perceived vulnerability and
play

perceived vulnerability and perceived risk: Implications for health - PowerPoint PPT Presentation

Differences between perceived vulnerability and perceived risk: Implications for health theory and interventions Jennifer J. Harman, PhD Colorado State University 2005-2010 Assistant Professor, Applied Social Psychology Colorado State


  1. Differences between perceived vulnerability and perceived risk: Implications for health theory and interventions Jennifer J. Harman, PhD Colorado State University

  2. 2005-2010  Assistant Professor, Applied Social Psychology Colorado State University  Remained an affiliate of CHIP  Got married and had 2 children

  3. In J. G. Lavino & R. B. Neumann (Eds.), Harman, J. J., Wilson, K., & Keneski, E. (2010). Social and Psychology of Risk Perception, pp. 1-45. environmental contributors to perceived vulnerability and perception of risk for negative health consequences . Hauppauge, NY: Nova Science Publishers, Inc.

  4. Background  Risk perception for HIV infection in intimate relationships • Harman, Smith & Egan, (2007) • Harman, O’Grady & Wilson (2009)  Seemingly no differences in high risk versus lower risk populations • Harman, Wilson & Keneski (2010)

  5. Background (cont.) Information Behavioral Behavior Skills Motivation Adapted from Fisher & Fisher, 1992

  6. Background (cont.) Information Motivation Behavioral Behavior Skills Motivation Social Perceived Attitudes Norms Vulnerability

  7. Perceived vulnerability (PV) versus Perception of risk (PoR)  Terms have been used interchangeably in health promotion/risk prevention literature  Affect/feeling • “ I feel vulnerable to getting HIV”  Cognitive/beliefs • “I think I am at high risk for getting HIV”

  8. Now we know our ABCs…  Affective attitudes  Behavioral attitudes  Cognitive attitudes

  9. Two separate constructs  Perceived Vulnerability (PV)  Affective in nature  Perception of Risk (PoR)  Cognitive in nature

  10. Health Behavior Theories and PV  Health Belief model (Rosenstock, 1974)  Protection Motivation Theory (Rogers, 1983)  Extended Parallel Process Model (Witte, 1992)

  11. Why should I care?  Research support for PV as a predictor of attitudes, intentions and outcomes is inconsistent.  Simple health concerns: PV usually related • E.g., adherence to a medical regimen following a sports injury  Complex health concerns: less consistent • E.g., genetic risk information for cancer

  12. Development PV PoR  Classical conditioning &  Linkages between other automatic associative acquired information and processes attitude object  E.g., fear-smoking  E.g., beliefs about exercise- diabetes  Probability important

  13. PV and PoR and health outcomes Negative Relationship? Positive Relationship?  Protective behavior activation  Defensive behavior activation  E.g., PV + condom use  Optimistic biases (e.g., Lek & Bishop, 1995)  Denial

  14. So what is the problem?  Health behavior change interventions often introduce threats to increase PV or PoR  If a defensive response is activated, this “threat” may backfire

  15. The measurement bugaboo  PV and PoR measurements often combined or not reported  PV: affective measures/automatic associations  IAT, facial expression instruments, physiological reactions, cartoon face identification  PoR: cognitive measures of beliefs  Self-report

  16. The intervention challenge  Interventions manipulate specific variables to create change in psychological and/or health outcomes  Social and environmental contributors to PV and PoR proximal in nature Social Environmental

  17. Changing PV  Implicit attitude change (Gawronski & Bodenhausen, 2001) • Change how associations are made • E.g., associate a new feeling with the behavior • Social marketing • Change activation of pre-existing patterns of associations

  18. Changing PoR  Explicit attitude change strategies  Change in associative evaluation • Gradual change of associative patterns lead to change in PoR  Change in propositions relevant for judgments • E.g., provide risk information  Change in strategy to achieve consistency • E.g., “It can happen to you” campaigns

  19. Narrative Intervention Review  MedLine and Psychinfo lit search 936 Total Citations 90 “eligible” articles 59 studies remained after through review

  20. Strategies used  76 intervention elements  Vast majority targeted PoR • 73% used second route of PoR change • 15.4% used third strategy (e.g., cognitive dissonance)  Only 8 interventions targeted PV • Used 1 st strategy  Majority measured PoR, consistent with what was targeted

  21. A recent empirical example  HIV disproportionately affects Blacks and Hispanics in the U.S. (CDC, 2008)  Incarcerated populations 5-6 times more likely to be infected than general population (Lopez et al., 2001)  Social antecedents of PV/PoR?  PV: past HIV risk behavior, past HIV testing  PoR: believe HIV is a problem in community, know someone who is infected

  22. Research Qs  Are PV and PoR empirically distinct from one another?  Would heterosexual individuals impacted by incarceration have higher levels of PV and PoR than non-impacted individuals?  Is PV higher with reports of past HIV risk behavior and less frequent HIV testing?  Is PoR higher when people believe HIV is a serious problem in their community and/or whether they know someone infected?  Are there different relationships between the social antecedents of PV and PoR for each sample?  What is the relationship between PV and PoR and attitudes towards condoms, intentions, and condom use?

  23. Method  Participants  Two heterosexual couple samples • Impacted sample • Non-impacted sample  Instruments  PV: I don’t worry about HIV  PoR: It is really unlikely that I will get HIV  PV determinants: • How often are you high on non-injected drugs or alcohol when you have sex? • How many times have you been tested for HIV?  PoR determinants: • How many people do you know who have or had HIV/AIDS? • How serious is HIV in your community?  Condom Attitudes, Intentions and Use

  24. RQs 1 & 2  RQ1: Are PV and PoR distinct?  Correlations ranged from .40-.67 for all samples  RQ2: Do impacted individuals have higher PV and PoR? No!  Males: reported less PV • t (101)= -2.65, p = .009  Males and females less PoR • t (101) = -6.77 men • t (101) = -5.78 women • p s < .001

  25. RQ3 & 5  Does being high in drugs or alcohol during sex influence PV?  Did not influence PV, or PoR  Does previous HIV testing influence PV?  Impacted sample tested much more frequently than non- impacted sample  Did not influence PV, or PoR

  26. RQ4 & 5  Does the belief that HIV is serious problem in the community influence PoR?  Impacted sample saw it as a significantly more serious problem ( p s < .001)  Not related to PoR for any sample  Belief lowered PV for non-impacted males!  Does knowing someone who has/had HIV influence PoR?  Impacted sample knew more people  Not related to PoR for any sample  Knowing someone lowered PV for non-impacted males

  27. RQ6  Condom Attitudes  PV predicted more positive attitudes among impacted women and more negative attitudes among non-impacted women  Intentions to use condoms  PV predicted lower intentions to use among non- impacted women  Condom use  PoR for non-impacted women and impacted men associated with lower reports of condom use

  28. Discussion of empirical example  PV and PoR are moderately related, but distinct  PV and PoR lower among impacted men and women  Past risk behaviors and testing were not related to PV or PoR  Other antecedents operating?

  29. Conclusion  PV = affect/automatic associations  PoR= cognitive/explicit beliefs/propositions  Different strategies and social/environmental determinants should be used to change them  Measurement should reflect affective and cognitive aspects

  30. Conclusion  PV and PoR should operate similarly across different negative health outcomes  HIV, cancer, diabetes  Considerable differences may exist between individuals and groups of differing risks  Once differences are identified, explore reasons behind the differences, then develop tailored interventions  E.g., experimental testing of social/environmental determinants for change among specific groups

  31. Future directions  Create a valid measure of PV and PoR  In progress now  Retest interventions that have manipulated PV and/or PoR using new measure to determine if change occurs  Manipulate external/situational cues to determine effect on PV and PoR

  32. Thanks!  National Institute of Health #F31-MH069079, a Grant-in-Aid from the Society for the Psychological Study of Social Issues, and a research grant from division 38 of the American Psychological Association (Health Psychology)  Kristina Wilson & Liz Keneski  Peter McGraw, Hannah Gould, and Heather Patrick

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend