Literature DB >> 31429032

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

David H Barker1,2, Lori A J Scott-Sheldon3,4,5, Daniel Gittins Stone6, Larry K Brown3,7.   

Abstract

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.

Entities:  

Keywords:  Adolescence; Clinical trials; HIV; Sexual risk behavior

Mesh:

Year:  2019        PMID: 31429032      PMCID: PMC6759377          DOI: 10.1007/s10508-019-01526-8

Source DB:  PubMed          Journal:  Arch Sex Behav        ISSN: 0004-0002


  81 in total

1.  Assessing sexual risk behaviour with the Timeline Followback (TLFB) approach: continued development and psychometric evaluation with psychiatric outpatients.

Authors:  M P Carey; K B Carey; S A Maisto; C M Gordon; L S Weinhardt
Journal:  Int J STD AIDS       Date:  2001-06       Impact factor: 1.359

2.  A new scale for measuring dynamic patterns of sexual partnership and concurrency: application to three French Caribbean regions.

Authors:  Françoise Le Pont; Nicolas Pech; Pierre-Yves Boelle; Michel Giraud; Augustin Gilloire; Sandrine Halfen; Patrick de Colomby
Journal:  Sex Transm Dis       Date:  2003-01       Impact factor: 2.830

3.  Condom use, frequency of sex, and number of partners: multidimensional characterization of adolescent sexual risk-taking.

Authors:  Blair Beadnell; Diane M Morrison; Anthony Wilsdon; Elizabeth A Wells; Elise Murowchick; Marilyn Hoppe; Mary Rogers Gillmore; Deborah Nahom
Journal:  J Sex Res       Date:  2005-08

Review 4.  HIV prevention for adolescents: where do we go from here?

Authors:  Marguerita Lightfoot
Journal:  Am Psychol       Date:  2012-11

5.  Self-administered web-based timeline followback procedure for drinking and smoking behaviors in young adults.

Authors:  Sandra Yu Rueger; Constantine J Trela; Michael Palmeri; Andrea C King
Journal:  J Stud Alcohol Drugs       Date:  2012-09       Impact factor: 2.582

6.  Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: a latent class analysis approach.

Authors:  Sara A Vasilenko; Kari C Kugler; Nicole M Butera; Stephanie T Lanza
Journal:  Arch Sex Behav       Date:  2014-01-22

7.  Long-term effects of a middle school- and high school-based human immunodeficiency virus sexual risk prevention intervention.

Authors:  D M Siegel; M J Aten; M Enaharo
Journal:  Arch Pediatr Adolesc Med       Date:  2001-10

8.  A tutorial on count regression and zero-altered count models for longitudinal substance use data.

Authors:  David C Atkins; Scott A Baldwin; Cheng Zheng; Robert J Gallop; Clayton Neighbors
Journal:  Psychol Addict Behav       Date:  2012-08-20

Review 9.  The social brain in adolescence.

Authors:  Sarah-Jayne Blakemore
Journal:  Nat Rev Neurosci       Date:  2008-04       Impact factor: 34.870

10.  Scaling sexual behavior or "sexual risk propensity" among men at risk for HIV in Kisumu, Kenya.

Authors:  C L Mattson; Richard T Campbell; George Karabatsos; Kawango Agot; J O Ndinya-Achola; Stephen Moses; Robert C Bailey
Journal:  AIDS Behav       Date:  2008-07-24
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  1 in total

1.  Causally Interpretable Meta-analysis: Application in Adolescent HIV Prevention.

Authors:  David H Barker; Issa J Dahabreh; Jon A Steingrimsson; Christopher Houck; Geri Donenberg; Ralph DiClemente; Larry K Brown
Journal:  Prev Sci       Date:  2021-07-09
  1 in total

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