Using Intervention Theory to Model Factors Influencing Behavior Change

Project RESPECT was a multisite randomized trial comparing three clinic-based interventions’ ability to increase condom use and prevent infection with HIV and sexually transmitted diseases. Because Project RESPECT had guiding concepts that determined the content of the sessions, the authors investigated how the intervention operated using these theoretical variables. Growth curve analysis and structural equation modeling estimated the correlation between intentions toward condom use and self-reports of condom use and isolated the treatment effects on mediating variables—attitudes, self-efficacy, and social norms—that predict intentions. The correlations between intentions and behavior exceeded .70 for both genders, justifying the emphasis on intentions. Project RESPECT was effective through changing attitudes and self-efficacy for females in both counseling interventions. For males, only enhanced counseling had significant effects on these two mediator variables.

[1]  J. S. Long,et al.  Testing Structural Equation Models , 1993 .

[2]  M. Fishbein,et al.  Failure to find a behavioral surrogate for STD incidence--what does it really mean? , 2000, Sexually transmitted diseases.

[3]  M. Fishbein,et al.  Quality assurance of HIV prevention counseling in a multi-center randomized controlled trial. Project RESPECT Study Group. , 1996, Public health reports.

[4]  P. Bentler,et al.  Evaluating model fit. , 1995 .

[5]  M. Fishbein,et al.  Acting on one's intentions: Variations in condom use intentions and behaviours as a function of type of partner, gender, ethnicity and risk , 2000, Psychology, health & medicine.

[6]  James L. Arbuckle,et al.  Full Information Estimation in the Presence of Incomplete Data , 1996 .

[7]  G. A. Marcoulides,et al.  A First Course in Structural Equation Modeling , 2000 .

[8]  F Rhodes,et al.  Efficacy of risk-reduction counseling to prevent human immunodeficiency virus and sexually transmitted diseases: a randomized controlled trial. Project RESPECT Study Group. , 1998, JAMA.

[9]  David R. Holtgrave,et al.  NIMH/APPC workgroup on behavioral and biological outcomes in HIV/STD prevention studies: a position statement. , 2000, Sexually transmitted diseases.

[10]  N M Thompson,et al.  Analysis of change: modeling individual growth. , 1991, Journal of consulting and clinical psychology.

[11]  M. Hennessy,et al.  Using structural equations to estimate effects of behavioral interventions , 1994 .

[12]  A. Lazzarin,et al.  Man-to-woman sexual transmission of HIV: longitudinal study of 343 steady partners of infected men. , 1993, Journal of acquired immune deficiency syndromes.

[13]  Jan de Leeuw,et al.  Introducing Multilevel Modeling , 1998 .

[14]  John W. Graham,et al.  Analysis With Missing Data in Prevention Research , 1997 .

[15]  M. Appelbaum,et al.  Estimating Individual Developmental Functions: Methods and Their Assumptions , 1991 .

[16]  M. Fishbein,et al.  Evaluating AIDS Prevention Interventions Using Behavioral and Biological Outcome Measures , 2000, Sexually transmitted diseases.

[17]  D. Rubin,et al.  Statistical Analysis with Missing Data , 1988 .

[18]  Richard G. Lomax,et al.  A Beginner's Guide to Structural Equation Modeling , 2022 .

[19]  Mark W. Lipsey,et al.  Theory as method: Small theories of treatments , 1993 .

[20]  King K. Holmes,et al.  Research issues in human behavior and sexually transmitted diseases in the AIDS era , 1991 .

[21]  Huey-tsyh Chen.  Theory-driven evaluations , 1990 .

[22]  I. de Vincenzi,et al.  A Longitudinal Study of Human Immunodeficiency Virus Transmission by Heterosexual Partners , 1994 .

[23]  Craig K. Enders,et al.  A Primer on Maximum Likelihood Algorithms Available for Use With Missing Data , 2001 .

[24]  Geoffrey M. Maruyama,et al.  Basics of structural equation modeling , 1997 .

[25]  Bringing It All Together: Modeling Intervention Processes Using Structural Equation Modeling , 1999 .

[26]  J. Zenilman,et al.  Using growth curves to determine the timing of booster sessions , 1999 .

[27]  Roderick J. A. Little,et al.  The Analysis of Social Science Data with Missing Values , 1989 .

[28]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[29]  M. Fishbein,et al.  Factors influencing behavior and behavior change. , 2000 .

[30]  Martin Fishbein,et al.  Using Information to Change Sexually Transmitted Disease-Related Behaviors , 1994 .

[31]  John B. Willett,et al.  Cross-Domain Analyses of Change Over Time: Combining Growth Modeling and Covariance Structure Analysis , 1996 .

[32]  Rex B. Kline,et al.  Software Review: Software Programs for Structural Equation Modeling: Amos, EQS, and LISREL , 1998 .

[33]  M. Hennessy,et al.  Equation Modeling Bringing It All Together : Modeling Intervention Processes Using Structural , 2000 .

[34]  M. Kaneko,et al.  A methodological inquiry into the evaluation of smoking cessation programmes. , 1999, Health education research.

[35]  R. Hoyle.  Structural equation modeling: concepts, issues, and applications , 1997 .

[36]  Terry E. Duncan,et al.  An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Application, Second Edition , 1999 .

[37]  T. Revenson,et al.  Handbook of Health Psychology , 2001 .

[38]  H. Marsh,et al.  An evaluation of incremental fit indices: A clarification of mathematical and empirical properties. , 1996 .

[39]  G. A. Marcoulides,et al.  Advanced structural equation modeling : issues and techniques , 1996 .

[40]  Joop J. Hox,et al.  Amos, Eqs and Lisrel for Windows: A comparative review , 1995 .

[41]  C. Weiss.  How Can Theory-Based Evaluation Make Greater Headway? , 1997 .