials, it is important to perform a clinical quality assurance (CQA) audit. The CQA audit process consists of a detailed plan for conducting audits, points of improvement, generating meaningful audit results, verifying SOP, and regulatory compliance, and promoting improvement in clinical trial research [ 25 ]. All the components of a CQA audit are delineated in Table ​ Table6 6 .

CRF: case report form; CSR: clinical study report; IC: informed consent; PV: pharmacovigilance; SAE: serious adverse event

Clinical trial operations at the investigator's site

The selection of an investigation site is important before starting a clinical trial. It is essential that the individuals recruited for the study meet the inclusion criteria of the trial, and the investigator's and patient's willingness to accept the protocol design and the timelines set by the regulatory authorities including the IRBs.

Before conducting clinical research, it is important for an investigator to agree to the terms and conditions of the agreement and maintain the confidentiality of the protocol. Evaluation of the protocol for the feasibility of its practices with respect to the resources, infrastructure, qualified and trained personnel available, availability of the study subjects, and benefit to the institution and the investigator is done by the sponsor during the site selection visit.

The standards of a clinical research trial are ensured by the Council for International Organizations of Medical Sciences (CIOMS), National Bioethics Advisory Commission (NBAC), United Nations Programme on Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS) (UNAIDS), and World Medical Association (WMA) [ 26 ].

Recommendations for conducting clinical research based on the WMA support the slogan that says, “The health of my patient will be my first consideration.” According to the International Code of Medical Ethics (ICME), no human should be physically or mentally harmed during the clinical trial, and the study should be conducted in the best interest of the person [ 26 ].

Basic principles recommended by the Helsinki declaration include the conduction of clinical research only after the prior proof of the safety of the drug in animal and lab experiments. The clinical trials must be performed by scientifically, and medically qualified and well-trained personnel. Also, it is important to analyze the benefit of research over harm to the participants before initiating the drug trials.

The doctors may prescribe a drug to alleviate the suffering of the patient, save the patient from death, and gain additional knowledge of the drug only after obtaining informed consent. Under the equipoise principle, the investigators must be able to justify the treatment provided as a part of the clinical trial, wherein the patient in the placebo arm may be harmed due to the unavailability of the therapeutic/trial drug.

Clinical trial operations greatly depend on the environmental conditions and geographical attributes of the trial site. It may influence the costs and targets defined by the project before the initiation. It was noted that one-fourth of the clinical trial project proposals/applications submit critical data on the investigational drug from outside the country. Also, it was noted that almost 35% of delays in clinical trials owing to patient recruitment with one-third of studies enrolling only 5% of the participants [ 27 ].

It was suggested that clinical trial feasibility assessment in a defined geographical region may be undertaken for improved chances of success. Points to be considered under the feasibility assessment program include if the disease under the study is related to the population of the geographical region, appropriateness of the study design, patient, and comparator group, visit intervals, potential regulatory and ethical challenges, and commitments of the study partners, CROs in respective countries (multi-centric studies) [ 27 ].

Feasibility assessments may be undertaken at the program level (ethics, regulatory, and medical preparedness), study level (clinical, regulatory, technical, and operational aspects), and at the investigation site (investigational drug, competency of personnel, participant recruitment, and retention, quality systems, and infrastructural aspects) [ 27 ].

Clinical trials: true experiments

In accordance with the revised schedule "Y" of the Drugs and Cosmetics Act (DCA) (2005), a drug trial may be defined as a systematic study of a novel drug component. The clinical trials aim to evaluate the pharmacodynamic, and pharmacokinetic properties including ADME, efficacy, and safety of new drugs.

According to the drug and cosmetic rules (DCR), 1945, a new chemical entity (NCE) may be defined as a novel drug approved for a disease/condition, in a specified route, and at a particular dosage. It also may be a new drug combination, of previously approved drugs.

A clinical trial may be performed in three types; one that is done to find the efficacy of an NCE, a comparison study of two drugs against a medical condition, and the clinical research of approved drugs on a disease/condition. Also, studies of the bioavailability and BE studies of the generic drugs, and the drugs already approved in other countries are done to establish the efficacy of new drugs [ 28 ].

Apart from the discovery of a novel drug, clinical trials are also conducted to approve novel medical devices for public use. A medical device is defined as any instrument, apparatus, appliance, software, and any other material used for diagnostic/therapeutic purposes. The medical devices may be divided into three classes wherein class I uses general controls; class II uses general and special controls, and class III uses general, special controls, and premarket approvals [ 28 ].

The premarket approval applications ensure the safety and effectiveness, and confirmation of the activities from bench to animal to human clinical studies. The FDA approval for investigational device exemption (IDE) for a device not approved for a new indication/disease/condition. There are two types of IDE studies that include the feasibility study (basic safety and potential effectiveness) and the pivotal study (trial endpoints, randomization, monitoring, and statistical analysis plan) [ 28 ].

As evidenced by the available literature, there are two types of research that include observational and experimental research. Experimental research is alternatively known as the true type of research wherein the research is conducted by the intervention of a new drug/device/method (educational research). Most true experiments use randomized control trials that remove bias and neutralize the confounding variables that may interfere with the results of research [ 28 ].

The variables that may interfere with the study results are independent variables also called prediction variables (the intervention), dependent variables (the outcome), and extraneous variables (other confounding factors that could influence the outside). True experiments have three basic elements that include manipulation (that influence independent variables), control (over extraneous influencers), and randomization (unbiased grouping) [ 29 ].

Experiments can also be grouped as true, quasi-experimental, and non-experimental studies depending on the presence of specific characteristic features. True experiments have all three elements of study design (manipulation, control, randomization), and prospective, and have great scientific validity. Quasi-experiments generally have two elements of design (manipulation and control), are prospective, and have moderate scientific validity. The non-experimental studies lack manipulation, control, and randomization, are generally retrospective, and have low scientific validity [ 29 ].

Clinical trials: epidemiological and human genetics study

Epidemiological studies are intended to control health issues by understanding the distribution, determinants, incidence, prevalence, and impact on health among a defined population. Such studies are attempted to perceive the status of infectious diseases as well as non-communicable diseases [ 30 ].

Experimental studies are of two types that include observational (cross-sectional studies (surveys), case-control studies, and cohort studies) and experimental studies (randomized control studies) [ 3 , 31 ]. Such research may pose challenges related to ethics in relation to the social and cultural milieu.

Biomedical research related to human genetics and transplantation research poses an increased threat to ethical concerns, especially after the success of the human genome project (HGP) in the year 2000. The benefits of human genetic studies are innumerable that include the identification of genetic diseases, in vitro fertilization, and regeneration therapy. Research related to human genetics poses ethical, legal, and social issues (ELSI) that need to be appropriately addressed. Most importantly, these genetic research studies use advanced technologies which should be equally available to both economically well-placed and financially deprived people [ 32 ].

Gene therapy and genetic manipulations may potentially precipitate conflict of interest among the family members. The research on genetics may be of various types that include pedigree studies (identifying abnormal gene carriers), genetic screening (for diseases that may be heritable by the children), gene therapeutics (gene replacement therapy, gene construct administration), HGP (sequencing the whole human genome/deoxyribonucleic acid (DNA) fingerprinting), and DNA, cell-line banking/repository [ 33 ]. The biobanks are established to collect and store human tissue samples like umbilical tissue, cord blood, and others [ 34 ].

Epidemiological studies on genetics are attempts to understand the prevalence of diseases that may be transmitted among families. The classical epidemiological studies may include single case observations (one individual), case series (< 10 individuals), ecological studies (population/large group of people), cross-sectional studies (defined number of individuals), case-control studies (defined number of individuals), cohort (defined number of individuals), and interventional studies (defined number of individuals) [ 35 ].

Genetic studies are of different types that include familial aggregation (case-parent, case-parent-grandparent), heritability (study of twins), segregation (pedigree study), linkage study (case-control), association, linkage, disequilibrium, cohort case-only studies (related case-control, unrelated case-control, exposure, non-exposure group, case group), cross-sectional studies, association cohort (related case-control, familial cohort), and experimental retrospective cohort (clinical trial, exposure, and non-exposure group) [ 35 ].

Ethics and concerns in clinical trial/research

Because clinical research involves animals and human participants, adhering to ethics and ethical practices assumes increased significance [ 36 ]. In view of the unethical research conducted on war soldiers after the Second World War, the Nuremberg code was introduced in 1947, which promulgated rules for permissible medical experiments on humans. The Nuremberg code suggests that informed consent is mandatory for all the participants in a clinical trial, and the study subjects must be made aware of the nature, duration, and purpose of the study, and potential health hazards (foreseen and unforeseen). The study subjects should have the liberty to withdraw at any time during the trial and to choose a physician upon medical emergency. The other essential principles of clinical research involving human subjects as suggested by the Nuremberg code included benefit to the society, justification of study as noted by the results of the drug experiments on animals, avoiding even minimal suffering to the study participants, and making sure that the participants don’t have life risk, humanity first, improved medical facilities for participants, and suitably qualified investigators [ 37 ].

During the 18th world medical assembly meeting in the year 1964, in Helsinki, Finland, ethical principles for doctors practicing research were proposed. Declaration of Helsinki, as it is known made sure that the interests and concerns of the human participants will always prevail over the interests of the society. Later in 1974, the National Research Act was proposed which made sure that the research proposals are thoroughly screened by the Institutional ethics/Review Board. In 1979, the April 18th Belmont report was proposed by the national commission for the protection of human rights during biomedical and behavioral research. The Belmont report proposed three core principles during research involving human participants that include respect for persons, beneficence, and justice. The ICH laid down GCP guidelines [ 38 ]. These guidelines are universally followed throughout the world during the conduction of clinical research involving human participants.

ICH was first founded in 1991, in Brussels, under the umbrella of the USA, Japan, and European countries. The ICH conference is conducted once every two years with the participation from the member countries, observers from the regulatory agencies, like the World Health Organization (WHO), European Free Trade Association (EFTA), and the Canadian Health Protection Branch, and other interested stakeholders from the academia and the industry. The expert working groups of the ICH ensure the quality, efficacy, and safety of the medicinal product (drug/device). Despite the availability of the Nuremberg code, the Belmont Report, and the ICH-GCP guidelines, in the year 1982, International Ethical Guidelines for Biomedical Research Involving Human Subjects was proposed by the CIOMS in association with WHO [ 39 ]. The CIOMS protects the rights of the vulnerable population, and ensures ethical practices during clinical research, especially in underdeveloped countries [ 40 ]. In India, the ethical principles for biomedical research involving human subjects were introduced by the Indian Council of Medical Research (ICMR) in the year 2000 and were later amended in the year 2006 [ 41 ]. Clinical trial approvals can only be done by the IRB approved by the Drug Controller General of India (DGCI) as proposed in the year 2013 [ 42 ].

Current perspectives and future implications

A recent study attempted to evaluate the efficacy of adaptive clinical trials in predicting the success of a clinical trial drug that entered phase 3 and minimizing the time and cost of drug development. This study highlighted the drawbacks of such clinical trial designs that include the possibility of type 1 (false positive) and type 2 (false negative) errors [ 43 ].

The usefulness of animal studies during the preclinical phases of a clinical trial was evaluated in a previous study which concluded that animal studies may not completely guarantee the safety of the investigational drug. This is noted by the fact that many drugs which passed toxicity tests in animals produced adverse reactions in humans [ 44 ].

The significance of BE studies to compare branded and generic drugs was reported previously. The pharmacokinetic BE studies of Amoxycillin comparing branded and generic drugs were carried out among a group of healthy participants. The study results have demonstrated that the generic drug had lower Cmax as compared to the branded drug [ 45 ].

To establish the BE of the generic drugs, randomized crossover trials are carried out to assess the Cmax and the AUC. The ratio of each pharmacokinetic characteristic must match the ratio of AUC and/or Cmax, 1:1=1 for a generic drug to be considered as a bioequivalent to a branded drug [ 46 ].

Although the generic drug development is comparatively more beneficial than the branded drugs, synthesis of extended-release formulations of the generic drug appears to be complex. Since the extended-release formulations remain for longer periods in the stomach, they may be influenced by gastric acidity and interact with the food. A recent study suggested the use of bio-relevant dissolution tests to increase the successful production of generic extended-release drug formulations [ 47 ].

Although RCTs are considered the best designs, which rule out bias and the data/results obtained from such clinical research are the most reliable, RCTs may be plagued by miscalculation of the treatment outcomes/bias, problems of cointerventions, and contaminations [ 48 ].

The perception of healthcare providers regarding branded drugs and their view about the generic equivalents was recently analyzed and reported. It was noted that such a perception may be attributed to the flexible regulatory requirements for the approval of a generic drug as compared to a branded drug. Also, could be because a switch from a branded drug to a generic drug in patients may precipitate adverse events as evidenced by previous reports [ 49 ].

Because the vulnerable population like drug/alcohol addicts, mentally challenged people, children, geriatric age people, military persons, ethnic minorities, people suffering from incurable diseases, students, employees, and pregnant women cannot make decisions with respect to participating in a clinical trial, ethical concerns, and legal issues may prop up, that may be appropriately addressed before drug trials which include such groups [ 50 ].

Conclusions

Clinical research and clinical trials are important from the public health perspective. Clinical research facilitates scientists, public health administrations, and people to increase their understanding and improve preparedness with reference to the diseases prevalent in different geographical regions of the world. Moreover, clinical research helps in mitigating health-related problems as evidenced by the current Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic and other emerging and re-emerging microbial infections. Clinical trials are crucial to the development of drugs, devices, and vaccines. Therefore, scientists are required to be up to date with the process and procedures of clinical research and trials as discussed comprehensively in this review.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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Introduction, implications.

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An experimental study of effects on schoolchildren of exposure to point-of-sale cigarette advertising and pack displays

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Melanie Wakefield, Daniella Germain, Sarah Durkin, Lisa Henriksen, An experimental study of effects on schoolchildren of exposure to point-of-sale cigarette advertising and pack displays, Health Education Research , Volume 21, Issue 3, July 2006, Pages 338–347, https://doi.org/10.1093/her/cyl005

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By creating a sense of familiarity with tobacco, cigarette advertising and bold packaging displays in stores where children often visit may help to pre-dispose them to smoking. A total of 605 ninth-grade students were randomly allocated to view a photograph of a typical convenience store point-of-sale which had been digitally manipulated to show either cigarette advertising and pack displays, pack displays only or no cigarettes. Students then completed a self-administered questionnaire. Compared with those who viewed the no cigarettes, students either in the display only condition or cigarette advertising condition perceived it would be easier to purchase tobacco from these stores. Those who saw the cigarette advertising perceived it would be less likely they would be asked for proof of age, and tended to think a greater number of stores would sell cigarettes to them, compared with respondents who saw no tobacco products. Respondents in the display only condition tended to recall displayed cigarette brands more often than respondents who saw no cigarettes. Cigarette advertising similarly influenced students, and tended to weaken students' resolve not to smoke in future. Retail tobacco advertising as well as cigarette pack displays may have adverse influences on youth, suggesting that tighter tobacco marketing restrictions are needed.

As usual avenues for tobacco advertising have become increasingly unavailable, the visual presence of the cigarette pack and the in-store pack display has become an essential means of communicating brand imagery for tobacco companies [ 1, 2 ]. Tobacco industry documents indicate that tobacco companies understood the importance of the cigarette pack display as a means of promoting brand awareness: ‘The aim of the exercise is instant recognition: (Horizon) along with Benson & Hedges, that's given us full gold and blue blocks on display and that helps our brands stand out’ [ 3 ].

It has been demonstrated that widespread in-store tobacco advertising can influence and distort adolescents' perceptions regarding popularity, use and availability of tobacco. Experimental research has shown that adolescents exposed to retail tobacco advertising perceived significantly easier access to cigarettes than a control group [ 4 ]. Advertising exposure also influenced perceptions about smoking prevalence, peer approval for smoking and support for tobacco control policies [ 4 ]. Another study [ 5 ] found that schoolchildren exposed to point-of-sale advertisements were more likely than those exposed to a photograph of a pack of cigarettes to report positive attributes of users of the brand of cigarettes. Further research has shown that adolescents who reported at least weekly exposure to retail tobacco marketing were more likely to have experimented with smoking [ 6 ] and that in-store branded tobacco advertising and promotion are strongly associated with choice of cigarette brands by adolescents [ 7 ].

The presence of tobacco in stores alongside everyday items such as confectionery, soft drinks and magazines helps to create a sense of familiarity with tobacco products. This familiarity may act to de-emphasize the serious health consequences of tobacco consumption and increase youth perceptions of the prevalence of smoking, as well as their perceived access to tobacco products [ 8 ]. The presence of tobacco products in neighbourhood retail outlets conveys to young people that tobacco use is desirable, socially acceptable and prevalent in society [ 9 ].

In Victoria, Australia, point-of-sale tobacco advertising has been banned since January 2002, and cigarette pack displays are limited to one pack face per brand variant. An observational study conducted following the implementation of this law found that, although compliance was evident, displays emerged that tilted packs towards the floor, providing maximum viewing of the top of all the packs queued in the display and a consequently greater visual and colourful presence for each brand variant [ 10 ]. Efforts to enhance the displays to achieve maximum ‘standout’ for cigarette brands has led researchers to be concerned that cigarette displays at the point-of-sale may be just as influential as traditional advertising, acting as a promotional tool for cigarette brands.

The present study aims to examine the effect of cigarette packaging displays and advertising at the point-of-sale on students' smoking-related perceptions, beliefs and intentions. Given previous research, we hypothesized that exposure to retail tobacco advertising and cigarette pack displays at the point-of-sale would influence students' perceptions about ease of access to cigarettes, normative beliefs about smoking, perceived harms of smoking, perceived popularity of cigarette brands and future intentions to smoke.

Participants

Data collection took place in late 2003 and early 2004 from a convenience sample of ninth-grade students (aged 14–15 years) from five secondary schools in Victoria, Australia: two Catholic boys schools, a private co-educational school, a public co-educational school and a Catholic girls' school. Three of the schools were located in areas that had above average level of socio-economic advantage for Victoria, while the other two schools were in areas that had below average level of socio-economic advantage [ 11 ].

Schools were approached by a research assistant to determine willingness to have their students involved in the study. Schools were informed that the study would be an investigation into product advertising in convenience stores. Specific detail about examining tobacco marketing was not disclosed, to avoid risk of priming student's responses. Information was sent home to students' parents, along with a consent form, to obtain parental permission to be involved in the study. Out of 886 ninth-grade students approached, active parental permission was obtained for 605 students, resulting in an overall response rate of 68%.

The between-subjects experimental study design was adapted from that developed by Henriksen et al. [ 4 ]. Within each classroom, participants were randomly exposed to one of the three point-of-sale conditions under the guise of pre-testing a news story written for teenagers.

No cigarettes

A convenience store's point-of-sale area with no visible tobacco presence.

Cigarette display

A convenience store's point-of-sale area with a cigarette pack display, but no cigarette advertising (as required by the current law in Victoria).

Cigarette advertising

A point-of-sale area with both cigarette advertising and cigarette pack displays.

A colour photograph of a point-of-sale section of a convenience store was digitally altered to create the three versions of the same retail environment. Adobe Photoshop was used to eliminate cigarette advertising and cigarette pack displays and to replace these with other non-tobacco product advertising or displays. No retailers or customers were visible in the photographs and references to store names were removed.

Trained research assistants visited schools to administer the study. Before the experimental manipulation, all students took part in a discussion designed to increase the salience of general brand advertising and display. Following the discussion of brand advertising, students within classrooms were randomly assigned to see photographs of one of the three conditions. A research assistant then read aloud a fictional news story about teen eating habits and visits to convenience stores. Students were told to look carefully at the photograph they were given of the point-of-sale, and asked to imagine walking around the shop noticing what to buy, while they listened to the story.

After the news story had been read out, the research assistant collected all point-of-sale photographs to ensure students did not subsequently refer back to them. Students then completed a brief questionnaire. The entire data collection session was completed during a class period of ∼45 min.

Dependent variables

Perceived difficulty of access.

Students were asked about their own, and students their age, likelihood of being able to purchase tobacco from the pictured stores, using a Likert scale ranging from ‘1 = very easy’ to ‘5 = very hard’. These two questions were combined and averaged to create an overall measure of perceived difficulty of purchasing tobacco (α > 0.70). Students were also asked about the likelihood they would be asked for proof of age if they tried to purchase cigarettes at the store, using a Likert scale ranging from ‘1 = very likely’ to ‘5 = very unlikely’. Finally, students were asked to estimate how many stores in their neighbourhood would sell tobacco to them, and to other students their age.

Normative beliefs

Perceived prevalence of smoking was assessed by asking how many out of 100 classmates in their year level, 100 high school students and 100 adults they thought smoked cigarettes at least once a week. Perceived approval of smoking was measured by asking students how much they agreed or disagreed on a Likert scale ranging from ‘1 = strongly agree’ to ‘5 = strongly disagree’ with a range of attributes to describe smokers (‘A teenager who smokes cigarettes seems … cool; successful; smart; healthy; athletic; and popular’). Perceived peer approval was measured by asking students whether most students their age, and most high school students, ‘think it's ok to smoke cigarettes once in a while’. These two questions measured on a Likert scale from ‘1 = strongly agree’ to ‘5 = strongly disagree’, were combined and averaged to create an overall ‘peer approval of smoking’ measure (α > 0.70).

Perceived harm

Students were asked whether they agreed or disagreed that ‘Smoking can harm your health’, and how dangerous they thought it was to smoke <10 cigarettes a day, and one or two cigarettes occasionally, on a Likert scale ranging from ‘1 = not dangerous’ to ‘3 = very dangerous’.

Perceived brand popularity

We asked students to nominate the brand they would be likely to smoke if they were a smoker, and then nominate what they thought were the most popular brands smoked by students their age and adults. In order to examine whether cigarette displays and advertising influenced which brands students thought were the most popular, the cigarette brands that were clearly advertised in the cigarette advertising condition (Benson & Hedges, Lucky Strike, Horizon, Marlboro and Winfield) were coded as ‘advertised brands’. Similarly, those cigarette brands that were the most prominent in the cigarette display and cigarette advertising conditions were coded as ‘prominently displayed brands’. These brands were determined by their visual presentation in the display, based on the criteria of being presented by a block of colour or a block with a distinctive feature of the pack (e.g. the prominent stripe on Alpine and Winfield packs). Prominently displayed brands included Horizon, Dunhill, Winfield, Benson & Hedges and Alpine.

Intention to smoke

To gauge students' future intentions to smoke, students were asked whether they thought they would smoke a cigarette at any time during the next year, with responses being ‘definitely not, probably not, probably yes or definitely yes’. Students who had not tried smoking were also asked if they thought they would try a cigarette soon, and also ‘If one of your best friends were to offer you a cigarette, would you smoke it?’ with responses also being ‘definitely not, probably not, probably yes or definitely yes’.

Descriptive variables

Students indicated their sex, whether they had any older brothers or sisters, or a parent or guardian who smoked and how many, if any, of their five best friends smoked. Students were also asked to indicate their frequency of visiting a convenience store, with response options being ‘practically every day, a few times a week, about once a week, about once a month or hardly ever’.

Following the method of Pierce et al. [ 12 ], students were categorized as non-susceptible never smokers, susceptible never smokers or experimenters. Students who reported trying smoking (even just a few puffs) were coded as ‘experimenters’. Students who had never smoked and indicated they would definitely not try smoking cigarettes ‘soon’ and ‘in the next year’, and would definitely not smoke a cigarette if one of their best friends were to offer them one, were coded as ‘non-susceptible never smokers’. Students who did not answer ‘definitely no’ to each circumstance were considered ‘susceptible never smokers’.

Finally, an ‘others smoking’ variable was created by combining students' responses to whether they had at least one parent who smokes, a sibling who smoked and how many of the respondent's best friends smoked. This was a continuous variable, where a lower value indicated less exposure to cigarettes from family and friends.

Chi-square analysis was used to determine whether random assignment produced equivalent groups in relation to tobacco use and other characteristics. To test hypotheses, generalized estimating equations (GEEs) with random effects were used to determine the effects of exposure to the three point-of-sale conditions, controlling for sex, smoking susceptibility and social and familial exposure to smoking. The school attended by respondents was treated as a random effect to account for clustering by school.

Logistic regression analyses were used to examine the relationship between the cigarette brands respondents thought were most popular among students and adults, and those cigarette brands that were advertised or displayed in the pictured stores.

Sample characteristics

The sample of 605 students consisted of 51% females, 41% of students had tried smoking cigarettes and 9% currently smoked. Of those who had not yet tried smoking, 11% said they would probably or definitely try a cigarette soon and 8% reported they would probably or definitely try smoking during the next year. Over one-third (36%) of students had at least one parent or guardian who smoked, 21% said they had at least one older brother or sister who smoked and 45% reported at least one of their best friends smoked.

Table I shows that the characteristics of students were equally distributed by condition in relation to demographic characteristics and peer and family exposure to smoking.

Student characteristics, by exposure condition

Regardless of experimental condition, students who were experimenting with smoking visited convenience stores more often ( ⁠ X ¯ = 3.1, on scale of 1 = practically every day to 5 = hardly ever) than those students who were susceptible non-smokers ( ⁠ X ¯ = 3.5) ( P = 0.002) and those who were non-susceptible non-smokers ( ⁠ X ¯ = 3.7) ( P < 0.01). There was no significant difference between the latter two conditions.

Perceived access to tobacco

Table II indicates that students who were exposed to either the cigarette display or the cigarette advertising conditions perceived it would be less difficult for either themselves or students their age to purchase tobacco, than those students who saw the no cigarettes condition ( P = 0.000). In addition, students who saw the cigarette advertising condition were less likely than respondents in the no cigarettes condition to report that they would be asked for proof of age if they tried to buy cigarettes ( P = 0.01).

Perceived access to cigarettes, by exposure condition

Covariates = sex, ‘susceptibility’ and ‘others smoking’, random effects = school id.

Scale: 1 (very easy) to 5 (very hard).

Significantly different ( P < 0.01) to condition a: no cigarettes.

Scale: 1 (very likely) to 5 (very unlikely).

Significantly different ( P < 0.05) to condition a: no cigarettes.

Trend towards a significant difference ( P < 0.1) between condition a: no cigarettes.

On average, students reported that at least one store in their neighbourhood would sell cigarettes to them ( ⁠ X ¯ = 1.5 stores) or students their age ( ⁠ X ¯ = 1.8 stores). Students who saw the no cigarettes condition tended to report a lower number of neighbourhood stores would sell them cigarettes ( ⁠ X ¯ = 1.4 stores), compared with those who saw the cigarette advertising point-of-sale ( ⁠ X ¯ = 1.7 stores) ( P = 0.07). There was no exposure effect for the number of neighbourhood stores that participants thought would sell to ‘students their age’.

Normative beliefs about smoking

On average, students thought ∼30% of students their age smoke cigarettes at least once a week, with no significant differences between the experimental conditions ( Table III ).

Perceived smoking prevalence, by exposure condition

Covariates = sex, susceptibility and others smoking, random effects = school id.

Trend towards a significant difference ( P < 0.1) between condition b: cigarette display.

Significantly different ( P < 0.05) to condition b: cigarette display.

Scale: 1 (strongly agree) to 5 (strongly disagree).

However, those in the cigarette advertising condition reported on average that ∼52% of high school students smoked at least once a week, compared with those who saw the cigarette display condition, who estimated ∼48% of high school students smoke ( P = 0.03).

Respondents who saw the cigarette advertising condition also thought a higher proportion of adults smoke (63%) than did those who saw the cigarette display condition (59%).

There was little variation between experimental conditions and students' approval of smoking ( P > 0.10). Students also tended to disagree with statements attributing positive characteristics to teenagers who smoked, with no significant differences between experimental conditions ( Table III ).

Perceived harm of smoking

Regardless of survey condition, most students agreed that smoking can harm your health ( ⁠ X ¯ = 1.3, SD = 0.81). Over half of students (52%) considered smoking <10 cigarettes a day ‘very dangerous’. However, only 15% of students thought smoking one or two cigarettes occasionally was ‘very dangerous’, with a further 55% considering it ‘a little dangerous’ and 25% ‘not dangerous’. Students who saw the cigarette advertising condition were significantly more likely ( P = 0.02) to consider smoking one or two cigarettes occasionally as less dangerous ( ⁠ X ¯ = 1.9), than were respondents who saw the cigarette display condition ( ⁠ X ¯ = 2.1) ( Table IV ).

Perceived harm of smoking, by exposure condition

Covariates = sex, susceptibility and others smoking; random effects = school id.

Scale: 1 (not dangerous) to 3 (very dangerous).

Future intentions to smoke

Students who saw the cigarette advertising condition tended to be more likely to suggest that they would smoke a cigarette any time during the following year ( ⁠ X ¯ = 2.0, on scale of ‘1 = definitely not’ to ‘4 = definitely yes’), compared with those who saw the cigarette display condition ( ⁠ X ¯ = 1.9) ( P = 0.07).

Examining only students who had not yet tried smoking ( n = 348), those who had been exposed to the cigarette advertising condition, were more likely to suggest that they would smoke a cigarette if one of their best friends offered them one, compared with those who saw the cigarette display condition ( P = 0.039). However, no significant exposure effects existed for never-smokers' intentions to try a cigarette ‘soon’ or during the following year ( P > 0.1).

Perceived popularity of cigarette brands and brand preferences

As shown in Table V , when asked to name cigarette brands that were most popular among adult smokers, students exposed to the cigarette advertising condition were more likely to report a cigarette brand that was advertised (Winfield, Horizon, Benson & Hedges, Marlboro or Lucky Strike), compared with those exposed to the no cigarettes condition ( P = 0.049). There was also a trend for respondents exposed to the cigarette advertising condition to report one of the advertised brands, more than those who saw the cigarette display condition ( P = 0.057).

Perceived cigarette brand popularity and brand preferences, by exposure condition

Tobacco brands that were prominently visible in the displays of the cigarette display and cigarette advertising conditions (i.e. Winfield, Horizon, Benson & Hedges, Alpine and Dunhill) were also related to which brands students thought were most popular among adults. There was a trend for those respondents who saw the cigarette display condition to report brands that were prominently displayed, more than students who saw the no cigarettes condition ( P = 0.052).

There were no significant differences between conditions in relation to the brands respondents thought were popular among students their age who smoke. However, when respondents were asked which cigarette brand they would try if they smoked, those exposed to the cigarette advertising condition also tended to report an advertised brand more than those who saw the cigarette display condition ( P = 0.09).

This experimental study aimed to assess whether cigarette pack displays in retail stores influenced students' perceptions about smoking in ways similar to those previously found for retail tobacco advertising [ 4 ].

Overall, our results suggest that the presence of cigarettes at the point-of-sale—whether cigarette display only or display plus tobacco advertising—increased students' perceptions about the ease of purchasing cigarettes. In addition, the presence of tobacco advertising decreased students' perceived likelihood of being asked for proof of age and tended to increase perceptions of the number of stores that would sell them cigarettes. This pattern of findings suggests the presence of displays in retail stores serve to create the perception among students that cigarettes are easily available and accessible in their community, while the presence of tobacco advertising further strengthens perceived ease of accessibility of cigarettes.

Our study findings also suggest that, like advertising, the cigarette pack display is an effective vehicle for promoting brand recall, as evidenced by the cigarette brands reported by students to be the most popular among adult smokers. High recall of cigarette brand names that were advertised in the pictured store, as well as cigarette brands that were prominent in the displays, suggests that tobacco companies are effectively using cigarette packaging displays as a communication device for creating and reinforcing brand awareness and recognition [ 7 ]. Cigarette brand names that were advertised in the pictured store also tended to affect the brands of cigarettes students reported they might try if they did smoke.

Exposure to point-of-sale advertising, but not displays, tended to weaken student's resolve not to smoke in the following year. Findings also indicate that exposure to advertising, as opposed to a pack display on its own, influenced whether students would accept a cigarette from one of their friends if they offered. In countries such as the United States in which point-of-sale tobacco advertising has continued to proliferate, this is great cause for concern. US Federal Trade Commission figures indicate that in 2002, tobacco companies spent $12.47 billion on tobacco promotion, a considerable amount of which was focused on the point-of-sale [ 13 ].

No effects were observed for most variables measuring perceived harm from smoking, except the perceived danger of smoking one or two cigarettes per day, which was significantly higher among those in the cigarette advertising condition than those in the cigarette display condition. Overall, we found no consistent effects of cigarette advertising or display on peer approval for smoking, the likelihood of positive attributes being ascribed to smokers, or overall harm from smoking. Several of the perceived harm variables and all the smoker attribute variables were highly skewed in a desirable direction, suggesting established views about smoking which may not be easy to manipulate by a single experimental exposure.

Results from this study support some of the findings of the experimental study of Henriksen et al. [ 4 ]. Like Henriksen et al. , we found that retail cigarette advertising induced significantly easier perceived access to cigarettes and increased perceived smoking prevalence of high school students and adults. However, unlike Henriksen et al. , cigarette advertising did not influence perceived prevalence of smoking among students their own age. We also did not find advertising to induce more positive appraisals of smokers. There were differences between our study and that of Henriksen et al. that may have accounted for differences in some findings. These include the fact that students are no longer routinely exposed to retail tobacco advertising in Australia, that Australian students were in Grade 9 (aged 14–15 years) only, rather than Grades 8 and 9 (aged 13–15 years), that Australian students were recruited by active, rather than passive consent, and that Australian students were exposed to only one photograph in each condition, rather than two. However, given these methodological and contextual differences, the fact that we did find experimental effects for most variables used in both studies suggests that the effects are relatively robust.

There were several study limitations, not the least of which was that the stimulus conditions were artificial. Students briefly viewed one of the three manipulated point-of-sale photographs in a classroom setting, rather than visiting a real store environment, so they may have perceived the photographs to be unrealistic, and may not have responded in the same way to a real life situation. However, the fact we did observe effects of the different point-of-sale photographs on students' perceptions about smoking even with a brief exposure suggests that the influence of cigarette advertising as well as pack displays in the actual store environment is probably considerable.

In addition, we cannot be certain that the responses of students who saw the store with no cigarettes were not influenced by their own memory of what a convenience store ‘usually’ looks like (i.e. in Victoria, with the presence of tobacco displays). Over one-third (35%, n = 74) of students who saw the store with no cigarettes reported that they had seen tobacco products, even though there was none present, and this false recognition was positively related to being a current smoker ( P < 0.05). It is possible that due to students' misperceptions of what they had seen during the experimental manipulation we may not have achieved a ‘clean’ measure of student's exposure to a store with no tobacco products, and therefore condition effects may have been diluted. This also suggests that cigarette displays maybe extremely salient to smoking teenagers and can potentially influence their recollections of this type of marketing.

We confirmed the finding of Henriksen et al. [ 6 ] that frequency of student visits to convenience stores was associated with a higher likelihood of experimenting with cigarettes, one interpretation being that there may be long-term cumulative effects of point-of-sale exposure. Future research might aim to study students' brand recall and perceptions about smoking immediately after exiting real stores that vary in dominance of cigarette displays at the point-of-sale.

A strength of the study was that we were able to randomize students to conditions within classrooms, rather than randomizing whole classrooms, as in the study of Henriksen et al. [ 4 ]. However, since data collection occurred within classrooms and only five schools were involved, there may still be clustering of respondents, so to be conservative, we analysed the data using GEEs with random effects, where the school attended by respondents was treated as a random effect. We also controlled for sex, smoking susceptibility and social and familial exposures to cigarette smoking. Thus, the effects observed in this study are independent of these other well-known influences on smoking perceptions.

This study suggests that the presence of cigarette displays at the point-of-sale, even in the absence of cigarette advertising, has adverse effects on students' perceptions about ease of access to cigarettes and brand recall, both factors that increase the risk of taking up smoking [ 14, 15 ]. Furthermore, the study suggests that cigarette advertising has similar effects, and may also weaken students' firm intentions not to smoke in future, a measure that also strongly predicts smoking uptake [ 16 ]. These findings make a case for eliminating cigarette advertising at the point-of-sale, and also for placing cigarettes out of sight in the retail environment, as has happened in Saskatechewan, Canada [ 17 ]. Such a move may help to curb the alarming rate of smoking uptake among adolescents.

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