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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

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