example of experimental research paper pdf

Research Design in Business and Management pp 221–234 Cite as

Experimental Research Design

• Stefan Hunziker 3 &
• Michael Blankenagel 3  
• First Online: 10 November 2021

3033 Accesses

1 Citations

This chapter addresses the peculiarities, characteristics, and major fallacies of experimental research designs. Experiments have a long and important history in the social, natural, and medicinal sciences. Unfortunately, in business and management this looks differently. This is astounding, as experiments are suitable for analyzing cause-and-effect relationships. A true experiment is a brilliant method for finding out if one element really causes other elements. Also, researchers find relevant information on how to write an experimental research design paper and learn about typical methodologies used for this research design. The chapter closes with referring to overlapping and adjacent research designs.

This is a preview of subscription content, log in via an institution .

Buying options

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF

Tax calculation will be finalised at checkout

Purchases are for personal use only

Aronson, E., Ellsworth, P., Carlsmith, J., & Gonzales, M. (1990). Methods of research in social psychology (2nd ed.). McGraw-Hill.

Google Scholar  

Bargh, J., Chen, M., & Burrows, L. (1996). Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology., 71 (2), 230–244.

Article   Google Scholar  

Biais, B., & Weber, M. (2009). Hindsight bias, risk perception, and investment performance. Management Science, 55 (6), 1018–1029.

Bortz, J. & Döring, N. (2006). Forschungsmethoden und evaluation . Springer.

Bowlin, K. O., Hales, J., & Kachelmeier, S. J. (2009). Experimental evidence of how prior experience as an auditor influences managers’ strategic reporting decisions. Rev Account Stud, 14 (1), 63–87.

Burmeister, K., & Schade, C. (2007). Are entrepreneurs’ decisions more biased? An experimental investigation of the susceptibility to status quo bias. Journal of Business Venturing, 22 (3), 340–362.

Christensen, L. B. (2007). Experimental methodology . Pearson/Allyn and Bacon.

de Vaus, D. A. (2001). Research design in social research . Reprinted. Los Angeles: SAGE Publications, Inc.

Doyle, A. C. (1890). The sign of the four. Lippincott’s Monthly Magazine . Ward, Lock & Co.

Franke, N., Schreier, M., & Kaiser, U. (2010). The “I designed it myself” effect in mass customization. Management Science, 56 (1), 125–140.

Friese, M., Wilhelm, H., & Michaela, W. (2009). The impulsive consumer: Predicting consumer behavior with implicit reaction time measurements. Social Psychology of Consumer Behavior (pp. 335–364). Psychology Press.

Fromkin, H. L., & Streufert, S. (1976). Laboratory experimentation. In M. D. Dunnette (Ed.), Handbook of industrial and organizational psychology (pp. 415–465). Rand McNally College.

Harbring, C., & Irlenbusch, B. (2011). Sabotage in tournaments: evidence from a laboratory experiment. Management Science, 57 (4), 611–627.

Hennig-Thurau, T., Groth, M., Paul, M., & Gremler, D. D. (2006). Are all smiles created equal? How emotional contagion and emotional labor affect service relationships. Journal of Marketing, 70 (3), 58–73.

Homburg, C., Koschate, N., & Hoyer, W. D. (2005). Do Satisfied customers really pay more? A study of the relationship between customer satisfaction and willingness to pay. Journal of Marketing, 69 (2), 84–96.

Johnson, B. (2001). Toward a new classification of nonexperimental quantitative research. Educational Researcher, 30 (2), 3–13.

Koschate-Fischer, N., & Schandelmeier, S. (2014). A Guideline for Designing Experimental Studies in Marketing research and a Critical Discussion of Selected Problem Areas. Journal of Business Economics, 84 (6), 793–826.

Krishnaswamy K. N., Sivakumar A. I. & Mathirajan M. (2009). Management research methodology: Integration of principles, methods and techniques . Dorling Kindersley.

Lödding, H., & Lohmann, S. (2012). INCAP – applying short-term flexibility to control inventories. International Journal of Production Research, 50 (3), 909–919.

Mohnen, A., Pokorny, K., & Sliwka, D. (2008). Transparency, inequity aversion, and the dynamics of peer pressure in teams: Theory and evidence. Journal of Labor Economics, 26 (4), 693–720.

Perdue, B. C., & Summers, J. O. (1986). Checking the success of manipulations in marketing experiments. Journal of Marketing Research, 23 (4), 317–326.

Robson, C. (2011). Real world research: A resource for users of social research methods in applied settings (3rd ed.). Wiley.

Rogers, W. S. (2003). Social psychology: Experimental and critical approaches . Open University Press.

Sandri, S., Schade, C., Mußhoff, O., & Odening, M. (2010). Holding on for too long? An experimental study on inertia in entrepreneurs’ and non-entrepreneurs’ disinvestment choices. Journal of Economic Behavior & Organization, 76 (1), 30–44.

Schoen, K., & Crilly, N. (2012). Implicit methods for testing product preference: Exploratory studies with the affective simon task. In J. Brasset, J. McDonnell, & M. Malpass (Eds.), Proceedings of 8th international design and emotion conference, ed. London: Central Saint Martins College of Art and Design.

Stier, W. (1999). Empirische Forschungsmethoden . Springer.

Trochim, W. (2005). Research methods: The concise knowledge base. Atomic Dog Pub.

Weber, M., & Zuchel, H. (2005). How do prior outcomes affect risk attitude? Comparing escalation of commitment and the house-money effect. Decision Analysis, 2 (1), 30–43.

Download references

Author information

Authors and affiliations.

Wirtschaft/IFZ – Campus Zug-Rotkreuz, Hochschule Luzern, Zug-Rotkreuz, Zug , Switzerland

Stefan Hunziker & Michael Blankenagel

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Stefan Hunziker .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature

About this chapter

Cite this chapter.

Hunziker, S., Blankenagel, M. (2021). Experimental Research Design. In: Research Design in Business and Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34357-6_12

Download citation

DOI : https://doi.org/10.1007/978-3-658-34357-6_12

Published : 10 November 2021

Publisher Name : Springer Gabler, Wiesbaden

Print ISBN : 978-3-658-34356-9

Online ISBN : 978-3-658-34357-6

eBook Packages : Business and Economics (German Language)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

APA Sample Paper: Experimental Psychology

Welcome to the Purdue OWL

This page is brought to you by the OWL at Purdue University. When printing this page, you must include the entire legal notice.

Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

• - Google Chrome

Intended for healthcare professionals

• Access provided by Google Indexer
• My email alerts
• BMA member login
• Username * Password * Forgot your log in details? Need to activate BMA Member Log In Log in via OpenAthens Log in via your institution

Search form

• Advanced search
• Search responses
• Search blogs
• Beauty sleep:...

Beauty sleep: experimental study on the perceived health and attractiveness of sleep deprived people

• Related content
• Peer review
• John Axelsson , researcher 1 2 ,
• Tina Sundelin , research assistant and MSc student 2 ,
• Michael Ingre , statistician and PhD student 3 ,
• Eus J W Van Someren , researcher 4 ,
• Andreas Olsson , researcher 2 ,
• Mats Lekander , researcher 1 3
• 1 Osher Center for Integrative Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
• 2 Division for Psychology, Department of Clinical Neuroscience, Karolinska Institutet
• 3 Stress Research Institute, Stockholm University, Stockholm
• 4 Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, and VU Medical Center, Amsterdam, Netherlands
• Correspondence to: J Axelsson john.axelsson{at}ki.se
• Accepted 22 October 2010

Objective To investigate whether sleep deprived people are perceived as less healthy, less attractive, and more tired than after a normal night’s sleep.

Design Experimental study.

Setting Sleep laboratory in Stockholm, Sweden.

Participants 23 healthy, sleep deprived adults (age 18-31) who were photographed and 65 untrained observers (age 18-61) who rated the photographs.

Intervention Participants were photographed after a normal night’s sleep (eight hours) and after sleep deprivation (31 hours of wakefulness after a night of reduced sleep). The photographs were presented in a randomised order and rated by untrained observers.

Main outcome measure Difference in observer ratings of perceived health, attractiveness, and tiredness between sleep deprived and well rested participants using a visual analogue scale (100 mm).

Results Sleep deprived people were rated as less healthy (visual analogue scale scores, mean 63 (SE 2) v 68 (SE 2), P<0.001), more tired (53 (SE 3) v 44 (SE 3), P<0.001), and less attractive (38 (SE 2) v 40 (SE 2), P<0.001) than after a normal night’s sleep. The decrease in rated health was associated with ratings of increased tiredness and decreased attractiveness.

Conclusion Our findings show that sleep deprived people appear less healthy, less attractive, and more tired compared with when they are well rested. This suggests that humans are sensitive to sleep related facial cues, with potential implications for social and clinical judgments and behaviour. Studies are warranted for understanding how these effects may affect clinical decision making and can add knowledge with direct implications in a medical context.

Introduction

The recognition [of the case] depends in great measure on the accurate and rapid appreciation of small points in which the diseased differs from the healthy state Joseph Bell (1837-1911)

Good clinical judgment is an important skill in medical practice. This is well illustrated in the quote by Joseph Bell, 1 who demonstrated impressive observational and deductive skills. Bell was one of Sir Arthur Conan Doyle’s teachers and served as a model for the fictitious detective Sherlock Holmes. 2 Generally, human judgment involves complex processes, whereby ingrained, often less consciously deliberated responses from perceptual cues are mixed with semantic calculations to affect decision making. 3 Thus all social interactions, including diagnosis in clinical practice, are influenced by reflexive as well as reflective processes in human cognition and communication.

Sleep is an essential homeostatic process with well established effects on an individual’s physiological, cognitive, and behavioural functionality 4 5 6 7 and long term health, 8 but with only anecdotal support of a role in social perception, such as that underlying judgments of attractiveness and health. As illustrated by the common expression “beauty sleep,” an individual’s sleep history may play an integral part in the perception and judgments of his or her attractiveness and health. To date, the concept of beauty sleep has lacked scientific support, but the biological importance of sleep may have favoured a sensitivity to perceive sleep related cues in others. It seems warranted to explore such sensitivity, as sleep disorders and disturbed sleep are increasingly common in today’s 24 hour society and often coexist with some of the most common health problems, such as hypertension 9 10 and inflammatory conditions. 11

To describe the relation between sleep deprivation and perceived health and attractiveness we asked untrained observers to rate the faces of people who had been photographed after a normal night’s sleep and after a night of sleep deprivation. We chose facial photographs as the human face is the primary source of information in social communication. 12 A perceiver’s response to facial cues, signalling the bearer’s emotional state, intentions, and potential mate value, serves to guide actions in social contexts and may ultimately promote survival. 13 14 15 We hypothesised that untrained observers would perceive sleep deprived people as more tired, less healthy, and less attractive compared with after a normal night’s sleep.

Using an experimental design we photographed the faces of 23 adults (mean age 23, range 18-31 years, 11 women) between 14.00 and 15.00 under two conditions in a balanced design: after a normal night’s sleep (at least eight hours of sleep between 23.00-07.00 and seven hours of wakefulness) and after sleep deprivation (sleep 02.00-07.00 and 31 hours of wakefulness). We advertised for participants at four universities in the Stockholm area. Twenty of 44 potentially eligible people were excluded. Reasons for exclusion were reported sleep disturbances, abnormal sleep requirements (for example, sleep need out of the 7-9 hour range), health problems, or availability on study days (the main reason). We also excluded smokers and those who had consumed alcohol within two days of the protocol. One woman failed to participate in both conditions. Overall, we enrolled 12 women and 12 men.

The participants slept in their own homes. Sleep times were confirmed with sleep diaries and text messages. The sleep diaries (Karolinska sleep diary) included information on sleep latency, quality, duration, and sleepiness. Participants sent a text message to the research assistant by mobile phone (SMS) at bedtime and when they got up on the night before sleep deprivation. They had been instructed not to nap. During the normal sleep condition the participants’ mean duration of sleep, estimated from sleep diaries, was 8.45 (SE 0.20) hours. The sleep deprivation condition started with a restriction of sleep to five hours in bed; the participants sent text messages (SMS) when they went to sleep and when they woke up. The mean duration of sleep during this night, estimated from sleep diaries and text messages, was 5.06 (SE 0.04) hours. For the following night of total sleep deprivation, the participants were monitored in the sleep laboratory at all times. Thus, for the sleep deprivation condition, participants came to the laboratory at 22.00 (after 15 hours of wakefulness) to be monitored, and stayed awake for a further 16 hours. We therefore did not observe the participants during the first 15 hours of wakefulness, when they had had a slightly restricted sleep, but had good control over the last 16 hours of wakefulness when sleepiness increased in magnitude. For the sleep condition, participants came to the laboratory at 12.00 (after five hours of wakefulness). They were kept indoors two hours before being photographed to avoid the effects of exposure to sunlight and the weather. We had a series of five or six photographs (resolution 3872×2592 pixels) taken in a well lit room, with a constant white balance (×900l; colour temperature 4200 K, Nikon D80; Nikon, Tokyo). The white balance was differently set during the two days of the study and affected seven photographs (four taken during sleep deprivation and three during a normal night’s sleep). Removing these participants from the analyses did not affect the results. The distance from camera to head was fixed, as was the focal length, within 14 mm (between 44 and 58 mm). To ensure a fixed surface area of each face on the photograph, the focal length was adapted to the head size of each participant.

For the photo shoot, participants wore no makeup, had their hair loose (combed backwards if long), underwent similar cleaning or shaving procedures for both conditions, and were instructed to “sit with a straight back and look straight into the camera with a neutral, relaxed facial expression.” Although the photographer was not blinded to the sleep conditions, she followed a highly standardised procedure during each photo shoot, including minimal interaction with the participants. A blinded rater chose the most typical photograph from each series of photographs. This process resulted in 46 photographs; two (one from each sleep condition) of each of the 23 participants. This part of the study took place between June and September 2007.

In October 2007 the photographs were presented at a fixed interval of six seconds in a randomised order to 65 observers (mainly students at the Karolinska Institute, mean age 30 (range 18-61) years, 40 women), who were unaware of the conditions of the study. They rated the faces for attractiveness (very unattractive to very attractive), health (very sick to very healthy), and tiredness (not at all tired to very tired) on a 100 mm visual analogue scale. After every 23 photographs a brief intermission was allowed, including a working memory task lasting 23 seconds to prevent the faces being memorised. To ensure that the observers were not primed to tiredness when rating health and attractiveness they rated the photographs for attractiveness and health in the first two sessions and tiredness in the last. To avoid the influence of possible order effects we presented the photographs in a balanced order between conditions for each session.

Statistical analyses

Data were analysed using multilevel mixed effects linear regression, with two crossed independent random effects accounting for random variation between observers and participants using the xtmixed procedure in Stata 9.2. We present the effect of condition as a percentage of change from the baseline condition as the reference using the absolute value in millimetres (rated on the visual analogue scale). No data were missing in the analyses.

Sixty five observers rated each of the 46 photographs for attractiveness, health, and tiredness: 138 ratings by each observer and 2990 ratings for each of the three factors rated. When sleep deprived, people were rated as less healthy (visual analogue scale scores, mean 63 (SE 2) v 68 (SE 2)), more tired (53 (SE 3) v 44 (SE 3)), and less attractive (38 (SE 2) v 40 (SE 2); P<0.001 for all) than after a normal night’s sleep (table 1 ⇓ ). Compared with the normal sleep condition, perceptions of health and attractiveness in the sleep deprived condition decreased on average by 6% and 4% and tiredness increased by 19%.

 Multilevel mixed effects regression on effect of how sleep deprived people are perceived with respect to attractiveness, health, and tiredness

• View inline

A 10 mm increase in tiredness was associated with a −3.0 mm change in health, a 10 mm increase in health increased attractiveness by 2.4 mm, and a 10 mm increase in tiredness reduced attractiveness by 1.2 mm (table 2 ⇓ ). These findings were also presented as correlation, suggesting that faces with perceived attractiveness are positively associated with perceived health (r=0.42, fig 1 ⇓ ) and negatively with perceived tiredness (r=−0.28, fig 1). In addition, the average decrease (for each face) in attractiveness as a result of deprived sleep was associated with changes in tiredness (−0.53, n=23, P=0.03) and in health (0.50, n=23, P=0.01). Moreover, a strong negative association was found between the respective perceptions of tiredness and health (r=−0.54, fig 1). Figure 2 ⇓ shows an example of observer rated faces.

 Associations between health, tiredness, and attractiveness

Fig 1  Relations between health, tiredness, and attractiveness of 46 photographs (two each of 23 participants) rated by 65 observers on 100 mm visual analogue scales, with variation between observers removed using empirical Bayes’ estimates

• Download figure
• Open in new tab
• Download powerpoint

Fig 2  Participant after a normal night’s sleep (left) and after sleep deprivation (right). Faces were presented in a counterbalanced order

To evaluate the mediation effects of sleep loss on attractiveness and health, tiredness was added to the models presented in table 1 following recommendations. 16 The effect of sleep loss was significantly mediated by tiredness on both health (P<0.001) and attractiveness (P<0.001). When tiredness was added to the model (table 1) with an estimated coefficient of −2.9 (SE 0.1; P<0.001) the independent effect of sleep loss on health decreased from −4.2 to −1.8 (SE 0.5; P<0.001). The effect of sleep loss on attractiveness decreased from −1.6 (table 1) to −0.62 (SE 0.4; P=0.133), with tiredness estimated at −1.1 (SE 0.1; P<0.001). The same approach applied to the model of attractiveness and health (table 2), with a decrease in the association from 2.4 to 2.1 (SE 0.1; P<0.001) with tiredness estimated at −0.56 (SE 0.1; P<0.001).

Sleep deprived people are perceived as less attractive, less healthy, and more tired compared with when they are well rested. Apparent tiredness was strongly related to looking less healthy and less attractive, which was also supported by the mediating analyses, indicating that a large part of the found effects and relations on appearing healthy and attractive were mediated by looking tired. The fact that untrained observers detected the effects of sleep loss in others not only provides evidence for a perceptual ability not previously subjected to experimental control, but also supports the notion that sleep history gives rise to socially relevant signals that provide information about the bearer. The adaptiveness of an ability to detect sleep related facial cues resonates well with other research, showing that small deviations from the average sleep duration in the long term are associated with an increased risk of health problems and with a decreased longevity. 8 17 Indeed, even a few hours of sleep deprivation inflict an array of physiological changes, including neural, endocrinological, immunological, and cellular functioning, that if sustained are relevant for long term health. 7 18 19 20 Here, we show that such physiological changes are paralleled by detectable facial changes.

These results are related to photographs taken in an artificial setting and presented to the observers for only six seconds. It is likely that the effects reported here would be larger in real life person to person situations, when overt behaviour and interactions add further information. Blink interval and blink duration are known to be indicators of sleepiness, 21 and trained observers are able to evaluate reliably the drowsiness of drivers by watching their videotaped faces. 22 In addition, a few of the people were perceived as healthier, less tired, and more attractive during the sleep deprived condition. It remains to be evaluated in follow-up research whether this is due to random error noise in judgments, or associated with specific characteristics of observers or the sleep deprived people they judge. Nevertheless, we believe that the present findings can be generalised to a wide variety of settings, but further studies will have to investigate the impact on clinical studies and other social situations.

Importantly, our findings suggest a prominent role of sleep history in several domains of interpersonal perception and judgment, in which sleep history has previously not been considered of importance, such as in clinical judgment. In addition, because attractiveness motivates sexual behaviour, collaboration, and superior treatment, 13 sleep loss may have consequences in other social contexts. For example, it has been proposed that facial cues perceived as attractive are signals of good health and that this recognition has been selected evolutionarily to guide choice of mate and successful transmission of genes. 13 The fact that good sleep supports a healthy look and poor sleep the reverse may be of particular relevance in the medical setting, where health estimates are an essential part. It is possible that people with sleep disturbances, clinical or otherwise, would be judged as more unhealthy, whereas those who have had an unusually good night’s sleep may be perceived as rather healthy. Compared with the sleep deprivation used in the present investigation, further studies are needed to investigate the effects of less drastic acute reductions of sleep as well as long term clinical effects.

Conclusions

People are capable of detecting sleep loss related facial cues, and these cues modify judgments of another’s health and attractiveness. These conclusions agree well with existing models describing a link between sleep and good health, 18 23 as well as a link between attractiveness and health. 13 Future studies should focus on the relevance of these facial cues in clinical settings. These could investigate whether clinicians are better than the average population at detecting sleep or health related facial cues, and whether patients with a clinical diagnosis exhibit more tiredness and are less healthy looking than healthy people. Perhaps the more successful doctors are those who pick up on these details and act accordingly.

Taken together, our results provide important insights into judgments about health and attractiveness that are reminiscent of the anecdotal wisdom harboured in Bell’s words, and in the colloquial notion of “beauty sleep.”

What is already known on this topic

Short or disturbed sleep and fatigue constitute major risk factors for health and safety

Complaints of short or disturbed sleep are common among patients seeking healthcare

The human face is the main source of information for social signalling

What this study adds

The facial cues of sleep deprived people are sufficient for others to judge them as more tired, less healthy, and less attractive, lending the first scientific support to the concept of “beauty sleep”

By affecting doctors’ general perception of health, the sleep history of a patient may affect clinical decisions and diagnostic precision

Cite this as: BMJ 2010;341:c6614

We thank B Karshikoff for support with data acquisition and M Ingvar for comments on an earlier draft of the manuscript, both without compensation and working at the Department for Clinical Neuroscience, Karolinska Institutet, Sweden.

Contributors: JA designed the data collection, supervised and monitored data collection, wrote the statistical analysis plan, carried out the statistical analyses, obtained funding, drafted and revised the manuscript, and is guarantor. TS designed and carried out the data collection, cleaned the data, drafted, revised the manuscript, and had final approval of the manuscript. JA and TS contributed equally to the work. MI wrote the statistical analysis plan, carried out the statistical analyses, drafted the manuscript, and critically revised the manuscript. EJWVS provided statistical advice, advised on data handling, and critically revised the manuscript. AO provided advice on the methods and critically revised the manuscript. ML provided administrative support, drafted the manuscript, and critically revised the manuscript. All authors approved the final version of the manuscript.

Funding: This study was funded by the Swedish Society for Medical Research, Rut and Arvid Wolff’s Memory Fund, and the Osher Center for Integrative Medicine.

Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any company for the submitted work; no financial relationships with any companies that might have an interest in the submitted work in the previous 3 years; no other relationships or activities that could appear to have influenced the submitted work.

Ethical approval: This study was approved by the Karolinska Institutet’s ethical committee. Participants were compensated for their participation.

Participant consent: Participant’s consent obtained.

Data sharing: Statistical code and dataset of ratings are available from the corresponding author at john.axelsson{at}ki.se .

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode .

• ↵ Deten A, Volz HC, Clamors S, Leiblein S, Briest W, Marx G, et al. Hematopoietic stem cells do not repair the infarcted mouse heart. Cardiovasc Res 2005 ; 65 : 52 -63. OpenUrl Abstract / FREE Full Text
• ↵ Doyle AC. The case-book of Sherlock Holmes: selected stories. Wordsworth, 1993.
• ↵ Lieberman MD, Gaunt R, Gilbert DT, Trope Y. Reflection and reflexion: a social cognitive neuroscience approach to attributional inference. Adv Exp Soc Psychol 2002 ; 34 : 199 -249. OpenUrl CrossRef
• ↵ Drummond SPA, Brown GG, Gillin JC, Stricker JL, Wong EC, Buxton RB. Altered brain response to verbal learning following sleep deprivation. Nature 2000 ; 403 : 655 -7. OpenUrl CrossRef PubMed
• ↵ Harrison Y, Horne JA. The impact of sleep deprivation on decision making: a review. J Exp Psychol Appl 2000 ; 6 : 236 -49. OpenUrl CrossRef PubMed Web of Science
• ↵ Huber R, Ghilardi MF, Massimini M, Tononi G. Local sleep and learning. Nature 2004 ; 430 : 78 -81. OpenUrl CrossRef PubMed Web of Science
• ↵ Spiegel K, Leproult R, Van Cauter E. Impact of sleep debt on metabolic and endocrine function. Lancet 1999 ; 354 : 1435 -9. OpenUrl CrossRef PubMed Web of Science
• ↵ Kripke DF, Garfinkel L, Wingard DL, Klauber MR, Marler MR. Mortality associated with sleep duration and insomnia. Arch Gen Psychiatry 2002 ; 59 : 131 -6. OpenUrl CrossRef PubMed Web of Science
• ↵ Olson LG, Ambrogetti A. Waking up to sleep disorders. Br J Hosp Med (Lond) 2006 ; 67 : 118 , 20. OpenUrl PubMed
• ↵ Rajaratnam SM, Arendt J. Health in a 24-h society. Lancet 2001 ; 358 : 999 -1005. OpenUrl CrossRef PubMed Web of Science
• ↵ Ranjbaran Z, Keefer L, Stepanski E, Farhadi A, Keshavarzian A. The relevance of sleep abnormalities to chronic inflammatory conditions. Inflamm Res 2007 ; 56 : 51 -7. OpenUrl CrossRef PubMed Web of Science
• ↵ Haxby JV, Hoffman EA, Gobbini MI. The distributed human neural system for face perception. Trends Cogn Sci 2000 ; 4 : 223 -33. OpenUrl CrossRef PubMed Web of Science
• ↵ Rhodes G. The evolutionary psychology of facial beauty. Annu Rev Psychol 2006 ; 57 : 199 -226. OpenUrl CrossRef PubMed Web of Science
• ↵ Todorov A, Mandisodza AN, Goren A, Hall CC. Inferences of competence from faces predict election outcomes. Science 2005 ; 308 : 1623 -6. OpenUrl Abstract / FREE Full Text
• ↵ Willis J, Todorov A. First impressions: making up your mind after a 100-ms exposure to a face. Psychol Sci 2006 ; 17 : 592 -8. OpenUrl Abstract / FREE Full Text
• ↵ Krull JL, MacKinnon DP. Multilevel modeling of individual and group level mediated effects. Multivariate Behav Res 2001 ; 36 : 249 -77. OpenUrl CrossRef Web of Science
• ↵ Ayas NT, White DP, Manson JE, Stampfer MJ, Speizer FE, Malhotra A, et al. A prospective study of sleep duration and coronary heart disease in women. Arch Intern Med 2003 ; 163 : 205 -9. OpenUrl CrossRef PubMed Web of Science
• ↵ Bryant PA, Trinder J, Curtis N. Sick and tired: does sleep have a vital role in the immune system. Nat Rev Immunol 2004 ; 4 : 457 -67. OpenUrl CrossRef PubMed Web of Science
• ↵ Cirelli C. Cellular consequences of sleep deprivation in the brain. Sleep Med Rev 2006 ; 10 : 307 -21. OpenUrl CrossRef PubMed Web of Science
• ↵ Irwin MR, Wang M, Campomayor CO, Collado-Hidalgo A, Cole S. Sleep deprivation and activation of morning levels of cellular and genomic markers of inflammation. Arch Intern Med 2006 ; 166 : 1756 -62. OpenUrl CrossRef PubMed Web of Science
• ↵ Schleicher R, Galley N, Briest S, Galley L. Blinks and saccades as indicators of fatigue in sleepiness warnings: looking tired? Ergonomics 2008 ; 51 : 982 -1010. OpenUrl CrossRef PubMed Web of Science
• ↵ Wierwille WW, Ellsworth LA. Evaluation of driver drowsiness by trained raters. Accid Anal Prev 1994 ; 26 : 571 -81. OpenUrl CrossRef PubMed Web of Science
• ↵ Horne J. Why we sleep—the functions of sleep in humans and other mammals. Oxford University Press, 1988.

• Search Menu
• Advance Articles
• Editor's Choice
• Author Guidelines
• Submission Site
• Open Access
• About Health Education Research
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Dispatch Dates
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

Introduction, implications.

• < Previous

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

• Article contents
• Figures & tables
• Supplementary Data

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

• Permissions Icon Permissions

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.

Google Scholar

Google Preview

• advertising

Email alerts

Citing articles via.

• Recommend to your Library

Affiliations

• Online ISSN 1465-3648
• Print ISSN 0268-1153
• Copyright © 2024 Oxford University Press
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.