CClinicalTrials.gg
CompletedNCT02921841DSTARUpdated Jan 27, 2020Results posted

Digital Star: HIV Prevention for Youth in Mental Health Treatment

An interventional study of D*STAR and D*HEALTH in Human Immunodeficiency Virus and Mental Health, sponsored by Rhode Island Hospital. Completed at 1 site in United States. Open to participants aged 13 Years to 20 Years. Per ClinicalTrials.gov, last updated 2020-01-27.

Sponsored by Rhode Island Hospital · Not applicable, Interventional, and Prevention

Phase
Not applicable
Study type
Interventional
Enrollment
125
Allocation
Randomized
Ages
13 Years to 20 Years
Sex
All
01

Study summary

Teenagers in mental health treatment are at greater risk for HIV and other sexually transmitted infections. This greater risk comes from many factors, some of which are related to poor emotion regulation and low self-confidence. There is a need for an HIV prevention program specifically for these at-risk teens. The goal of this study is to develop a computerized HIV prevention study tailored to adolescents in mental health treatment. The first part of the study will develop core sessions of D*STAR. It will do this by using focus group feedback from approximately 15 adolescents in mental health treatment, and approximately 10 parents of youth in mental health treatment and mental health treatment center staff. Feedback on D*STAR prototype sessions will also be collected from two individual interviews with approximately 15 youth in mental health treatment. Core sessions will then be reviewed in an open trial with approximately 30 adolescents.

The second part of the study will develop and refine digital versions of the remaining sessions of STAR and a digital general health promotion intervention. It will do this by using focus group feedback from approximately 20 adolescents in mental health treatment, and approximately 10 community advisory board members which include variety of staff from mental health treatment settings such as administrators, supervisors, therapists, health teachers at therapeutic schools, clinicians at day hospitals and day treatment programs, parents of youth in mental health treatment and from relevant community organizations, such as those serving lesbian, gay, bisexual, transgender, and questioning youth. Feedback on D*STAR prototype sessions will also be collected from two individual interviews with approximately 20 youth in mental health treatment. All developed sessions (from both Phase I and Phase II) will then be reviewed in an open trial with approximately 20 adolescents. A randomized control trial (RCT) will then be conducted to compare D*STAR to a time matched digital general health promotion intervention among approximately 120 adolescents. For the pilot and RCT phases, assessments will be administered prior to randomization, immediately following the last intervention session, and at one month post-intervention (pilot study) or at three month post-intervention (RCT).

Read the detailed description

Adolescents in mental health treatment are at greater risk for HIV and other STIs than their peers due to an earlier age of onset of sex, less protected sex, more sexual partners, and more frequent substance use. The numerous adolescents who receive mental health treatment do so in a variety of settings such as day hospital programs, therapeutic schools and residential centers. These programs offer a variety of health services but there is no efficacious HIV prevention program specifically tailored for the issues of youth in mental health treatment, other than the one described in this project. STAR ("Safe Thinking and Affect Regulation"). The goal of this SBIR (Small Business Innovation Research) Fast-Track project is to transform STAR into an engaging digital, multimedia format, Digital STAR (D*STAR), for easy and reliable use by care agencies that serve adolescents in mental health treatment. To transform this intervention, Virtually Better, a company with a successful history of production and distribution of cutting-edge technological interventions, has teamed with the research developers of STAR at Rhode Island Hospital and Brown University. During the two phases of this Fast-Track project, digital session development will be accomplished by an iterative process of feedback and refinement between Virtually Better, the developers of STAR, adolescents in mental health treatment, and a Community Advisory Board.

Phase 1: Specific Aims A. To develop and refine digital versions of core sessions of STAR that introduce affect regulation and cognitive monitoring in sexual situations, and provide basic sexual health skills and education. These sessions represent essential content areas and modalities of the D*STAR intervention.

B. To conduct focus groups of the feasibility, utility, and acceptability of the planned sessions. There will be focus groups with approximately 10 Community Advisory Board (CAB) members comprised of parents of youth in mental health treatment and mental health treatment staff. There will also be focus groups with approximately 15 adolescents in mental health treatment (13-18 years old) .

C. To conduct two qualitative interview sessions of approximately 15 youth with mental health treatment to determine the acceptability of the session's prototypes and revise based on feedback.

D. To conduct an open trial of D*STAR sessions with approximately 30 adolescents to determine its preliminary impact with self-report assessments at baseline and then 1 month post intervention.

Phase 2: Specific Aims A. To develop and refine digital versions the remaining sessions of STAR and a digital general health promotion (HP) intervention, building upon the essential content areas and refinements developed in Phase I.

B. To conduct qualitative evaluations of the feasibility, utility, and acceptability of D*STAR and the digital HP intervention with adolescents in mental health treatment, our Community Advisory Board (CAB), and mental health treatment center staff.

Hypothesis: Both digital interventions (HP and D*STAR) will be rated by youth, our CAB, and mental health treatment center staff as enjoyable, useful and easy to implement.

C. To conduct a randomized control trial of D*STAR compared to the time matched digital HP intervention among 120 adolescents ages 13 to 18 in mental health treatment.

Hypothesis: Participants in D*STAR will report safer sexual behaviors, greater HIV knowledge and greater self-efficacy for HIV prevention skills than participants in digital HP at three months follow-up.

02

Conditions studied

  • Human Immunodeficiency Virus
  • Mental Health

Keywords

  • Adolescents
  • HIV prevention
  • computerized intervention
  • mental health treatment
03

In context

Acquired Immunodeficiency Syndrome

2,040 studies on the registry are indexed under Acquired Immunodeficiency Syndrome; 272 are open to participants now.

This study's enrollment of 125 is above the median of 105 across 1,543 interventional studies indexed under Acquired Immunodeficiency Syndrome.

Browse Acquired Immunodeficiency Syndrome studies →

Lead sponsor

Rhode Island Hospital is the lead sponsor of 187 studies on the registry; 37 are open to participants now.

Of its 11 completed or terminated interventional studies of FDA-regulated products, 2 (18%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
13 Years to 20 Years
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

Adolescent males and females ages 13 to 20 years who are in mental health treatment will be eligible for enrollment in each phase of study according to the following criteria:

  1. English speaking,
  2. adolescent assent given to participate in the study,
  3. consent of a parent/legal guardian and HIPAA research authorization permission and
  4. attending an alternative / therapeutic school, mental health day treatment program, partial hospital program, or therapeutic group homes.

Exclusion criteria

Exclusion Criteria:

  1. self-report of HIV infection (STAR is not designed to address disclosure, stigma, and medical adherence issues),
  2. recent or current pregnancy,
  3. cognitive limitation that impairs consent capacity by judgment of clinical staff and
  4. current participation in another psychosocial intervention that is addressing STI/HIV prevention.
05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
125 participants (actual)

Study arms

  • Experimental
    DSTAR

    Digital HIV Prevention intervention developed to specifically address the needs of youth in mental health treatment. Sessions introduce affect regulation and cognitive monitoring in sexual situations, and provide basic sexual health skills and education.

    Behavioral: D*STAR

  • Active comparator
    DHEALTH

    Digital general health promotion intervention. Time and attention matched intervention that targets health behaviors relevant to youth including exercise, nutrition, sleep, and smoking. Basic information about HIV and sexuality is also included.

    Behavioral: D*HEALTH

Interventions

  • BehavioralD*STAR
  • BehavioralD*HEALTH

    Digital general health promotion intervention. Time and attention matched intervention that targets health behaviors relevant to youth including exercise, nutrition, sleep, and smoking. Basic information about HIV and sexuality is also included.

06

What researchers measure

Primary outcomes

  1. HIV Knowledge

    HIV Knowledge Questionnaire. A 18-item (true, false, uncertain) scale surveys routes of transmission, casual contact misconceptions, general information and course of illness. Scores range from 0-18 with higher scores indicating greater HIV knowledge.

    Time frame: 3 months post-intervention

  2. Self-efficacy for HIV Prevention

    The scale contains 13 items that reflect the context of condom use, such as "could use a condom when I'm very upset". Scores range from 13 to 52 with higher scores indicated lower self-efficacy for HIV prevention.

    Time frame: 3 months post-intervention

  3. Lifetime Sexual Intercourse

    Lifetime oral, vaginal, and/or anal sex

    Time frame: 3-months post-intervention

  4. Recent Oral, Vaginal, and/or Anal Sex

    Oral, vaginal, and/or anal sex in the past 3 months

    Time frame: 3-months post-intervention

  5. Frequency of Sexual Intercourse

    Number of oral, vaginal, and/or anal sexual occurrences in the past 3 months.

    Time frame: 3-months post-intervention

  6. Number of Sexual Partners

    Number of sexual partners in the past 3 months.

    Time frame: 3-months post-intervention

  7. Frequency of Condom Use

    Number of times a condom was used during oral, vaginal, and/or anal sex

    Time frame: 3-months post-intervention

  8. Condom Use Intention

    On a scale of 0 to 100, participants report how likely it is that they will use a condom when they have sex in the next 3 months. Zero represented "I will not use a condom", "50" represented "I will use a condom half the time.", and "100" represented "I will use a condom all the time.".

    Time frame: 3-months post-intervention

  9. Recent Alcohol Use

    Alcohol use in the past 30 days (yes/no)

    Time frame: 3-months post-intervention

  10. Frequency of Recent Alcohol Use

    Number of days alcohol was used in the past 30 days

    Time frame: 3-months post-intervention

  11. Quantity of Recent Alcohol Use

    Number of drinks reported on days that a participant drank alcohol in the past 30 days

    Time frame: 3-months post-intervention

  12. Recent Marijuana Use

    Marijuana use in the past 30 days (yes/no)

    Time frame: 3-months post-intervention

  13. Frequency of Recent Marijuana Use

    Number of days marijuana was used in the past 30 days

    Time frame: 3-months post-intervention

Secondary outcomes

  1. Affect Dysregulation Scale

    A six-item scale assessing adolescents' perceived abilities to manage emotional upset (e.g., "In the past three months, I have had trouble controlling my feelings.") in sexual situations. Scores range from 6 to 24 with higher scores indicated poorer perceived ability to manage emotional upset in sexual situations.

    Time frame: 3 months post-intervention (average 6 months)

07

Results

Posted Jan 27, 2020
Limitations and caveats
This study had a small sample. Participants were recruited from alternative schools across Rhode Island which may not be representative of all adolescents that attend alternative schools.

Participant flow

Participant flow — Overall Study
MilestoneDSTARDHEALTH
Started6857
Completed5244
Not completed1613

Outcome measures

PrimaryHIV Knowledge

HIV Knowledge Questionnaire. A 18-item (true, false, uncertain) scale surveys routes of transmission, casual contact misconceptions, general information and course of illness. Scores range from 0-18 with higher scores indicating greater HIV knowledge.

Time frame:
3 months post-intervention
Reported as:
Mean · score on a scale
HIV Knowledge
score on a scaleDSTARDHEALTH
HIV Knowledge11.10 ± 3.3210.98 ± 3.18
PrimarySelf-efficacy for HIV Prevention

The scale contains 13 items that reflect the context of condom use, such as "could use a condom when I'm very upset". Scores range from 13 to 52 with higher scores indicated lower self-efficacy for HIV prevention.

Time frame:
3 months post-intervention
Reported as:
Mean · score on a scale
Self-efficacy for HIV Prevention
score on a scaleDSTARDHEALTH
Self-efficacy for HIV Prevention37.83 ± 9.7637.37 ± 8.63
PrimaryLifetime Sexual Intercourse

Lifetime oral, vaginal, and/or anal sex

Time frame:
3-months post-intervention
Reported as:
Count of participants · Participants
Lifetime Sexual Intercourse
ParticipantsDSTARDHEALTH
No2315
Yes2929
PrimaryRecent Oral, Vaginal, and/or Anal Sex

Oral, vaginal, and/or anal sex in the past 3 months

Time frame:
3-months post-intervention
Reported as:
Count of participants · Participants
Recent Oral, Vaginal, and/or Anal Sex
ParticipantsDSTARDHEALTH
No3427
Yes1816
PrimaryFrequency of Sexual Intercourse

Number of oral, vaginal, and/or anal sexual occurrences in the past 3 months.

Time frame:
3-months post-intervention
Reported as:
Mean · sexual acts
Frequency of Sexual Intercourse
sexual actsDSTARDHEALTH
Frequency of Sexual Intercourse13.75 ± 18.119.40 ± 15.61
PrimaryNumber of Sexual Partners

Number of sexual partners in the past 3 months.

Time frame:
3-months post-intervention
Reported as:
Mean · sexual partners
Number of Sexual Partners
sexual partnersDSTARDHEALTH
Number of Sexual Partners2.06 ± 1.482.00 ± 1.47
PrimaryFrequency of Condom Use

Number of times a condom was used during oral, vaginal, and/or anal sex

Time frame:
3-months post-intervention
Reported as:
Mean · times a condom was used
Frequency of Condom Use
times a condom was usedDSTARDHEALTH
Frequency of Condom Use3.33 ± 6.452.36 ± 3.23
PrimaryCondom Use Intention

On a scale of 0 to 100, participants report how likely it is that they will use a condom when they have sex in the next 3 months. Zero represented "I will not use a condom", "50" represented "I will use a condom half the time.", and "100" represented "I will use a condom all the time.".

Time frame:
3-months post-intervention
Reported as:
Mean · units on a scale
Condom Use Intention
units on a scaleDSTARDHEALTH
Condom Use Intention58.75 ± 42.8461.84 ± 45.47
PrimaryRecent Alcohol Use

Alcohol use in the past 30 days (yes/no)

Time frame:
3-months post-intervention
Reported as:
Count of participants · Participants
Recent Alcohol Use
ParticipantsDSTARDHEALTH
No4236
Yes108
PrimaryFrequency of Recent Alcohol Use

Number of days alcohol was used in the past 30 days

Time frame:
3-months post-intervention
Reported as:
Mean · days
Frequency of Recent Alcohol Use
daysDSTARDHEALTH
Frequency of Recent Alcohol Use5.71 ± 10.737.57 ± 10.34
PrimaryQuantity of Recent Alcohol Use

Number of drinks reported on days that a participant drank alcohol in the past 30 days

Time frame:
3-months post-intervention
Reported as:
Mean · alcoholic drinks
Quantity of Recent Alcohol Use
alcoholic drinksDSTARDHEALTH
Quantity of Recent Alcohol Use3.14 ± 3.5310.50 ± 6.44
PrimaryRecent Marijuana Use

Marijuana use in the past 30 days (yes/no)

Time frame:
3-months post-intervention
Reported as:
Count of participants · Participants
Recent Marijuana Use
ParticipantsDSTARDHEALTH
No3532
Yes1210
PrimaryFrequency of Recent Marijuana Use

Number of days marijuana was used in the past 30 days

Time frame:
3-months post-intervention
Reported as:
Mean · days
Frequency of Recent Marijuana Use
daysDSTARDHEALTH
Frequency of Recent Marijuana Use15.83 ± 12.698.60 ± 7.51
SecondaryAffect Dysregulation Scale

A six-item scale assessing adolescents' perceived abilities to manage emotional upset (e.g., "In the past three months, I have had trouble controlling my feelings.") in sexual situations. Scores range from 6 to 24 with higher scores indicated poorer perceived ability to manage emotional upset in sexual situations.

Time frame:
3 months post-intervention (average 6 months)
Reported as:
Mean · score on a scale
Affect Dysregulation Scale
score on a scaleDSTARDHEALTH
Affect Dysregulation Scale9.39 ± 2.608.90 ± 2.97

Adverse events

Collected over Up to 5 months. Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
DSTAR0/68 (0%)0/68 (0%)0/68 (0%)
DHEALTH0/57 (0%)0/57 (0%)0/57 (0%)

Baseline characteristics

Age, Continuous
Age, Continuous(years)DSTARDHEALTHTotal
Mean15.9 ± 1.415.8 ± 1.315.8 ± 1.4
Sex/Gender, Customized
Sex/Gender, Customized(Participants)DSTARDHEALTHTotal
Gender — Male424082
Gender — Female231740
Gender — Other101
Gender — Unknown or Not Reported202
Ethnicity (NIH/OMB)
Ethnicity (NIH/OMB)(Participants)DSTARDHEALTHTotal
Hispanic or Latino242044
Not Hispanic or Latino433679
Unknown or Not Reported112
Race (NIH/OMB)
Race (NIH/OMB)(Participants)DSTARDHEALTHTotal
American Indian or Alaska Native224
Asian112
Native Hawaiian or Other Pacific Islander6612
Black or African American112
White272451
More than one race181028
Unknown or Not Reported131326
Region of Enrollment
Region of Enrollment(participants)DSTARDHEALTHTotal
United States6857125
History of Arrest
History of Arrest(Participants)DSTARDHEALTHTotal
No352661
Yes333164
Sexual Orientation
Sexual Orientation(Participants)DSTARDHEALTHTotal
Heterosexual504191
Homosexual538
Bisexual9817
Undecided/Questioning347
Unknown or Not Reported112
School Lunch Price
School Lunch Price(Participants)DSTARDHEALTHTotal
Full Price211738
Reduced Price or Free453984
Unknown or Not Reported213
08

Study locations

1 site
  • Rhode Island Hospital
    Providence, Rhode Island 02903, United States
09

References and documents

Publications

  • Brown LK, Nugent NR, Houck CD, Lescano CM, Whiteley LB, Barker D, Viau L, Zlotnick C. Safe Thinking and Affect Regulation (STAR): human immunodeficiency virus prevention in alternative/therapeutic schools. J Am Acad Child Adolesc Psychiatry. 2011 Oct;50(10):1065-74. doi: 10.1016/j.jaac.2011.06.018. Epub 2011 Aug 27. PubMed 21961780 ↗
  • CDC. Estimated HIV incidence in the United States, 2007-2010, HIV Surveillance Supplemental Report, 2012. Accessed from: http://www.cdc.gov/hiv/topics/surveillance/resources/reports/#supplemental.
  • UNAIDS. UNAIDS World AIDS Day Report, 2011, Accessed from: http://www.unaids.org/en/resources/documents/2011/20111121_JC2216_WordAIDSday_report_2011
  • CDC. 2008 Sexually Transmitted Disease Surveillance. 2009. Accessed from: http://www.cdc.gov/std/stats08/default.htm
  • Martinez G, Copen CE, Abma JC. Teenagers in the United States: sexual activity, contraceptive use, and childbearing, 2006-2010 national survey of family growth. Vital Health Stat 23. 2011 Oct;(31):1-35. PubMed 22256688 ↗
  • Kaiser Family Foundation. Medicare and HIV/AIDS Fact Sheet. February, 2009. Accessed from: http://www.kff.org/hivaids/7171.cfm
  • Schackman BR, Gebo KA, Walensky RP, Losina E, Muccio T, Sax PE, Weinstein MC, Seage GR 3rd, Moore RD, Freedberg KA. The lifetime cost of current human immunodeficiency virus care in the United States. Med Care. 2006 Nov;44(11):990-7. doi: 10.1097/01.mlr.0000228021.89490.2a. PubMed 17063130 ↗
  • CDC. Projecting Possible Future Courses of the HIV Epidemic in the United States. 2010. Accessed from: https://npin.cdc.gov/publication/projecting-possible-future-courses-hiv-epidemic-united-states
  • Brown LK, Barone VJ, Fritz GK, Cebollero P, Nassau JH. AIDS education: the Rhode Island experience. Health Educ Q. 1991 Summer;18(2):195-206. doi: 10.1177/109019819101800205. PubMed 2055777 ↗
  • Santelli JS, Kaiser J, Hirsch L, Radosh A, Simkin L, Middlestadt S. Initiation of sexual intercourse among middle school adolescents: the influence of psychosocial factors. J Adolesc Health. 2004 Mar;34(3):200-8. doi: 10.1016/j.jadohealth.2003.06.004. PubMed 14967343 ↗
  • Houck CD, Lescano CM, Brown LK, Tolou-Shams M, Thompson J, Diclemente R, Fernandez MI, Pugatch D, Schlenger WE, Silver BJ. "Islands of Risk": subgroups of adolescents at risk for HIV. J Pediatr Psychol. 2006 Jul;31(6):619-29. doi: 10.1093/jpepsy/jsj067. Epub 2005 Aug 24. PubMed 16120764 ↗
  • Jessor R, Jessor S. Problem behavior and psychosocial development: A longitudinal study of youth. New York: Academic Press; 1977.
  • Raffaelli M, Crockett LJ. Sexual risk taking in adolescence: the role of self-regulation and attraction to risk. Dev Psychol. 2003 Nov;39(6):1036-46. doi: 10.1037/0012-1649.39.6.1036. PubMed 14584983 ↗
  • DiClemente RJ, Wingood GM, Crosby RA, Sionean C, Brown LK, Rothbaum B, Zimand E, Cobb BK, Harrington K, Davies S. A prospective study of psychological distress and sexual risk behavior among black adolescent females. Pediatrics. 2001 Nov;108(5):E85. doi: 10.1542/peds.108.5.e85. PubMed 11694669 ↗
  • Brown LK, Tolou-Shams M, Lescano C, Houck C, Zeidman J, Pugatch D, Lourie KJ; Project SHIELD Study Group. Depressive symptoms as a predictor of sexual risk among African American adolescents and young adults. J Adolesc Health. 2006 Sep;39(3):444.e1-8. doi: 10.1016/j.jadohealth.2006.01.015. Epub 2006 Jul 10. PubMed 16919811 ↗
  • Robin L, Dittus P, Whitaker D, Crosby R, Ethier K, Mezoff J, Miller K, Pappas-Deluca K. Behavioral interventions to reduce incidence of HIV, STD, and pregnancy among adolescents: a decade in review. J Adolesc Health. 2004 Jan;34(1):3-26. doi: 10.1016/s1054-139x(03)00244-1. PubMed 14706401 ↗
  • Martin S, Oppenheim K. Video gaming: General and pathological use. Trends & Tudes. 2008; 6(1):1-6.
  • Stanton B. Adolescent human immunodeficiency virus prevention: what we have accomplished and what still needs to be done. Arch Pediatr Adolesc Med. 2009 Dec;163(12):1162-3. doi: 10.1001/archpediatrics.2009.226. No abstract available. PubMed 19996056 ↗
  • Lyles CM, Kay LS, Crepaz N, Herbst JH, Passin WF, Kim AS, Rama SM, Thadiparthi S, DeLuca JB, Mullins MM; HIV/AIDS Prevention Research Synthesis Team. Best-evidence interventions: findings from a systematic review of HIV behavioral interventions for US populations at high risk, 2000-2004. Am J Public Health. 2007 Jan;97(1):133-43. doi: 10.2105/AJPH.2005.076182. Epub 2006 Nov 30. PubMed 17138920 ↗
  • Sales JM, Milhausen RR, Diclemente RJ. A decade in review: building on the experiences of past adolescent STI/HIV interventions to optimise future prevention efforts. Sex Transm Infect. 2006 Dec;82(6):431-6. doi: 10.1136/sti.2005.018002. PubMed 17151029 ↗
  • Kim N, Stanton B, Li X, Dickersin K, Galbraith J. Effectiveness of the 40 adolescent AIDS-risk reduction interventions: a quantitative review. J Adolesc Health. 1997 Mar;20(3):204-15. doi: 10.1016/S1054-139X(96)00169-3. PubMed 9069021 ↗
  • Romero LM, Galbraith JS, Wilson-Williams L, Gloppen KM. HIV prevention among African American youth: how well have evidence-based interventions addressed key theoretical constructs? AIDS Behav. 2011 Jul;15(5):976-91. doi: 10.1007/s10461-010-9745-5. PubMed 20635131 ↗
  • Kirby D, Short L, Collins J, Rugg D, Kolbe L, Howard M, Miller B, Sonenstein F, Zabin LS. School-based programs to reduce sexual risk behaviors: a review of effectiveness. Public Health Rep. 1994 May-Jun;109(3):339-60. PubMed 8190857 ↗
  • Walter HJ, Vaughan RD. AIDS risk reduction among a multiethnic sample of urban high school students. JAMA. 1993 Aug 11;270(6):725-30. PubMed 8336374 ↗
  • St. Lawrence S, Crosby A, Belcher L, et al. Sexual risk reduction and anger management interventions for incarcerated male adolescents: A randomized controlled trial of two interventions. Journal of Sex Education and Therapy. 1999; 24(1&2): 9-17.
  • Rotheram-Borus MJ, Koopman C, Haignere C, Davies M. Reducing HIV sexual risk behaviors among runaway adolescents. JAMA. 1991 Sep 4;266(9):1237-41. PubMed 1870249 ↗
  • Rotheram-Borus MJ, Song J, Gwadz M, Lee M, Van Rossem R, Koopman C. Reductions in HIV risk among runaway youth. Prev Sci. 2003 Sep;4(3):173-87. doi: 10.1023/a:1024697706033. PubMed 12940468 ↗
  • Slesnick N, Kang MJ. The impact of an integrated treatment on HIV risk behavior among homeless youth: a randomized controlled trial. J Behav Med. 2008 Feb;31(1):45-59. doi: 10.1007/s10865-007-9132-5. Epub 2007 Oct 17. PubMed 17940861 ↗
  • Rew L, Fouladi RT, Land L, Wong YJ. Outcomes of a brief sexual health intervention for homeless youth. J Health Psychol. 2007 Sep;12(5):818-32. doi: 10.1177/1359105307080617. PubMed 17855465 ↗
  • Brown LK, Danovsky MB, Lourie KJ, DiClemente RJ, Ponton LE. Adolescents with psychiatric disorders and the risk of HIV. J Am Acad Child Adolesc Psychiatry. 1997 Nov;36(11):1609-17. doi: 10.1016/S0890-8567(09)66573-4. PubMed 9394948 ↗
  • Brown LK, Houck CD, Hadley WS, Lescano CM. Self-cutting and sexual risk among adolescents in intensive psychiatric treatment. Psychiatr Serv. 2005 Feb;56(2):216-8. doi: 10.1176/appi.ps.56.2.216. PubMed 15703353 ↗
  • Brown LK, Houck CD, Grossman CI, Lescano CM, Frenkel JL. Frequency of adolescent self-cutting as a predictor of HIV risk. J Dev Behav Pediatr. 2008 Jun;29(3):161-5. doi: 10.1097/DBP.0b013e318173a587. PubMed 18520618 ↗
  • Walkup J, Blank MB, Gonzalez JS, Safren S, Schwartz R, Brown L, Wilson I, Knowlton A, Lombard F, Grossman C, Lyda K, Schumacher JE. The impact of mental health and substance abuse factors on HIV prevention and treatment. J Acquir Immune Defic Syndr. 2008 Mar 1;47 Suppl 1:S15-9. doi: 10.1097/QAI.0b013e3181605b26. PubMed 18301129 ↗
  • Brown LK, Hadley W, Stewart A, Lescano C, Whiteley L, Donenberg G, DiClemente R; Project STYLE Study Group. Psychiatric disorders and sexual risk among adolescents in mental health treatment. J Consult Clin Psychol. 2010 Aug;78(4):590-7. doi: 10.1037/a0019632. PubMed 20658815 ↗
  • Tolou-Shams M, Brown LK, Houck C, Lescano CM; Project SHIELD Study Group. The association between depressive symptoms, substance use, and HIV risk among youth with an arrest history. J Stud Alcohol Drugs. 2008 Jan;69(1):58-64. doi: 10.15288/jsad.2008.69.58. PubMed 18080065 ↗
  • Lang DL, Sales JM, Salazar LF, DiClemente RJ, Crosby RA, Brown LK, Donenberg GR. Determinants of multimethod contraceptive use in a sample of adolescent women diagnosed with psychological disorders. Infect Dis Obstet Gynecol. 2011;2011:510239. doi: 10.1155/2011/510239. Epub 2011 Sep 29. PubMed 21969802 ↗
  • Donenberg GR, Emerson E, Bryant FB, Wilson H, Weber-Shifrin E. Understanding AIDS-risk behavior among adolescents in psychiatric care: links to psychopathology and peer relationships. J Am Acad Child Adolesc Psychiatry. 2001 Jun;40(6):642-53. doi: 10.1097/00004583-200106000-00008. PubMed 11392341 ↗
  • Nugent NR, Brown LK, Belzer M, Harper GW, Nachman S, Naar-King S; Adolescent Trials Network for HIV/AIDS Interventions. Youth living with HIV and problem substance use: elevated distress is associated with nonadherence and sexual risk. J Int Assoc Physicians AIDS Care (Chic). 2010 Mar-Apr;9(2):113-5. doi: 10.1177/1545109709357472. Epub 2010 Feb 4. PubMed 20133498 ↗
  • King M, Semlyen J, Tai SS, Killaspy H, Osborn D, Popelyuk D, Nazareth I. A systematic review of mental disorder, suicide, and deliberate self harm in lesbian, gay and bisexual people. BMC Psychiatry. 2008 Aug 18;8:70. doi: 10.1186/1471-244X-8-70. PubMed 18706118 ↗
  • Mustanski BS, Garofalo R, Emerson EM. Mental health disorders, psychological distress, and suicidality in a diverse sample of lesbian, gay, bisexual, and transgender youths. Am J Public Health. 2010 Dec;100(12):2426-32. doi: 10.2105/AJPH.2009.178319. Epub 2010 Oct 21. PubMed 20966378 ↗
  • Liu RT, Mustanski B. Suicidal ideation and self-harm in lesbian, gay, bisexual, and transgender youth. Am J Prev Med. 2012 Mar;42(3):221-8. doi: 10.1016/j.amepre.2011.10.023. PubMed 22341158 ↗
  • Brown LK, Kessel SM, Lourie KJ, Ford HH, Lipsitt LP. Influence of sexual abuse on HIV-related attitudes and behaviors in adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry. 1997 Mar;36(3):316-22. doi: 10.1097/00004583-199703000-00009. PubMed 9055511 ↗
  • Brown LK, Lourie KJ, Zlotnick C, Cohn J. Impact of sexual abuse on the HIV-risk-related behavior of adolescents in intensive psychiatric treatment. Am J Psychiatry. 2000 Sep;157(9):1413-5. doi: 10.1176/appi.ajp.157.9.1413. PubMed 10964856 ↗
  • Houck CD, Nugent NR, Lescano CM, Peters A, Brown LK. Sexual abuse and sexual risk behavior: beyond the impact of psychiatric problems. J Pediatr Psychol. 2010 Jun;35(5):473-83. doi: 10.1093/jpepsy/jsp111. Epub 2009 Dec 4. PubMed 19966316 ↗
  • Brown LK, Houck C, Lescano C, Donenberg G, Tolou-Shams M, Mello J. Affect regulation and HIV risk among youth in therapeutic schools. AIDS Behav. 2012 Nov;16(8):2272-8. doi: 10.1007/s10461-012-0220-3. PubMed 22669595 ↗
  • Slovic P, Peters E, Finucane ML, Macgregor DG. Affect, risk, and decision making. Health Psychol. 2005 Jul;24(4S):S35-40. doi: 10.1037/0278-6133.24.4.S35. PubMed 16045417 ↗
  • Slovic P. Perception of risk. Science. 1987 Apr 17;236(4799):280-5. doi: 10.1126/science.3563507. PubMed 3563507 ↗
  • Bell CC, McBride DF. Affect regulation and prevention of risky behaviors. JAMA. 2010 Aug 4;304(5):565-6. doi: 10.1001/jama.2010.1058. No abstract available. PubMed 20682937 ↗
  • Tice DM, Bratslavsky E, Baumeister RF. Emotional distress regulation takes precedence over impulse control: if you feel bad, do it! J Pers Soc Psychol. 2001 Jan;80(1):53-67. PubMed 11195891 ↗
  • Cole PM, Michel MK, Teti LO. The development of emotion regulation and dysregulation: a clinical perspective. Monogr Soc Res Child Dev. 1994;59(2-3):73-100. PubMed 7984169 ↗
  • Lescano CM, Brown LK, Miller PM, Puster KL. Unsafe sex: do feelings matter? J Prev Interv Community. 2007;33(1-2):51-62. doi: 10.1300/J005v33n01_05. PubMed 17298930 ↗
  • Ickovics JR, Meade CS, Kershaw TS, Milan S, Lewis JB, Ethier KA. Urban teens: Trauma, posttraumatic growth, and emotional distress among female adolescents. J Consult Clin Psychol. 2006 Oct;74(5):841-50. doi: 10.1037/0022-006X.74.5.841. PubMed 17032088 ↗
  • Linehan MM. Skills training manual for treating borderline personality disorder. New York, NY: Guilford Press; 1993.
  • Beck J. Cognitive Therapy: Basics and Beyond. New York, N.Y: Guilford; 1995.
  • Waldron HB, Kaminer Y. On the learning curve: the emerging evidence supporting cognitive-behavioral therapies for adolescent substance abuse. Addiction. 2004 Nov;99 Suppl 2(Suppl 2):93-105. doi: 10.1111/j.1360-0443.2004.00857.x. PubMed 15488108 ↗
  • Wilson D, Bouffard L, MacKenzie D. A quantitative review of structured, group-oriented, cognitive-behavioral programs for offenders. Journal of Criminal Justice and Behavior. 2005; 32(2):172-204.
  • Card JJ, Kuhn T, Solomon J, Benner TA, Wingood GM, DiClemente RJ. Translating an effective group-based HIV prevention program to a program delivered primarily by a computer: methods and outcomes. AIDS Educ Prev. 2011 Apr;23(2):159-74. doi: 10.1521/aeap.2011.23.2.159. PubMed 21517664 ↗
  • Wingood GM, Card JJ, Er D, Solomon J, Braxton N, Lang D, Seth P, Cartreine J, Diclemente RJ. Preliminary efficacy of a computer-based HIV intervention for African-American women. Psychol Health. 2011 Feb;26(2):223-34. doi: 10.1080/08870446.2011.531576. PubMed 21318931 ↗
  • Downs JS, Murray PJ, Bruine de Bruin W, Penrose J, Palmgren C, Fischhoff B. Interactive video behavioral intervention to reduce adolescent females' STD risk: a randomized controlled trial. Soc Sci Med. 2004 Oct;59(8):1561-72. doi: 10.1016/j.socscimed.2004.01.032. PubMed 15279915 ↗
  • Noar SM, Black HG, Pierce LB. Efficacy of computer technology-based HIV prevention interventions: a meta-analysis. AIDS. 2009 Jan 2;23(1):107-15. doi: 10.1097/QAD.0b013e32831c5500. PubMed 19050392 ↗
  • Ito KE, Kalyanaraman S, Ford CA, Brown JD, Miller WC. "Let's Talk About Sex": pilot study of an interactive CD-ROM to prevent HIV/STIS in female adolescents. AIDS Educ Prev. 2008 Feb;20(1):78-89. doi: 10.1521/aeap.2008.20.1.78. PubMed 18312069 ↗
  • Noar SM. Behavioral interventions to reduce HIV-related sexual risk behavior: review and synthesis of meta-analytic evidence. AIDS Behav. 2008 May;12(3):335-53. doi: 10.1007/s10461-007-9313-9. Epub 2007 Sep 21. PubMed 17896176 ↗
  • Swendeman D, Rotheram-Borus MJ. Innovation in sexually transmitted disease and HIV prevention: internet and mobile phone delivery vehicles for global diffusion. Curr Opin Psychiatry. 2010 Mar;23(2):139-44. doi: 10.1097/YCO.0b013e328336656a. PubMed 20087189 ↗
  • Tortolero SR, Markham CM, Peskin MF, Shegog R, Addy RC, Escobar-Chaves SL, Baumler ER. It's Your Game: Keep It Real: delaying sexual behavior with an effective middle school program. J Adolesc Health. 2010 Feb;46(2):169-79. doi: 10.1016/j.jadohealth.2009.06.008. Epub 2009 Aug 18. PubMed 20113923 ↗
  • Klein CH, Card JJ. Preliminary efficacy of a computer-delivered HIV prevention intervention for African American teenage females. AIDS Educ Prev. 2011 Dec;23(6):564-76. doi: 10.1521/aeap.2011.23.6.564. PubMed 22201239 ↗
  • Weinhardt LS, Mosack KE, Swain GR. Development of a computer-based risk-reduction counseling intervention: acceptability and preferences among low-income patients at an urban sexually transmitted infection clinic. AIDS Behav. 2007 Jul;11(4):549-56. doi: 10.1007/s10461-006-9163-x. Epub 2006 Sep 22. PubMed 17028993 ↗
  • Bell SG, Newcomer SF, Bachrach C, Borawski E, Jemmott JB 3rd, Morrison D, Stanton B, Tortolero S, Zimmerman R. Challenges in replicating interventions. J Adolesc Health. 2007 Jun;40(6):514-20. doi: 10.1016/j.jadohealth.2006.09.005. Epub 2006 Nov 29. PubMed 17531757 ↗
  • Norton WE, Amico KR, Cornman DH, Fisher WA, Fisher JD. An agenda for advancing the science of implementation of evidence-based HIV prevention interventions. AIDS Behav. 2009 Jun;13(3):424-9. doi: 10.1007/s10461-009-9556-8. Epub 2009 Apr 10. PubMed 19360464 ↗
  • Rotheram-Borus MJ, Swendeman D, Chovnick G. The past, present, and future of HIV prevention: integrating behavioral, biomedical, and structural intervention strategies for the next generation of HIV prevention. Annu Rev Clin Psychol. 2009;5:143-67. doi: 10.1146/annurev.clinpsy.032408.153530. PubMed 19327028 ↗
  • Fotheringham MJ, Wonnacott RL, Owen N. Computer use and physical inactivity in young adults: public health perils and potentials of new information technologies. Ann Behav Med. 2000 Fall;22(4):269-75. doi: 10.1007/BF02895662. PubMed 11253437 ↗
  • Padian NS, Buve A, Balkus J, Serwadda D, Cates W Jr. Biomedical interventions to prevent HIV infection: evidence, challenges, and way forward. Lancet. 2008 Aug 16;372(9638):585-99. doi: 10.1016/S0140-6736(08)60885-5. Epub 2008 Aug 5. PubMed 18687456 ↗
  • Grant RM, Lama JR, Anderson PL, McMahan V, Liu AY, Vargas L, Goicochea P, Casapia M, Guanira-Carranza JV, Ramirez-Cardich ME, Montoya-Herrera O, Fernandez T, Veloso VG, Buchbinder SP, Chariyalertsak S, Schechter M, Bekker LG, Mayer KH, Kallas EG, Amico KR, Mulligan K, Bushman LR, Hance RJ, Ganoza C, Defechereux P, Postle B, Wang F, McConnell JJ, Zheng JH, Lee J, Rooney JF, Jaffe HS, Martinez AI, Burns DN, Glidden DV; iPrEx Study Team. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010 Dec 30;363(27):2587-99. doi: 10.1056/NEJMoa1011205. Epub 2010 Nov 23. PubMed 21091279 ↗
  • Koblin BA, Mansergh G, Frye V, Tieu HV, Hoover DR, Bonner S, Flores SA, Hudson SM, Colfax GN; Project MIX Study Team. Condom-use decision making in the context of hypothetical pre-exposure prophylaxis efficacy among substance-using men who have sex with men: Project MIX. J Acquir Immune Defic Syndr. 2011 Nov 1;58(3):319-27. doi: 10.1097/QAI.0b013e31822b76d2. PubMed 21765363 ↗
  • Buchbinder SP, Liu A. Pre-exposure prophylaxis and the promise of combination prevention approaches. AIDS Behav. 2011 Apr;15 Suppl 1(Suppl 1):S72-9. doi: 10.1007/s10461-011-9894-1. PubMed 21331801 ↗
  • Underhill K, Operario D, Mimiaga MJ, Skeer MR, Mayer KH. Implementation science of pre-exposure prophylaxis: preparing for public use. Curr HIV/AIDS Rep. 2010 Nov;7(4):210-9. doi: 10.1007/s11904-010-0062-4. PubMed 20820971 ↗
  • Brown LK, Reynolds LA, Lourie KJ. A pilot HIV prevention program for adolescents in a psychiatric hospital. Psychiatr Serv. 1997 Apr;48(4):531-3. doi: 10.1176/ps.48.4.531. PubMed 9090740 ↗
  • Krueger R, Casey M. Focus groups: A Practical Guide for Applied Research (3rd edition.) Thousand Oaks, CA: Sage; 2000.
  • Harper G, Contreras R, Bangi A, Pedraza A. Collaborative process evaluation: Enhancing community relevance and cultural appropriateness in HIV prevention. Journal of Prevention and Intervention in the Community. 2003; 26(2):53-71.
  • Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: development of a general scale. Eval Program Plann. 1979;2(3):197-207. doi: 10.1016/0149-7189(79)90094-6. No abstract available. PubMed 10245370 ↗
  • Brown L, Hadley W, Donenberg G, DiClemente R, Lescano C, et al. A multisite HIV prevention trial for youth in mental health treatment. Poster presented at the International AIDS Society Conference; 2012 July 22-27; Washington, DC.
  • Brown LK, DiClemente RJ, Beausoleil NI. Comparison of human immunodeficiency virus related knowledge, attitudes, intentions, and behaviors among sexually active and abstinent young adolescents. J Adolesc Health. 1992 Mar;13(2):140-5. doi: 10.1016/1054-139x(92)90081-l. PubMed 1627582 ↗
  • Brown LK, Fritz GK. Children's knowledge and attitudes about AIDS. J Am Acad Child Adolesc Psychiatry. 1988 Jul;27(4):504-8. doi: 10.1097/00004583-198807000-00022. No abstract available. PubMed 3182608 ↗
  • Brown LK, Schultz JR, Parsons JT, Butler RB, Forsberg AD, Kocik SM, King G, Manco-Johnson M, Aledort L. Sexual behavior change among human immunodeficiency virus-infected adolescents with hemophilia. Adolescent Hemophilia Behavioral Intervention Evaluation Project Study Group. Pediatrics. 2000 Aug;106(2):E22. doi: 10.1542/peds.106.2.e22. PubMed 10920178 ↗
  • Prochaska JO, Redding CA, Harlow LL, Rossi JS, Velicer WF. The transtheoretical model of change and HIV prevention: a review. Health Educ Q. 1994 Winter;21(4):471-86. doi: 10.1177/109019819402100410. PubMed 7843978 ↗
  • Bernstein D, Fink L. Manual for the Childhood Trauma Questionnaire: A retrospective selfreport. San Antonio, TX: The Psychological Corporation; 1998.
  • Derogatis L, Spencer M. The Brief Symptom Inventory (BSI): Administration, scoring, and procedures manual-1. Baltimore, MD: Johns Hopkins University School of Medicine, Clinical Psychometrics Research Unit; 1982.
  • Miles M, Huberman A. Qualitative Data Analysis. Thousand Oaks, CA: Sage Publications; 1994.
  • Molenberghs G, Thijs H, Jansen I, Beunckens C, Kenward MG, Mallinckrodt C, Carroll RJ. Analyzing incomplete longitudinal clinical trial data. Biostatistics. 2004 Jul;5(3):445-64. doi: 10.1093/biostatistics/5.3.445. PubMed 15208205 ↗
  • Liang L, Zeger S. Longitudinal data analysis using generalized linear models. Biometrika. 1986; 73:13-22.
  • Raudenbush S, et al. Optimal Design Software for Multi-level and Longitudinal Research (Version 3.01) [Software]. www.wtgrantfoundation.org, 2011.
  • Anthony K, Nagel DM, Goss S. The Use of Technology in Mental Health: Applications ethics and practice. Sringfield, IL: Charles Thomas; 2010.
  • Luxton DD, McCann RA, Bush NE, Mishkind MC, Reger GM. mHealth for mental health: Integrating smartphone technology in behavioral healthcare. Professional Psychology: Research and Practice. 2011; 42(6):505-512.
  • Boschen M. Mobile Telephones and Psychotherapy: I: Capability and Applicability. The Behavior Therapist. 2009; 32(8):168-175.
  • Boschen, M. Mobile Telephones and Psychotherapy: II: A Review of the Empirical Research. The Behavior Therapist. 2009; 32(8):175-182.
  • Bang M, Timpka T, Eriksson H, Holm E, Nordin C. Mobile phone computing for in-situ cognitive behavioral therapy. Stud Health Technol Inform. 2007;129(Pt 2):1078-82. PubMed 17911881 ↗
  • CDC. HIV Prevention: Progress to date. 2013. Accessed from:https://www.cdc.gov/nchhstp/newsroom/docs/factsheets/progress-508.pdf

Study documents

  • Protocol and statistical analysis plan · Apr 16, 2019

Documents are hosted by the registry — open the source record to download them.

10

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jan 27, 2020, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
11

Registry details

Key details

Study ID
NCT02921841
Lead sponsor
Rhode Island Hospital
Collaborators
Virtually Better, Inc.
Responsible party
Dr. Larry K. Brown (Director of Research, Rhode Island Hospital) — Principal investigator
First posted
Oct 3, 2016
Start date
Nov 2016
Primary completion
Mar 2019
Completion
Jul 2019
Results posted
Jan 27, 2020
Last update
Jan 27, 2020

Study contacts

Margo Adams Larsen, PhD
principal investigator · Virtually Better, Inc.

Oversight

Data monitoring committee
Yes
View the source record on ClinicalTrials.gov ↗

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