A Test of Major Assumptions About Behavior Change: A Comprehensive Look at the Effects of Passive and Active HIV-Prevention Interventions Since the Beginning of the Epidemic.

Abstract

This meta-analysis tested the major theoretical assumptions about behavior change by examining the outcomes and mediating mechanisms of different preventive strategies in a sample of 354 HIVprevention interventions and 99 control groups, spanning the past 17 years. There were 2 main conclusions from this extensive review. First, the most effective interventions were those that contained attitudinal arguments, educational information, behavioral skills arguments, and behavioral skills training, whereas the least effective ones were those that attempted to induce fear of HIV. Second, the impact of the interventions and the different strategies behind them was contingent on the gender, age, ethnicity, risk group, and past condom use of the target audience in ways that illuminate the direction of future preventive efforts. Keywords behavior change; active intervention; HIV; health; communicationThe development of effective health behavior interventions and adequate understanding of the processes that underlie change to risky behavior continues to top the agenda for reducing disease and death among at-risk populations. For example, infection with HIV has been diagnosed in almost 1 million people in the United States (Centers for Disease Control [CDC], 2003) as well as an estimated 40 million worldwide (UNAIDS/ WHO Working Group, 2002). In some countries, the epidemic continues to escalate, and even in nations that have successfully Copyright 2005 by the American Psychological AssociationCorrespondence concerning this article should be addressed to Dolores Albarracín, Department of Psychology, University of Florida, Gainesville, FL 32611. E-mail: E-mail: dalbarra@ufl.edu. NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript curbed the spread of the disease, certain groups still show increases in infection rates (see, e.g., CDC, 2003). Given these distressing figures, it is no surprise that research on HIV prevention has become increasingly important and progressively more sophisticated. Indeed, HIV prevention presently constitutes one of the most significant paradigms for the discovery of health behavior change techniques and for the understanding of the theoretical processes that underlie such change.In fact, the HIV epidemic of the 1980s stimulated the uniting of funds and expertise from various disciplines in the development of a shared behavior-change paradigm. As a key example, in 1992, a group of behavioral researchers joined forces-upon request from the National Institutes of Health-to develop a paradigm for behavior change that would guide research and practice in the prevention of HIV (see Fishbein et al., 1992). Various models were examined, and the key assumptions were condensed into a limited number of premises that illuminated preventive efforts.Although the various models had independently received broad support, this support was derived almost entirely from behavior prediction studies. However, the formulation of these general assumptions contributed to...

The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions

“…Hierarchical Cluster Analysis (HCA), the optimal number of groupings (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) were examined for suitability using measures of Internal Validity (Dunn's Index) and Stability (Figure of Merit, FOM) [34]. Bootstrap methods were used in conjunction with the HCA, whereby data were resampled 10,000 times, to identify which groupings were strongly supported by the data.…”

“…For example, behavioral medicine researchers and practitioners have been found to report low confidence in their ability to replicate highly effective behavioral interventions for diabetes prevention [6]. The absence of standardized definitions and labels for intervention components means that systematic reviewers develop their own systems for classifying behavioral interventions and synthesizing study findings [7,8,9,10]. This proliferation of systems is likely to lead to duplication of effort and undermines the potential to accumulate evidence across reviews.…”

“…Identifying the presence of BCTs in intervention descriptions included in systematic reviews and national datasets of outcomes has allowed the identification of BCTs associated with effective interventions. Effective BCTs have been identified for interventions to increase physical activity and healthy eating [14] and to support smoking cessation [15,16], safe drinking [17], prevention of sexually transmitted infections [7,18] and changing professional behavior [19. Abraham and Michie [11] developed the first cross-behavior BCT taxonomy, building on previous intervention content analyses [7,8]. These authors demonstrated reliability in identifying 22 BCTs and 4 BCT packages across 221 intervention descriptions in papers and manuals.…”

“…theory [7,11], theoretical mechanism [25,26]) judged to be the most appropriate by the authors. In addition, they have mainly been developed for particular behavioral domains (e.g.…”

The Causal Effects of Relational Security and Insecurity on Condom Use Attitudes and Acquisition Behavior

“…Meta-analyses of condom behavior studies revealed a central determining role for attitudes; if people hold a negative attitude about condoms they are unlikely to use them (Albaracín et al, 2005;Albaracín, Johnson, Fishbein, & Muellerleile, 2001;Sheeran, Abraham, & Orbell, 1999). A major limitation of the literature on condom-related attitudes, however, is its disregard of relational processes that influence condom use (Ciesla, Roberts, & Hewitt, 2004;Feeney & Raphael, 1992;WHO, 2012).…”