Top

Gepubliceerd in:

09-06-2020

Incremental criterion validity of message perceptions and effects perceptions in the context of anti-smoking messages

Auteurs: Sabeeh A. Baig, Seth M. Noar, Nisha C. Gottfredson, Allison J. Lazard, Kurt M. Ribisl, Noel T. Brewer

Gepubliceerd in: Journal of Behavioral Medicine | Uitgave 1/2021

Abstract

To select promising health messages, formative research has often relied on perceived message effectiveness (PME) scales assessing either of two related constructs, message perceptions (persuasive potential) and effects perceptions (potential for behavioral impact). We sought to examine their incremental criterion validity within a comparative framework. Participants were 703 U.S. adult smokers (ages \(\ge\) 21) who received anti-smoking or comparable control (littering) messages on their cigarette packs for 3 weeks. Structural equation models examined both PME constructs as simultaneous correlates of outcomes from the UNC Tobacco Warnings Model. Message perceptions demonstrated incremental criterion validity with attention, an early behavioral antecedent (\(\beta\) = 0.82, p < .001). Effects perceptions demonstrated incremental criterion validity with later behavioral antecedents (range \(\beta\) = 0.74–0.87, all p < .01) and quitting behaviors (\(\beta\) = 0.36–0.66, all p < .001). Formative research on anti-smoking messages may benefit from focusing on effects perceptions to characterize potential for behavior change.

vorige artikel Anxiety, depression, and opioid misuse among adults with chronic pain: the role of emotion dysregulation

volgende artikel No effect of mindfulness-based cancer recovery on cardiovascular or cortisol reactivity in female cancer survivors

Alleen toegankelijk voor geautoriseerde gebruikers

Baig, S. A., et al. (2018). UNC Perceived Message Effectiveness: Validation of a brief scale. Annals of Behavioral Medicine. https://doi.org/10.1093/abm/kay080CrossRefPubMedCentral

Bollen, K. A., Harden, J. J., Ray, S., & Zavisca, J. (2014). BIC and alternative Bayesian information criteria in the selection of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 21(1), 1–19. https://doi.org/10.1080/10705511.2014.856691CrossRef

Bollen, K. A., Ray, S., Zavisca, J., & Harden, J. J. (2012). A comparison of Bayes factor approximation methods including two new methods. Sociological Methods & Research, 41(2), 294–324. https://doi.org/10.1177/0049124112452393CrossRef

Brennan, E., et al. (2013). Assessing the effectiveness of antismoking television advertisements: Do audience ratings of perceived effectiveness predict changes in quitting intentions and smoking behaviours? Tobacco Control, 23(5), 412–418. https://doi.org/10.1136/tobaccocontrol-2012-050949CrossRefPubMed

Brewer, N. T., et al. (2018). Cigarette pack messages about toxic chemicals: A randomised clinical trial. Tobacco Control. https://doi.org/10.1136/tobaccocontrol-2017-054112CrossRefPubMedPubMedCentral

CDC. (2008). Cigarette smoking among adults—United States, 2007. MMWR. Morbidity and Mortality Weekly Report, 57(45), 1221–1226.

Chalmers, R. P. (2015). Extended mixed-effects item response models with the MH-RM algorithm. Journal of Educational Measurement, 52(2), 200–222. https://doi.org/10.1111/jedm.12072CrossRef

Core Team, R. (2000). R language definition. Vienna, Austria: R Foundation for Statistical Computing.

Davis, S., et al. (2009). State-specific prevalence and trends in adult cigarette smoking-United States, 1998–2007. Morbidity and Mortality Weekly Report, 58(9), 221–226.

Davis, K. C., et al. (2011). Exploring African American women’s perceptions of a social marketing campaign to promote HIV testing. Social Marketing Quarterly, 17(3), 39–60. https://doi.org/10.1080/15245004.2011.595536CrossRef

Davis, K. C., et al. (2013). Perceived effectiveness of cessation advertisements: The importance of audience reactions and practical implications for media campaign planning. Health Communication, 28(5), 461–472. https://doi.org/10.1080/10410236.2012.696535CrossRefPubMed

Davis, K. C., et al. (2016). Perceived effectiveness of antismoking ads and association with quit attempts among smokers: Evidence from the TIPS From Former Smokers campaign. Health Communication, 32(8), 931–938. https://doi.org/10.1080/10410236.2016.1196413CrossRefPubMed

Dillard, J. P., & Ha, Y. (2016). Interpreting perceived effectiveness: Understanding and addressing the problem of mean validity. Journal of Health Communication, 21(9), 1016–1022. https://doi.org/10.1080/10810730.2016.1204379CrossRefPubMed

Dillard, J. P., Shen, L., & Vail, R. G. (2007a). Does perceived message effectiveness cause persuasion or vice versa? 17 consistent answers. Human Communication Research, 33(4), 467–488. https://doi.org/10.1111/j.1468-2958.2007.00308.xCrossRef

Dillard, J. P., Weber, K. M., & Vail, R. G. (2007b). The relationship between the perceived and actual effectiveness of persuasive messages: A meta-analysis with implications for formative campaign research. Journal of Communication, 57(4), 613–631. https://doi.org/10.1111/j.1460-2466.2007.00360.xCrossRef

Dillard, J. P., & Ye, S. (2008). The perceived effectiveness of persuasive messages: Questions of structure, referent, and bias. Journal of Health Communication, 13(2), 149–168. https://doi.org/10.1080/10810730701854060CrossRefPubMed

Donovan, R. J., Jalleh, G., & Carter, O. B. J. (2006). Tobacco industry smoking prevention advertisements’ impact on youth motivation for smoking in the future. Social Marketing Quarterly, 12(2), 3–13. https://doi.org/10.1080/15245000600721644CrossRef

Fathelrahman, A. I., Omar, M., Awang, R., et al. (2010). Impact of the new Malaysian cigarette pack warnings on smokers’ awareness of health risks and interest in quitting smoking. International Journal of Environmental Research and Public Health, 7(11), 4089–4099. https://doi.org/10.3390/ijerph7114089CrossRefPubMedPubMedCentral

Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press.

Hall, M. G., et al. (2018). Why smokers avoid cigarette pack risk messages: Two randomized clinical trials. Social Science & Medicine, 213, 165–172.CrossRef

Hyland, A., et al. (2016). Design and methods of the Population Assessment of Tobacco and Health (PATH) study. Tobacco Control, 26(4), 371–378. https://doi.org/10.1136/tobaccocontrol-2016-052934CrossRefPubMedPubMedCentral

Jarosz, A. F., & Wiley, J. (2014). What are the odds? A practical guide to computing and reporting Bayes factors. Journal of Problem Solving. https://doi.org/10.7771/1932-6246.1167CrossRef

Keller, P. A., & Block, L. G. (1996). Increasing the persuasiveness of fear appeals: The effect of arousal and elaboration. Journal of Consumer Research, 22(4), 448. https://doi.org/10.1086/209461CrossRef

Klein, W. M. P., Zajac, L. E., & Monin, M. M. (2009). Worry as a moderator of the association between risk perceptions and quitting intentions in young adult and adult smokers. Annals of Behavioral Medicine, 38(3), 256–261. https://doi.org/10.1007/s12160-009-9143-2CrossRefPubMed

Lambert, S. D., & Loiselle, C. G. (2007). Health information-seeking behavior. Qualitative Health Research, 17(8), 1006–1019. https://doi.org/10.1177/1049732307305199CrossRefPubMed

Lee, S., et al. (2011). Smoking cues, argument strength, and perceived effectiveness of antismoking PSAs. Nicotine & Tobacco Research, 13(4), 282–290. https://doi.org/10.1093/ntr/ntq255CrossRef

Li, L., et al. (2014). Smoking-related thoughts and microbehaviours, and their predictive power for quitting. Tobacco Control, 24(4), 354–361. https://doi.org/10.1136/tobaccocontrol-2013-051384CrossRefPubMedPubMedCentral

Millsap, R. E., & Yun-Tein, J. (2004). Assessing factorial invariance in ordered-categorical measures. Multivariate Behavioral Research, 39(3), 479–515. https://doi.org/10.1207/s15327906mbr3903_4CrossRef

Nelson, D., et al. (2004). The Health Information National Trends Survey (HINTS): Development, design, and dissemination. Journal of Health Communication, 9(5), 443–460. https://doi.org/10.1080/10810730490504233CrossRefPubMed

Niederdeppe, J., et al. (2011). Socioeconomic variation in recall and perceived effectiveness of campaign advertisements to promote smoking cessation. Social Science and Medicine, 72(5), 773–780. https://doi.org/10.1016/j.socscimed.2010.12.025CrossRefPubMed

Noar, S. M. (2006). A 10-year retrospective of research in health mass media campaigns: Where do we go from here? Journal of Health Communication, 11(1), 21–42. https://doi.org/10.1080/10810730500461059CrossRefPubMed

Noar, S. M., et al. (2016). Pictorial cigarette pack warnings: A meta-analysis of experimental studies. Tobacco Control, 25(3), 341–354. https://doi.org/10.1136/tobaccocontrol-2014-051978CrossRefPubMed

Noar, S. M., Barker, J., & Yzer, M. (2018a). Measurement and design heterogeneity in perceived message effectiveness studies: A call for research. Journal of Communication, 68(5), 990–993. https://doi.org/10.1093/joc/jqy047CrossRef

Noar, S. M., et al. (2018b). Perceived message effectiveness measures in tobacco education campaigns: A systematic review. Communication Methods and Measures, 12(4), 295–313. https://doi.org/10.1080/19312458.2018.1483017CrossRefPubMedPubMedCentral

Noar, S. M., et al. (2018c). Identifying principles for effective messages about chemicals in cigarette smoke. Preventive Medicine, 106, 31–37. https://doi.org/10.1016/j.ypmed.2017.09.005CrossRefPubMed

Nonnemaker, J., et al. (2010). Experimental study of graphic cigarette warning labels. Final Results Report. RTI Project, 7

O’Keefe, D. J. (2018). Message pretesting using assessments of expected or perceived persuasiveness: Evidence about diagnosticity of relative actual persuasiveness. Journal of Communication, 68(1), 120–142. https://doi.org/10.1093/joc/jqx009CrossRef

Partos, T. R., et al. (2014). The predictive utility of micro indicators of concern about smoking: Findings from the International Tobacco Control Four Country Study. Addictive Behaviors, 39(8), 1235–1242. https://doi.org/10.1016/j.addbeh.2014.04.001CrossRefPubMedPubMedCentral

Revelle, W. (2011). An overview of the psych package. Department of Psychology Northwestern University. Retrieved 3 March, 2012.

Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 1, 2. https://doi.org/10.18637/jss.v048.i02CrossRef

Vispoel, W. P., Morris, C. A., & Kilinc, M. (2017). Practical applications of generalizability theory for designing, evaluating, and improving psychological assessments. Journal of Personality Assessment. https://doi.org/10.1080/00223891.2017.1296455CrossRefPubMed

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063CrossRefPubMed

Wickham, H. (2016). Ggplot2: Elegant graphics for data analysis. Berlin: Springer. https://doi.org/10.1007/978-3-319-24277-4CrossRef

Yzer, M., LoRusso, S., & Nagler, R. H. (2014). On the conceptual ambiguity surrounding perceived message effectiveness. Health Communication, 30(2), 125–134. https://doi.org/10.1080/10410236.2014.974131CrossRef

Titel: Incremental criterion validity of message perceptions and effects perceptions in the context of anti-smoking messages
Auteurs: Sabeeh A. Baig
Seth M. Noar
Nisha C. Gottfredson
Allison J. Lazard
Kurt M. Ribisl
Noel T. Brewer
Publicatiedatum: 09-06-2020
Uitgeverij: Springer US
Gepubliceerd in: Journal of Behavioral Medicine / Uitgave 1/2021
Print ISSN: 0160-7715
Elektronisch ISSN: 1573-3521
DOI: https://doi.org/10.1007/s10865-020-00163-0

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Log in om toegang te krijgen

Andere artikelen Uitgave 1/2021

Temporal changes in psychobehavioural responses during the early phase of the COVID-19 pandemic in Malaysia

Pain resilience, pain catastrophizing, and executive functioning: performance on a short-term memory task during simultaneous ischemic pain

Social Constraints and PTSD among Chinese American breast cancer survivors: not all kinds of social support provide relief

Cognitions and behaviors related to risk for alcohol-exposed pregnancies among young adult women

Correction to: Transitions in coping profiles after breast cancer diagnosis: implications for depressive and physical symptoms

Perceived discrimination predicts elevated biological markers of inflammation among sexual minority adults