Archives of Sexual Behavior

, Volume 48, Issue 8, pp 2305–2320 | Cite as

Using Composite Scores to Summarize Adolescent Sexual Risk Behavior: Current State of the Science and Recommendations

  • David H. BarkerEmail author
  • Lori A. J. Scott-Sheldon
  • Daniel Gittins Stone
  • Larry K. Brown
Original Paper


Composite scores offer the advantage of summarizing across multiple sexual risk behaviors to both simplify results and better capture the influence of core contextual, interpersonal, and intrapersonal dynamics that affect multiple sexual risk behaviors. There is inconsistency in how researchers utilize composite scores with minimal guidance on the advantages and disadvantages of frequently used approaches. Strengths and weaknesses of each approach are discussed in the context of assessing adolescent sexual risk behavior. A latent variable model and three commonly used composites were applied to data combined across four clinical trials (n = 1322; 50% female). Findings suggested that the latent variable approach was limited due to minimal correlations among sexual risk behaviors, that choice of composite had minimal impact on cross-sectional results so long as there is sufficient variability in risk behavior in the sample, but composite choice could impact results from clinical trials particularly for subgroup analyses. There are unique challenges to creating composites of adolescent risk behavior, including the fluidity and infrequency of adolescent sexual relationships that result in many participants reporting no sexual behavior at any given assessment and a low correlation between the number of partners and condomless sex acts. These challenges impede application of data-driven approaches to defining sexual risk composites. Recommendations to improve consistency in reporting include: (1) reporting each type of risk behavior separately prior to forming a composite, (2) aggregating across assessments to increase the chance of observing sexual risk behaviors, and (3) continued work toward a unified definition of adolescent sexual risk behavior that can guide the development of appropriate measurement models.


Adolescence Sexual risk behavior HIV Clinical trials 



This work was supported by the National Institute of Mental Health (K23MH102131 to David H. Barker) and by the National Institute on Alcohol Abuse and Alcoholism (R01AA021355 to Lori A. J. Scott-Sheldon) of the National Institutes of Health. The work was facilitated by the Providence/Boston Center for AIDS Research (P30AI042853). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.


This study was funded by the following grants: National Institute of Mental Health (K23MH102131); National Institute on Alcohol Abuse and Alcoholism (R01AA021355), and National Institute of Allergy and Infectious Diseases (P30 AI042853).

Compliance with Ethical Standards

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all parents/caregivers, and assent was obtained from all participants under the age of 18.


  1. Aicken, C. R. H., Gray, M., Clifton, S., Tanton, C., Field, N., Sonnenberg, P., et al. (2013). Improving questions on sexual partnerships: Lessons learned from cognitive interviews for Britain’s Third National Survey of Sexual Attitudes and Lifestyles (“Natsal-3”). Archives of Sexual Behavior,42, 173–185.Google Scholar
  2. Ashenhurst, J. R., Wilhite, E. R., Harden, K. P., & Fromme, K. (2017). Number of sexual partners and relationship status are associated with unprotected sex across emerging adulthood. Archives of Sexual Behavior,46, 419–432.PubMedGoogle Scholar
  3. Atkins, D. C., Baldwin, S. A., Zheng, C., Gallop, R. J., & Neighbors, C. (2013). A tutorial on count regression and zero-altered count models for longitudinal substance use data. Psychology of Addictive Behaviors,27, 166–177.PubMedGoogle Scholar
  4. Bancroft, J., Janssen, E., Strong, D., Carnes, L., Vukadinovic, Z., & Long, J. S. (2003). Sexual risk-taking in gay men: The relevance of sexual arousability, mood, and sensation seeking. Archives of Sexual Behavior,32, 555–572.PubMedGoogle Scholar
  5. Beadnell, B., Morrison, D. M., Wilsdon, A., Wells, E. A., Murowchick, E., Hoppe, M., … Nahom, D. (2005). Condom use, frequency of sex, and number of partners: Multidimensional characterization of adolescent sexual risk-taking. Journal of Sex Research,42, 192–202.PubMedGoogle Scholar
  6. Bird, H. R., Shaffer, D., Fisher, P., & Gould, M. S. (1993). The Columbia Impairment Scale (CIS): Pilot findings on a measure of global impairment for children and adolescents. International Journal of Methods in Psychiatric Research,3, 167–176.Google Scholar
  7. Blakemore, S.-J. (2008). The social brain in adolescence. Nature Reviews Neuroscience,9, 267.PubMedGoogle Scholar
  8. Blood, E. A., & Shrier, L. A. (2013). The temporal relationship between momentary affective states and condom use in depressed adolescents. Archives of Sexual Behavior,42, 1209–1216.PubMedGoogle Scholar
  9. Boekeloo, B. O., Schamus, L. A., Simmens, S. J., Cheng, T. L., O’Connor, K., & D’Angelo, L. J. (1999). A STD/HIV prevention trial among adolescents in managed care. Pediatrics,103, 107–115.PubMedGoogle Scholar
  10. Bollen, K. A., & Bauldry, S. (2011). Three Cs in measurement models: Causal indicators, composite indicators, and covariates. Psychological Methods,16, 265–284.PubMedCentralPubMedGoogle Scholar
  11. Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2003). The theoretical status of latent variables. Psychological Review,110, 203–219.Google Scholar
  12. Bowleg, L., Neilands, T., Tabb, L. P., Burkholder, G. J., Malebranche, D. J., & Tschann, J. M. (2014). Neighborhood context and Black heterosexual men’s sexual HIV risk behaviors. AIDS and Behavior,18, 2207–2218.PubMedCentralPubMedGoogle Scholar
  13. Brown, L. K., Nugent, N. R., Houck, C. D., Lescano, C. M., Whiteley, L. B., Barker, D., … Zlotnick, C. (2011). Safe Thinking and Affect Regulation (STAR): Human immunodeficiency virus prevention in alternative/therapeutic schools. Journal of the American Academy of Child and Adolescent Psychiatry,50, 1065–1074.PubMedCentralPubMedGoogle Scholar
  14. Carey, M. P., Carey, K. B., Maisto, S. A., Gordon, C. M., Schroder, K. E. E., & Vanable, P. A. (2004). Reducing HIV-risk behavior among adults receiving outpatient psychiatric treatment: Results from a randomized controlled trial. Journal of Consulting and Clinical Psychology,72, 252–268.PubMedCentralPubMedGoogle Scholar
  15. Carey, M. P., Carey, K. B., Maisto, S. A., Gordon, C. M., & Weinhardt, L. S. (2001). Assessing sexual risk behaviour with the Timeline Followback (TLFB) approach: Continued development and psychometric evaluation with psychiatric outpatients. International Journal of STD and AIDS,12, 365–375.Google Scholar
  16. Carmona, J., Slesnick, N., Guo, X., & Letcher, A. (2014). Reducing high risk behaviors among street living youth: Outcomes of an integrated prevention intervention. Children and Youth Services Review,43, 118–123.PubMedCentralPubMedGoogle Scholar
  17. Carver, K., Joyner, K., & Udry, J. R. (2003). National estimates of adolescent romantic relationships. In P. Florsheim (Ed.), Adolescent romantic relations and sexual behavior: Theory, research, and practical implications (pp. 23–56). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  18. Collins, R. L., Kashdan, T. B., Koutsky, J. R., Morsheimer, E. T., & Vetter, C. J. (2008). A self-administered timeline followback to measure variations in underage drinkers’ alcohol intake and binge drinking. Addictive Behaviors,33, 196–200.Google Scholar
  19. Connolly, J., & McIsaac, C. (2009). Adolescents’ explanations for romantic dissolutions: A developmental perspective. Journal of Adolescence,32, 1209–1223.Google Scholar
  20. Cooper, M. L. (2010). Toward a person × situation model of sexual risk-taking behaviors: Illuminating the conditional effects of traits across sexual situations and relationship contexts. Journal of Personality and Social Psychology,98, 319–341.Google Scholar
  21. Coyle, K. K., Kirby, D. B., Robin, L. E., Banspach, S. W., Baumler, E., & Glassman, J. R. (2006). All4You! A randomized trial of an HIV, other STDs, and pregnancy prevention intervention for alternative school students. AIDS Education and Prevention,18, 187–203.Google Scholar
  22. Crosby, G. M., Stall, R. D., Paul, J. P., Barrett, D. C., & Midanik, L. T. (1996). Condom use among gay/bisexual male substance abusers using the timeline follow-back method. Addictive Behaviors,21, 249–257.Google Scholar
  23. Denison, J. A., O’Reilly, K. R., Schmid, G. P., Kennedy, C. E., & Sweat, M. D. (2008). HIV voluntary counseling and testing and behavioral risk reduction in developing countries: A meta-analysis, 1990–2005. AIDS and Behavior,12, 363–373.Google Scholar
  24. DiClemente, R. J., Wingood, G. M., Rose, E. S., Sales, J. M., Lang, D. L., Caliendo, A. M., … Crosby, R. A. (2009). Efficacy of sexually transmitted disease/human immunodeficiency virus sexual risk-reduction intervention for African American adolescent females seeking sexual health services: A randomized controlled trial. Archives of Pediatrics and Adolescent Medicine,163, 1112–1121.Google Scholar
  25. Dolezal, C., Marhefka, S. L., Santamaria, E. K., Leu, C.-S., Brackis-Cott, E., & Mellins, C. A. (2012). A comparison of audio computer-assisted self-interviews to face-to-face interviews of sexual behavior among perinatally HIV-exposed youth. Archives of Sexual Behavior,41, 401–410.Google Scholar
  26. Edwards, J. R. (2011). The fallacy of formative measurement. Organizational Research Methods,14, 370–388.Google Scholar
  27. Epstein, M., Bailey, J. A., Manhart, L. E., Hill, K. G., & Hawkins, J. D. (2014). Sexual risk behavior in young adulthood: Broadening the scope beyond early sexual initiation. Journal of Sex Research,51, 721–730.PubMedCentralPubMedGoogle Scholar
  28. Falasinnu, T., Gilbert, M., Hottes, T. S., Gustafson, P., Ogilvie, G., & Shoveller, J. (2015). Predictors identifying those at increased risk for STDs: A theory-guided review of empirical literature and clinical guidelines. International Journal of STD and AIDS,26, 839–851.Google Scholar
  29. Fenton, K. A. (2001). Measuring sexual behaviour: Methodological challenges in survey research. Sexually Transmitted Infections,77, 84–92.PubMedCentralPubMedGoogle Scholar
  30. Fergus, S., Zimmerman, M. A., & Caldwell, C. H. (2007). Growth trajectories of sexual risk behavior in adolescence and young adulthood. American Journal of Public Health,97, 1096–1101.PubMedCentralPubMedGoogle Scholar
  31. Fonner, V. A., Kennedy, C. E., O’Reilly, K. R., & Sweat, M. D. (2013). Systematic assessment of condom use measurement in evaluation of HIV prevention interventions: Need for standardization of measures. AIDS and Behavior,18, 2374–2386.Google Scholar
  32. Gioia, C. J., Sobell, L. C., Sobell, M. B., & Simco, E. R. (2012). Shorter and proximal timeline followback windows are representative of longer posttreatment functioning. Psychology of Addictive Behaviors,26, 880–887.Google Scholar
  33. Graham, C. A., Crosby, R. A., Sanders, S. A., & Yarber, W. L. (2005). Assessment of condom use in men and women. Annual Review of Sex Research,16, 20–52.Google Scholar
  34. Graham, S. M., Raboud, J., McClelland, R. S., Jaoko, W., Ndinya-Achola, J., Mandaliya, K., … Bayoumi, A. M. (2013). Loss to follow-up as a competing risk in an observational study of HIV-1 incidence. PLoS ONE,8(3), e59480. Scholar
  35. Herbenick, D., Reece, M., Schick, V., Sanders, S. A., Dodge, B., & Fortenberry, J. D. (2010). Sexual behavior in the United States: Results from a national probability sample of men and women ages 14–94. Journal of Sexual Medicine,7, 255–265.Google Scholar
  36. Heywood, W., Patrick, K., Smith, A. M. A., & Pitts, M. K. (2015). Associations between early first sexual intercourse and later sexual and reproductive outcomes: A systematic review of population-based data. Archives of Sexual Behavior,44, 531–569.PubMedGoogle Scholar
  37. Hipwell, A. E., Stepp, S. D., Keenan, K., Chung, T., & Loeber, R. (2011). Parsing the heterogeneity of adolescent girls’ sexual behavior: Relationships to individual and interpersonal factors. Journal of Adolescence,34, 589–592.Google Scholar
  38. Hjorthøj, C. R., Hjorthøj, A. R., & Nordentoft, M. (2012). Validity of timeline follow-back for self-reported use of cannabis and other illicit substances—Systematic review and meta-analysis. Addictive Behaviors,37, 225–233.PubMedGoogle Scholar
  39. Huang, D. Y. C., Lanza, H. I., Murphy, D. A., & Hser, Y. I. (2012). Parallel development of risk behaviors in adolescence: Potential pathways to co-occurrence. International Journal of Behavioral Development,36, 247–257.PubMedCentralPubMedGoogle Scholar
  40. Huebner, A. J., & Howell, L. W. (2003). Examining the relationship between adolescent sexual risk-taking and perceptions of monitoring, communication, and parenting styles. Journal of Adolescent Health,33, 71–78.Google Scholar
  41. Jemmott, J. B., 3rd, Jemmott, L. S., & Fong, G. T. (2010). Efficacy of a theory-based abstinence-only intervention over 24 months: A randomized controlled trial with young adolescents. Archives of Pediatrics and Adolescent Medicine,164, 152–159.Google Scholar
  42. Kuhn, M., & Johnson, K. (2013). Applied predictive modeling. New York: Springer.Google Scholar
  43. Lagakos, S. W. (2006). The challenge of subgroup analyses—Reporting without distorting. New England Journal of Medicine,354, 1667–1669.Google Scholar
  44. Lanza, S. T., & Collins, L. M. (2008). A new SAS procedure for latent transition analysis: Transitions in dating and sexual risk behavior. Developmental Psychology,44, 446–456.PubMedCentralPubMedGoogle Scholar
  45. Le Pont, F., Pech, N., & Boelle, P. Y. (2003). A new scale for measuring dynamic patterns of sexual partnership and concurrency: Application to three French Caribbean regions. Sexually Transmitted Diseases,30, 6–9.PubMedGoogle Scholar
  46. Lescano, C. M., Vazquez, E. A., Brown, L. K., Litvin, E. B., & Pugatch, D. (2006). Condom use with “casual” and “main” partners: What’s in a name? Journal of Adolescent Health,39, 443.e1–443.e7.Google Scholar
  47. Li, X., Stanton, B., & Feigelman, S. (2000). Impact of perceived parental monitoring on adolescent risk behavior over 4 years. Journal of Adolescent Health,27, 49–56.PubMedGoogle Scholar
  48. Lightfoot, M. (2012). HIV prevention for adolescents: Where do we go from here? American Psychologist,67, 661–671.PubMedGoogle Scholar
  49. Maisto, S. A., Conigliaro, J. C., Gordon, A. J., McGinnis, K. A., & Justice, A. C. (2008). An experimental study of the agreement of self-administration and telephone administration of the timeline followback interview. Journal of Studies on Alcohol and Drugs,69, 468–471.PubMedCentralPubMedGoogle Scholar
  50. Manning, W. D., Longmore, M. A., Copp, J., & Giordano, P. C. (2014). The complexities of adolescent dating and sexual relationships: Fluidity, meaning(s), and implications for young adults’ well-being. New Directions for Child and Adolescent Development,144, 53–69.Google Scholar
  51. Markham, C. M., Lormand, D., Gloppen, K. M., Peskin, M. F., Flores, B., Low, B., & House, L. D. (2010). Connectedness as a predictor of sexual and reproductive health outcomes for youth. Journal of Adolescent Health,46, S23–S41.Google Scholar
  52. Mattson, C. L., Campbell, R. T., Karabatsos, G., Agot, K., Ndinya-Achola, J. O., Moses, S., & Bailey, R. C. (2008). Scaling sexual behavior or “sexual risk propensity” among men at risk for HIV in Kisumu, Kenya. AIDS and Behavior,14, 162–172.Google Scholar
  53. McAuliffe, T. L., DiFranceisco, W., & Reed, B. R. (2010). Low numeracy predicts reduced accuracy of retrospective reports of frequency of sexual behavior. AIDS and Behavior,14, 1320–1329.PubMedCentralPubMedGoogle Scholar
  54. Mullen, P. D., Ramirez, G., Strouse, D., Hedges, L. V., & Sogolow, E. (2002). Meta-analysis of the effects of behavioral HIV prevention interventions on the sexual risk behavior of sexually experienced adolescents in controlled studies in the United States. Journal of Acquired Immune Deficiency Syndromes,30, S94–S105.Google Scholar
  55. Murphy, D. A., Brecht, M.-L., Herbeck, D. M., & Huang, D. (2009). Trajectories of HIV risk behavior from age 15 to 25 in the national longitudinal survey of youth sample. Journal of Youth and Adolescence,38, 1226–1239.Google Scholar
  56. Murry, V. M., Berkel, C., Chen, Y., Brody, G. H., Gibbons, F. X., & Gerrard, M. (2011). Intervention induced changes on parenting practices, youth self-pride and sexual norms to reduce HIV-related behaviors among rural African American youths. Journal of Youth and Adolescence,40, 1147–1163.PubMedCentralPubMedGoogle Scholar
  57. Mustanski, B. (2008). Moderating effects of age on the alcohol and sexual risk taking association: An online daily diary study of men who have sex with men. AIDS and Behavior,12, 118–126.Google Scholar
  58. Napper, L. E., Fisher, D. G., Reynolds, G. L., & Johnson, M. E. (2010). HIV risk behavior self-report reliability at different recall periods. AIDS and Behavior,14, 152–161.Google Scholar
  59. Newman, P. A., & Zimmerman, M. A. (2000). Gender differences in HIV-related sexual risk behavior among urban African American youth: A multivariate approach. AIDS Education and Prevention,12, 308–325.Google Scholar
  60. Noar, S. M. (2008). Behavioral interventions to reduce HIV-related sexual risk behavior: Review and synthesis of meta-analytic evidence. AIDS and Behavior,12, 335–353.Google Scholar
  61. Norberg, M. M., Mackenzie, J., & Copeland, J. (2012). Quantifying cannabis use with the timeline followback approach: A psychometric evaluation. Drug and Alcohol Dependence,121, 247–252.Google Scholar
  62. Pearlman, D. N., Camberg, L., Wallace, L. J., Symons, P., & Finison, L. (2002). Tapping youth as agents for change. Journal of Adolescent Health,31, 31–39.Google Scholar
  63. Pedersen, E. R., Grow, J., Duncan, S., Neighbors, C., & Larimer, M. E. (2012). Concurrent validity of an online version of the timeline followback assessment. Psychology of Addictive Behaviors,26, 672–677.PubMedCentralPubMedGoogle Scholar
  64. Pequegnat, W., Hartwell, T. D., Green, A. M., Strader, L. C., & Group, N. I. of M. H. C. H. P. T. (2016). How many sexual partners of an individual need to be evaluated to capture HIV/STI risk behavior in a study? AIDS and Behavior,20, 1353–1359.Google Scholar
  65. Raffaelli, M., & Crockett, L. J. (2003). Sexual risk taking in adolescence: The role of self-regulation and attraction to risk. Developmental Psychology,39, 1036–1046.Google Scholar
  66. Reece, M., Herbenick, D., Schick, V., Sanders, S. A., Dodge, B., & Fortenberry, J. D. (2010). Condom use rates in a national probability sample of males and females ages 14 to 94 in the United States. Journal of Sexual Medicine,7, 266–276.Google Scholar
  67. Rizzo, C. J., Joppa, M. C., Barker, D., Zlotnick, C., Warren, J., Saint-Eloi Cadely, H., & Brown, L. K. (2017). Individual and relationship characteristics of adolescent girls with histories of physical dating violence. Journal of Interpersonal Violence. Scholar
  68. Rueger, S. Y., Trela, C. J., Palmeri, M., & King, A. C. (2012). Self-administered web-based timeline followback procedure for drinking and smoking behaviors in young adults. Journal of Studies on Alcohol and Drugs,73, 829–833.PubMedCentralPubMedGoogle Scholar
  69. Schroder, K. E. E., Carey, M. P., & Vanable, P. A. (2003a). Methodological challenges in research on sexual risk behavior: I. Item content, scaling, and data analytical options. Annals of Behavioral Medicine,26, 76–103.PubMedCentralPubMedGoogle Scholar
  70. Schroder, K. E. E., Carey, M. P., & Vanable, P. A. (2003b). Methodological challenges in research on sexual risk behavior: II. Accuracy of self-reports. Annals of Behavioral Medicine,26, 104–123.PubMedCentralPubMedGoogle Scholar
  71. Scott-Sheldon, L. A. J., Kalichman, S. C., & Carey, M. P. (2010). Assessment of sexual behavior. In A. Steptoe (Ed.), Handbook of behavioral medicine (pp. 59–72). New York, NY: Springer.Google Scholar
  72. Senn, T. E., Scott-Sheldon, L. A. J., & Carey, M. P. (2014). Relationship-specific condom attitudes predict condom use among STD clinic patients with both primary and non-primary partners. AIDS and Behavior,18, 1420–1427.PubMedCentralPubMedGoogle Scholar
  73. Siegel, D. M., Aten, M. J., & Enaharo, M. (2001). Long-term effects of a middle school—And high school-based human immunodeficiency virus sexual risk prevention intervention. Archives of Pediatrics and Adolescent Medicine,155, 1117–1126.Google Scholar
  74. Slater, C., & Robinson, A. J. (2014). Sexual health in adolescents. Clinics in Dermatology,32, 189–195.PubMedGoogle Scholar
  75. Sliwinski, M. J. (2008). Measurement-burst designs for social health research. Social and Personality Psychology Compass,2, 245–261.Google Scholar
  76. Sobell, L. C., Agrawal, S., Annis, H., Ayala-Velazquez, H., Echeverria, L., Leo, G. I., … Zióikowski, M. (2001). Cross-cultural evaluation of two drinking assessment instruments: Alcohol timeline followback and inventory of drinking situations. Substance Use and Misuse,36, 313–331.PubMedGoogle Scholar
  77. Sobell, L. C., Brown, J., Leo, G. I., & Sobell, M. B. (1996). The reliability of the alcohol timeline followback when administered by telephone and by computer. Drug and Alcohol Dependence,42, 49–54.PubMedGoogle Scholar
  78. Somerville, L. H. (2013). The teenage brain: Sensitivity to social evaluation. Current Directions in Psychological Science,22, 121–127.PubMedCentralPubMedGoogle Scholar
  79. Staras, S. A. S., Livingston, M. D., Maldonado-Molina, M. M., & Komro, K. A. (2013). The influence of sexual partner on condom use among urban adolescents. Journal of Adolescent Health,53, 742–748.PubMedGoogle Scholar
  80. Susser, E., Desvarieux, M., & Wittkowski, K. M. (1998). Reporting sexual risk behavior for HIV: A practical risk index and a method for improving risk indices. American Journal of Public Health,88, 671–674.PubMedCentralPubMedGoogle Scholar
  81. Tortolero, S. R., Markham, C. M., Peskin, M. F., Shegog, R., Addy, R. C., Escobar-Chaves, S. L., & Baumler, E. R. (2010). It’s your game: Keep it real: Delaying sexual behavior with an effective middle school program. Journal of Adolescent Health,46, 169–179.Google Scholar
  82. Vasilenko, S. A., Kugler, K. C., Butera, N. M., & Lanza, S. T. (2014). Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: A latent class analysis approach. Archives of Sexual Behavior,44, 705–715.PubMedCentralPubMedGoogle Scholar
  83. Webb, M. C., Chaney, J. D., Chen, W. W., Dodd, V. J., Huang, I.-C., & Sanders, S. (2015). Assessing specific sexual behavior: Instrument development and validation techniques. International Journal of Education and Social Science,2, 1–11.PubMedCentralPubMedGoogle Scholar
  84. Weinhardt, L. S., Carey, M. P., Maisto, S. A., Carey, K. B., Cohen, M. M., & Wickramasinghe, S. M. (1998). Reliability of the timeline follow-back sexual behavior interview. Annals of Behavioral Medicine,20, 25–30.PubMedCentralPubMedGoogle Scholar
  85. Williams, M., McCoy, H. V., Bowen, A., Saunders, L., Freeman, R., & Chen, D. (2001). An evaluation of a brief HIV risk reduction intervention using empirically derived drug use and sexual risk indices. AIDS and Behavior,5, 31–43.Google Scholar
  86. Wilson, H. W., & Widom, C. S. (2011). Pathways from childhood abuse and neglect to HIV-risk sexual behavior in middle adulthood. Journal of Consulting and Clinical Psychology,79, 236–246.PubMedCentralPubMedGoogle Scholar
  87. Wray, T. B., Kahler, C. W., & Monti, P. M. (2016). Using ecological momentary assessment (EMA) to study sex events among very high-risk men who have sex with men (MSM). AIDS and Behavior,20, 2231–2242.PubMedCentralPubMedGoogle Scholar
  88. Wu, Y., Burns, J. J., Stanton, B. F., Li, X., Harris, C. V., Galbraith, J., & Wei, L. (2005). Influence of prior sexual risk experience on response to intervention targeting multiple risk behaviors among adolescents. Journal of Adolescent Health,36, 56–63.Google Scholar

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Authors and Affiliations

  1. 1.Department of Psychiatry and Human Behavior, The Warren Alpert Medical SchoolBrown UniversityProvidenceUSA
  2. 2.Division of Child and Adolescent PsychiatryRhode Island HospitalProvidenceUSA
  3. 3.Centers for Behavioral and Preventive MedicineThe Miriam HospitalProvidenceUSA
  4. 4.Department of Behavioral and Social SciencesBrown University School of Public HealthProvidenceUSA
  5. 5.Department of Applied Psychology, Bouvé College of Health SciencesNortheastern UniversityBostonUSA

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