Do ultraviolet photos increase sun safe behavior expectations via fear? A randomized controlled trial in a sample of U.S. adults

Abstract

Ultraviolet (UV) photos reveal the world in a different light spectrum, including damage that is caused by UV light. In the context of skin cancer control, UV photos have the potential to communicate fear because they reveal underlying skin damage. U.S. adults (N = 2219) were assigned to a 5 (visual: UV skin damage, sun exposure, sunburn, photoaging, and mole removal) × 3 (replication: three examples of each visual condition) × 4 (efficacy: no efficacy, text only, visual, visual + text) randomized controlled trial. Compared to all other visual conditions combined, UV skin damage visuals generated greater fear which triggered increased sun safe behavior expectations. Compared with other visual conditions separately, only mole removal visuals produced equivalent fear as UV skin damage visuals. Visual efficacy conditions appeared to nullify rather than magnify the indirect path through fear. The results suggest one way UV images impact sun safe behavioral expectations is via fear and that researchers should continue to examine the position of fear in fear appeal theories.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

References

  1. Armitage, C. J., Norman, P., Alganem, S., & Conner, M. (2015). Expectations are more predictive of behavior than behavioral intentions: Evidence from two prospective studies. Annals of Behavioral Medicine, 49, 239–246.

    Article  PubMed  Google Scholar 

  2. Aspinwall, L. G., Taber, J. M., Kohlmann, W., Leaf, S. L., & Leachman, S. A. (2014). Unaffected family members report improvements in daily routine sun protection 2 years following melanoma genetic testing. Genetics in Medicine, 16, 846–853.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Birmingham, W. C., Hung, M., Boonyasiriwat, W., Kohlmann, W., Walters, S. T., Burt, R. W., et al. (2015). Effectiveness of the extended parallel process model in promoting colorectal cancer screening. Psycho-Oncology, 24, 1265–1278. https://doi.org/10.1002/pon.3899

    Article  PubMed  Google Scholar 

  4. Carcioppolo, N., Jensen, J. D., Wilson, S. E., Collins, W. B., Carrion, M., & Linnemeier, G. (2013). Examining HPV threat-to-efficacy ratios in the extended parallel process model. Health Communication, 28, 20–28.

    Article  PubMed  Google Scholar 

  5. Carrera, P., Muñoz, D., & Caballero, A. (2010). Mixed emotional appeals in emotional and danger control processes. Health Communication, 25, 726–736. https://doi.org/10.1080/10410236.2010.521914

    Article  PubMed  Google Scholar 

  6. Demierre, M. F., Maguire-Eisen, M., O’Connell, N., Sorenson, K., Berger, J., Williams, C., et al. (2009). A sun protection community intervention in Quincy middle schools: Insights from the use of ultraviolet photography and its impact on sunburn. Journal of the Dermatology Nurses’ Association, 1, 111–118.

    Article  Google Scholar 

  7. Dillard, J. P., Li, R., & Huang, Y. (2016a). Threat appeals: The fear–persuasion relationship is linear and curvilinear. Health Communication. https://doi.org/10.1080/10410236.2016.1220345

    Article  PubMed  PubMed Central  Google Scholar 

  8. Dillard, J. P., Li, R., Meczkowski, E., Yang, C., & Shen, L. (2016b). Fear responses to threat appeals: Functional form, methodological considerations, and correspondence between static and dynamic data. Communication Research. https://doi.org/10.1177/0093650216631097

    Article  Google Scholar 

  9. Emmons, K. M., Geller, A. C., Puleo, E., Savadatti, S. S., Hu, S. W., Gorham, S., et al. (2011). Skin cancer education and early detection at the beach: A randomized trial of dermatologist examination and biometric feedback. Journal of the American Academy of Dermatology, 64(2), 282–289. https://doi.org/10.1016/j.jaad.2010.01.040

    Article  PubMed  Google Scholar 

  10. Erdfelder, E., Faul, F., & Buchner, A. (1996). GPOWER: A general power analysis program. Behavior Research Methods, Instruments, & Computers, 28, 1–11. https://doi.org/10.3758/BF03203630

    Article  Google Scholar 

  11. Gamble, R. G., Asdigian, N. L., Aalborg, J., Gonzalez, V., Box, N. F., Huff, L. S., et al. (2012). Sun damage in ultraviolet photographs correlates with phenotypic melanoma risk factors in 12-year-old children. Journal of the American Academy of Dermatology, 67, 587–597. https://doi.org/10.1016/j.jaad.2011.11.922

    Article  PubMed  PubMed Central  Google Scholar 

  12. Gibbons, F. X., Gerrard, M., Lane, D. J., Mahler, H. I. M., & Kulik, J. A. (2005). Using UV photography to reduce use of tanning booths: A test of cognitive mediation. Health Psychology, 24, 358–363. https://doi.org/10.1037/0278-6133.24.4.358

    Article  PubMed  Google Scholar 

  13. Glanz, K., Schoenfeld, E., Weinstock, M. A., Layi, G., Kidd, J., & Shigaki, D. M. (2003). Development and reliability of a brief skin cancer risk assessment tool. Cancer Detection and Prevention, 27, 311–315. https://doi.org/10.1016/S0361-090X(03)00094-1

    Article  PubMed  Google Scholar 

  14. Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.

    Google Scholar 

  15. Heckman, C. J., Handorf, E., Darlow, S. D., Yaroch, A. L., & Raivitch, S. (2017). Refinement of measures to assess psychosocial constructs associated with skin cancer risk and protective behaviors of young adults. Journal of Behavioral Medicine, 40, 574–582. https://doi.org/10.1007/s10865-017-9825-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hornung, R. L., & Strecher, V. J. (2012). Ultraviolet photography as a skin cancer risk assessment and intervention tool. Journal of the American Academy of Dermatology, 67(4), 785–786. https://doi.org/10.1016/j.jaad.2012.02.016

    Article  PubMed  Google Scholar 

  17. Jain, P., Hoffman, E., Beam, M., & Xu, S. S. (2017). Effect of message format and content on attitude accessibility regarding sexually transmitted infections. Health Communication, 32, 1376–1384.

    Article  PubMed  Google Scholar 

  18. King, A. J. (2015a). Visual messaging and risk communication. In H. Cho, T. Reimer, & K. A. McComas (Eds.), Sage handbook of risk communication (pp. 193–205). Thousand Oaks, CA: Sage.

    Google Scholar 

  19. King, A. J. (2015b). A content analysis of visual cancer information: Prevalence and use of photographs and illustrations in printed health materials. Health Communication, 30, 722–731.

    Article  PubMed  Google Scholar 

  20. Kline, R. B. (2015). The mediation myth. Basic and Applied Social Psychology, 37, 202–213.

    Article  Google Scholar 

  21. Krieger, J. L., & Sarge, M. A. (2013). A serial mediation model of message framing on intentions to receive the human papillomavirus (HPV) vaccine: Revisiting the role of threat and efficacy perceptions. Health Communication, 28, 5–19.

    Article  PubMed  Google Scholar 

  22. Mahler, H. I. (2014). The role of emotions in UV protection intentions and behaviors. Psychology, Health & Medicine, 19, 344–354. https://doi.org/10.1080/13548506.2013.802359

    Article  Google Scholar 

  23. Mahler, H. I. (2015). Interventions to promote sun protection behaviors: What do we know about the efficacy of health- and appearance-based messages and the role of cognitions and emotions? Social and Personality Psychology Compass, 9, 238–251. https://doi.org/10.1111/spc3.12173

    Article  Google Scholar 

  24. Mahler, H. I. (2018). The relative role of cognitive and emotional reactions in mediating the effects of a social comparison sun protection intervention. Psychology & Health, 33, 235–257. https://doi.org/10.1080/08870446.2017.1310860

    Article  Google Scholar 

  25. Mahler, H. I., Kulik, J. A., Gerrard, M., & Gibbons, F. X. (2007). Long-term effects of appearance-based interventions on sun protection behaviors. Health Psychology, 26, 350–360. https://doi.org/10.1037/0278-6133.26.3.350

    Article  PubMed  Google Scholar 

  26. Mahler, H. I., Kulik, J. A., Gerrard, M., & Gibbons, F. X. (2013). Effects of photoaging information and UV photo on sun protection intentions and behaviours: A cross-regional comparison. Psychology & Health, 28, 1009–1031. https://doi.org/10.1080/08870446.2013.777966

    Article  Google Scholar 

  27. Mahler, H. I., Kulik, J. A., Gibbons, F. X., Gerrard, M., & Harrell, J. (2003). Effects of appearance-based intervention on sun protection intentions and self-reported behaviors. Health Psychology, 22, 199–209. https://doi.org/10.1037/0278-6133.22.2.199

    Article  PubMed  Google Scholar 

  28. Maloney, E. K., Lapinski, M. K., & Witte, K. (2011). Fear appeals and persuasion: A review and update of the extended parallel process model. Social and Personality Psychology Compass, 5, 206–219. https://doi.org/10.1111/j.1751-9004.2011.00341.x

    Article  Google Scholar 

  29. Maxweel, S. E., & Cole, D. A. (2007). Bias is cross-sectional analyses of longitudinal mediation. Psychological Methods, 12, 23–44.

    Article  Google Scholar 

  30. Mays, D., & Zhao, X. (2016). The influence of framed messages and self-affirmation on indoor tanning behavioral intentions among 18 to 30 year old women. Health Psychology, 35, 123–130. https://doi.org/10.1037/hea0000253

    Article  PubMed  Google Scholar 

  31. McCambridge, J., Kypri, K., & Elbourne, D. (2014). In randomization we trust? There are overlooked problems in experimenting with people in behavioral intervention trials. Journal of Clinical Epidemiology, 67, 247–253. https://doi.org/10.1016/j.jclinepi.2013.09.004

    Article  PubMed  PubMed Central  Google Scholar 

  32. McWhirter, J. E., & Hoffman-Goetz, L. (2015). Systematic review of population-based studies on the impact of images on UV attitudes and behaviors. Health Promotion International, 30, 397–410. https://doi.org/10.1093/heapro/dat031

    Article  PubMed  Google Scholar 

  33. Nabi, R. L., & Myrick, J. G. (2018). Uplifting fear appeals: Considering the role of hope in fear-based persuasive messages. Health Communication. https://doi.org/10.1080/10410236.2017.1422847

    Article  PubMed  Google Scholar 

  34. O’Keefe, D. J. (2003). Message properties, mediating states, and manipulation checks: Claims, evidence, and data analysis in experimental persuasive message effects research. Communication Theory, 13, 251–274. https://doi.org/10.1111/j.1468-2885.2003.tb00292.x

    Article  Google Scholar 

  35. Peters, G. Y., Ruiter, R. A. C., & Kok, G. (2013). Threatening communication: A critical re-analysis and a revised meta-analytic test of fear appeal theory. Health Psychology Review, 7, S8–S31. https://doi.org/10.1080/17437199.2012.703527

    Article  PubMed  PubMed Central  Google Scholar 

  36. Popova, L. (2012). The extended parallel process model: Illuminating the gaps in research. Health Education & Behavior, 39, 455–473. https://doi.org/10.1177/1090198111418108

    Article  Google Scholar 

  37. Ruiter, R. A. C., Kessels, L. T. E., Peters, G.-J. Y., & Kok, G. (2014). Sixty years of fear appeal research: Current state of the evidence. International Journal of Psychology, 49, 63–70. https://doi.org/10.1002/ijop.12042

    Article  PubMed  Google Scholar 

  38. Shen, L., & Coles, V. B. (2015). Fear and psychological reactance. Zeitschrift Für Psychologie, 223, 225–235. https://doi.org/10.1027/2151-2604/a000224

    Article  Google Scholar 

  39. Shi, J., & Smith, S. W. (2016). The effects of fear appeal message repetition on perceived threat, perceived efficacy, and behavioral intention in the extended parallel process model. Health Communication, 31, 275–286.

    Article  PubMed  Google Scholar 

  40. Shipp, A. J., & Aeon, B. (2018). Temporal focus: Thinking about the past, present, and future. Current Opinion in Psychology, 26, 37–43. https://doi.org/10.1016/j.copsyc.2018.04.005

    Article  PubMed  Google Scholar 

  41. Siegel, R. L., Miller, K. D., & Jemal, A. (2018). Cancer statistics, 2018. CA: A Cancer Journal for Clinicians, 68, 7–30. https://doi.org/10.3322/caac.21442

    Article  Google Scholar 

  42. So, J. (2013). A further extension of the extended parallel process model (E-EPPM): Implications of cognitive appraisal theory of emotion and dispositional coping style. Health Communication, 28, 72–83.

    Article  PubMed  Google Scholar 

  43. Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46, 137–150. https://doi.org/10.1037/h0062958

    Article  CAS  PubMed  Google Scholar 

  44. Stock, M. L., Gerrard, M., Gibbons, F. X., Dykstra, J. L., Weng, C.-Y., Mahler, H. I. M., et al. (2010). Sun protection intervention for highway workers: Long-term efficacy of UV photography and skin cancer information on men’s protective cognitions and behavior: Erratum. Annals of Behavioral Medicine, 39, 100. https://doi.org/10.1007/s12160-010-9179-3

    Article  PubMed Central  Google Scholar 

  45. Tannenbaum, M. B., Helpler, J., Zimmerman, R. S., Saul, L., Jacobs, S., Wilson, K., et al. (2015). Appealing to fear: A meta-analysis of fear appeal effectiveness and theories. Psychological Bulletin, 141, 1178–1204.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Tate, C. U. (2015). On the overuse and misuse of mediation analysis: It may be a matter of timing. Basic and Applied Social Psychology, 37, 235–246.

    Article  Google Scholar 

  47. Taylor, M. F., Westbrook, D., & Chang, P. (2016). Using UV photoaged photography to better understand Western Australian teenagers’ attitudes towards adopting sun-protective behaviors. International Journal of Adolescent Medicine and Health, 28, 45–53. https://doi.org/10.1515/ijamh-2014-0071

    Article  PubMed  Google Scholar 

  48. Vraga, E., Bode, L., & Troller-Renfree, S. (2016). Beyond self-reports: Using eye tracking to measure topic and style differences in attention to social media content. Communication Methods and Measures, 10, 149–164. https://doi.org/10.1080/19312458.2016.1150443

    Article  Google Scholar 

  49. Walsh, L. A., & Stock, M. L. (2012). UV photography, masculinity, and college men’s sun protection cognitions. Journal of Behavioral Medicine, 35, 431–442. https://doi.org/10.1007/s10865-011-9372-2

    Article  PubMed  Google Scholar 

  50. Walsh, L. A., Stock, M. L., Peterson, L. M., & Gerrard, M. (2014). Women’s sun protection cognitions in response to UV photography: The role of age, cognition, and affect. Journal of Behavioral Medicine, 37, 553–563. https://doi.org/10.1007/s10865-013-9512-y

    Article  PubMed  Google Scholar 

  51. Williams, A. L., Grogan, S., Clark-Carter, D., & Buckley, E. (2013). Appearance-based interventions to reduce ultraviolet exposure and/or increase sun protection intentions and behaviours: A systematic review and meta-analyses. British Journal of Health Psychology, 18, 182–217. https://doi.org/10.1111/j.2044-8287.2012.02089.x

    Article  PubMed  Google Scholar 

  52. Witte, K. (1992a). Putting the fear back into fear appeals: The extended parallel process model. Communication Monographs, 59, 329–349. https://doi.org/10.1080/03637759209376276

    Article  Google Scholar 

  53. Witte, K. (1992b). The role of threat and efficacy in AIDS prevention. International Quarterly of Community Health Education, 12, 225–249. https://doi.org/10.2190/U43P-9QLX-HJ5P-U2J5

    Article  Google Scholar 

  54. Witte, K. (1994). Fear control and danger control: A test of the extended parallel process model (EPPM). Communication Monographs, 61, 113–134. https://doi.org/10.1080/03637759409376328

    Article  Google Scholar 

  55. Witte, K. (2000). EPPM: Examples of items. Retrieved November 29, 2018 from https://msu.edu/~wittek/scale.htm

  56. Witte, K. (2013). Introduction: Pathways. Health Communication, 28, 3–4. https://doi.org/10.1080/10410236.2013.743783

    Article  PubMed  Google Scholar 

  57. Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education & Behavior, 27, 591–615. https://doi.org/10.1177/109019810002700506

    Article  CAS  Google Scholar 

  58. Witte, K., Cameron, K. A., Mckeon, J. K., & Berkowitz, J. M. (1996). Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of Health Communication, 1, 317–342. https://doi.org/10.1080/108107396127988

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This research was funded by a New Innovator grant (#DP2EB022360) from the National Institutes of Health (NIH) (PI: JDJ; Co-I: KKJ) and in part by the National Cancer Institute of the National Institutes of Health (K07CA196985 to YPW). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Manusheela Pokharel.

Ethics declarations

Conflict of interest

Manusheela Pokharel, Katheryn R. Christy, Jakob D. Jensen, Elizabeth A. Giorgi, Kevin K. John, Yelena P. Wu have no conflicts of interest to declare.

Human and animal rights and Informed consent

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1: UV skin damage visuals

figurea
figureb
figurec

Appendix 2: Sun exposure visuals

figured
figuree
figuref

Appendix 3: Sunburn visuals

figureg
figureh
figurei

Appendix 4: Photo ageing visuals

figurej
figurek
figurel

Appendix 5: Mole removal visuals

figurem
figuren
figureo

Appendix 6: Text efficacy condition stimuli

There are a number of things that you can do to reduce your risk of skin cancer, including:

  • Wearing sunscreen.

  • Staying out of the sun between 10 AM and 4 PM.

  • Wearing protective clothing (e.g., long sleeves, long pants, a broad brimmed hat, sunglasses).

  • Staying in the shade.

Next we’re going to ask you a bit about the image you just saw.

Appendix 7: Visual efficacy condition stimuli

figurep

Appendix 8: Estimated marginal means and 95% confidence intervals: visual conditions × efficacy conditions

Visual condition Efficacy condition Dependent variables
Susceptibility Severity Self efficacy Response efficacy Fear Behavior expectation
Mean (SE) 95% CI Mean (SE) 95% CI Mean (SE) 95% CI Mean (SE) 95% CI Mean (SE) 95% CI Mean (SE) 95% CI
Sun exposure No efficacy 4.24 (.15) (3.95, 4.54) 5.29 (.13) (5.03, 5.55) 4.92 (.13) (4.67, 5.17) 5.26 (.13) (5.00, 5.52) 2.24 (.16) (1.92, 2.56) 5.15 (.14) (4.88, 5.42)
Text 4.58 (.15) (4.28, 4.87) 5.54 (.13) (5.28, 5.79) 5.35 (.13) (5.10, 5.59) 5.67 (.13) (5.41, 5.92) 2.26 (.16) (1.94, 2.59) 5.32 (.14) (5.05, 5.59)
Visual 4.72 (.15) (4.42, 5.01) 5.79 (.13) (5.53, 6.04) 5.48 (.13) (5.24, 5.73) 5.68 (.13) (5.43, 5.94) 2.47 (.16) (2.15, 2.80) 5.53 (.14) (5.26, 5.80)
Visual + text 4.32 (.15) (4.03, 4.62) 5.40 (.13) (5.15, 5.66) 5.07 (.13) (4.82, 5.31) 5.31 (.13) (5.05, 5.57) 2.58 (.16) (2.26, 2.90) 5.08 (.14) (4.81, 5.35)
Sunburn No efficacy 4.67 (.15) (4.37, 4.97) 5.39 (.13) (5.13, 5.64) 4.80 (.13) (4.55, 5.04) 5.25 (.13) (5.00, 5.51) 2.44 (.16) (2.12, 2.76) 5.00 (.14) (4.73, 5.27)
Text 4.70 (.15) (4.40, 4.99) 5.65 (.13) (5.39, 5.91) 5.00 (.13) (4.75, 5.25) 5.53 (.13) (5.27, 5.79) 2.67 (.16) (2.34, 2.99) 5.07 (.14) (4.80, 5.34)
Visual 4.63 (.15) (4.33, 4.93) 5.35 (.13) (5.09, 5.60) 5.08 (.13) (4.83, 5.32) 5.28 (.13) (5.02, 5.54) 2.73 (.16) (2.40, 3.05) 5.20 (.14) (4.93, 5.47)
Visual + text 4.75 (.15) (4.46, 5.05) 5.47 (.13) (5.22, 5.73) 5.01 (.13) (4.76, 5.26) 5.43 (.13) (5.17, 5.69) 2.59 (.16) (2.27, 2.91) 5.22 (.14) (4.95, 5.49)
Aging No efficacy 4.44 (.15) (4.14, 4.73) 5.57 (.13) (5.31, 5.83) 5.21 (.13) (4.96, 5.46) 5.40 (.13) (5.14, 5.66) 2.38 (.16) (2.06, 2.71) 5.17 (.14) (4.90, 5.44)
Text 4.74 (.15) (4.45, 5.04) 5.39 (.13) (5.14, 5.65) 5.06 (.13) (4.81, 5.31) 5.35 (.13) (5.09, 5.61) 2.87 (.16) (2.55, 3.19) 5.04 (.14) (4.77, 5.30)
Visual 4.72 (.15) (4.43, 5.02) 5.69 (.13) (5.43, 5.94) 5.48 (.13) (5.23, 5.73) 5.62 (.13) (5.36, 5.88) 2.85 (.16) (2.53, 3.17) 5.41 (.14) (5.14, 5.67)
Visual + text 4.57 (.15) (4.27, 4.86) 5.40 (.13) (5.14, 5.65) 5.17 (.13) (4.92, 5.41) 5.50 (.13) (5.24, 5.76) 2.93 (.16) (2.60, 3.25) 5.31 (.14) (5.04, 5.58)
Mole removal No efficacy 4.93 (.15) (4.63, 5.22) 5.61 (.13) (5.35, 5.86) 5.28 (.13) (5.03, 5.53) 5.60 (.13) (5.34, 5.86) 3.28 (.16) (2.96, 3.60) 5.22 (.14) (4.95, 5.49)
Text 4.48 (.15) (4.18, 4.78) 5.45 (.13) (5.20, 5.71) 5.15 (.13) (4.90, 5.40) 5.54 (.13) (5.28, 5.80) 3.05 (.16) (2.73, 3.37) 5.17 (.14) (4.90, 5.44)
Visual 4.56 (.15) (4.26, 4.85) 5.61 (.13) (5.35, 5.87) 5.19 (.13) (4.94, 5.44) 5.61 (.13) (5.35, 5.87) 2.91 (.16) (2.59, 3.23) 5.38 (.14) (5.11, 5.65)
Visual + text 4.59 (.15) (4.29, 4.88) 5.57 (.13) (5.31, 5.82) 5.29 (.13) (5.04, 5.54) 5.55 (.13) (5.29, 5.81) 2.88 (.16) (2.55, 3.20) 5.45 (.14) (5.18, 5.72)
UV No efficacy 4.80 (.15) (4.51, 5.10) 5.69 (.13) (5.43, 5.94) 5.07 (.13) (4.82, 5.32) 5.53 (.13) (5.27, 5.79) 3.33 (.16) (3.00, 3.65) 5.15 (.14) (4.88, 5.41)
Text 4.50 (.15) (4.20, 4.79) 5.52 (.13) (5.27, 5.78) 5.06 (.13) (4.81, 5.31) 5.39 (.13) (5.13, 5.65) 3.16 (.16) (2.84, 3.48) 5.27 (.14) (5.00, 5.54)
Visual 4.56 (.15) (4.27, 4.86) 5.61 (.13) (5.36, 5.87) 5.29 (.13) (5.04, 5.54) 5.57 (.13) (5.31, 5.82) 2.86 (.16) (2.53, 3.18) 5.25 (.14) (4.98, 5.52)
Visual + text 4.63 (.15) (4.33, 4.93) 5.61 (.13) (5.12, 5.64) 5.05 (.13) (4.80, 5.30) 5.39 (.13) (5.13, 5.64) 2.94 (.16) (2.62, 3.26) 5.20 (.14) (4.93, 5.47)
  1. Means and standard errors (in parentheses)

Appendix 9: Estimated marginal means and 95% confidence intervals for fear: UVvsAll × efficacy conditions

Visual condition Efficacy condition Mean (SE) 95% CI
Non-UV conditions Control 2.59 (.08) (2.42, 2.75)
Text 2.71 (.08) (2.55, 2.87)
Visual 2.74 (.08) (2.58, 2.90)
Visual + text 2.74 (.08) (2.58, 2.90)
UV condition Control 3.33 (.16)a (3.00, 3.65)
Text 3.16 (.16)ab (2.84, 3.49)
Visual 2.86 (.16)b (2.53, 3.18)
Visual + text 2.94 (.16)b (2.62, 3.26)
  1. Means and standard errors (in parentheses)
  2. Means with different superscripts are significantly different, p < .10. In Non-UV conditions, the means are not significantly different. In UV conditions, fear in the control efficacy condition is significantly greater than in the visual efficacy condition, p = .04 and approaching significance in the Visual +Text efficacy condition, p = .098

Appendix 10: Simple mediation—tests of indirect effects of EPPM variables (MolevsAll)

N = 2220 Models without mediator Models with mediator
  B B Bootstrap results for indirect effects (95% CI) Bootstrap results for indirect effect sizes (95% CI)
R 2 c R 2 c′ a b ab Lower Upper k 2 Lower Upper
Susceptibility .00 .10 .12*** .08 .04 .31*** .01 − .0400 .0654 .00 .0000 .0116
Severity .00 .10 .33*** .07 .05 .60*** .03 − .0570 .1144 .01 .0003 .0381
Self-efficacy .00 .10 .52*** .02 .10 .78*** .08 − .0273 .1876 .03 .0018 .0711
Response Efficacy .00 .10 .38*** .02 .13† .64*** .08 − .0144 .1683 .03 .0025 .0567
Fear .00 .10 .05*** .04 .32*** .18*** .06* .0233 .0963 .02 .0068 .0273
  1. Process Model 4 with 1000 bootstraps where each mediator was tested one at a time. Fear is the only significant mediator as the boot confidence interval does not overlap zero. The predictor is the MolevsAll contrast, outcome is behavior expectation
  2. B unstandardized regression weights, c total effect of predictor on outcome without the mediator in the model, c′ direct effect of predictor on outcome while controlling for the mediator, a the path between the predictor and the mediator, b the path between the mediator and the outcome, ab indirect effect of predictor on outcome thorough the mediator, R2 amount of variance explained by the model, CI confidence intervals, k2 effect size
  3. p < .10; * p <  .05; ***p < .001

Appendix 11: Simple mediation models of the EPPM

figureq

Only fear significantly mediated the relation between X (MolevsAll) and Y (Behavior Expectation): effect = .06, Boot SE = .02, 95% Boot CI: .0233, .0963, Effect size (k2) = .02

p < .10; ***p  <  .001.

Appendix 12: PROCESS model 4 simple mediation analysis output with visual conditions as predictor, fear as mediator, and behavior expectations as outcome

figurerfigurerfigurer

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pokharel, M., Christy, K.R., Jensen, J.D. et al. Do ultraviolet photos increase sun safe behavior expectations via fear? A randomized controlled trial in a sample of U.S. adults. J Behav Med 42, 401–422 (2019). https://doi.org/10.1007/s10865-018-9997-5

Download citation

Keywords

  • Skin cancer
  • Sun-safe behaviors
  • Fear appeal
  • UV photo
  • Visuals
  • EPPM