Come As You Are - Assessing the Efficacy of a Nurse Case Management HIV Prevention and Care Intervention Among Homeless Youth

NCT03910218 | Completed Results DMC

• 1 other identifier: HSC-SN-18-0993
• Study Type: interventional
• Target: 474
• Locations: 1 country
• Sites: 1

Brief Summary

The purpose of this study is to to determine the efficacy of the Nurse Case Management HIV (NCM4HIV) intervention on HIV prevention compared to usual care among Youth Experiencing Homelessness (YEH).

Conditions

Behavior, Risk

Keywords

HIV prevention; homeless

Outcome Measures

Primary Outcomes (20)

• Number of Participants Who Use Preventive Prophylaxis (PrEP)

  baseline

• Number of Participants Who Use Preventive Prophylaxis (PrEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  At completion of the 3-month intervention (Month 3)

• Number of Participants Who Use Preventive Prophylaxis (PrEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  3 months after intervention (Month 6)

• Number of Participants Who Use Preventive Prophylaxis (PrEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  6 months after intervention (Month 9)

• Number of Participants Who Use Preventive Prophylaxis (PrEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  9 months after intervention (Month 12)

• Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)

  baseline

• Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  At completion of the 3-month intervention (Month 3)

• Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  3 months after intervention (Month 6)

• Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  6 months after intervention (Month 9)

• Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)

  Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  9 months after intervention (Month 12)

• Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey

  An item from the Youth Risk Behavior Survey was used to assess this outcome. The items asked if a condom was used at last sex. The number of participants who answered yes is reported.

  baseline

• Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey

  An item from the Youth Risk Behavior Survey was used to assess this outcome. The items asked if a condom was used at last sex. The number of participants who answered yes is reported.\\ Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  At completion of the 3-month intervention (Month 3)

• Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey

  An item from the Youth Risk Behavior Survey was used to assess this outcome. The items asked if a condom was used at last sex. The number of participants who answered yes is reported. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  3 months after intervention (Month 6)

• Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey

  An item from the Youth Risk Behavior Survey was used to assess this outcome. The items asked if a condom was used at last sex. The number of participants who answered yes is reported. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  6 months after intervention (Month 9)

• Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey

  An item from the Youth Risk Behavior Survey was used to assess this outcome. The items asked if a condom was used at last sex. The number of participants who answered yes is reported. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  9 months after intervention (Month 12)

• Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)

  Sexually Transmitted Infection tested includes syphilis, chlamydia and gonorrhea.

  Baseline

• Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)

  Sexually Transmitted Infection tested includes syphilis, chlamydia and gonorrhea. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  At completion of the 3-month intervention (Month 3)

• Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)

  Sexually Transmitted Infection tested includes syphilis, chlamydia and gonorrhea. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  3 months after intervention (Month 6)

• Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)

  Sexually Transmitted Infection tested includes syphilis, chlamydia and gonorrhea. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  6 months after intervention (Month 9)

• Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)

  Sexually Transmitted Infection tested includes syphilis, chlamydia and gonorrhea. Multiple imputation was used because there were high missing fractions for many variables. This approach assumed that data were missing at random (MAR) and the imputation model used the same multilevel modeling approach that was used for analysis. The models made use of the correlations among repeated measurements for participants to estimate missing values. The descriptive statistics represent averages across 10 imputed data sets.

  9 months after intervention (Month 12)

Secondary Outcomes (17)

• Mental Health as Measured by the Brief Symptom Index-18

  baseline

• Mental Health as Measured by the Brief Symptom Index-18

  At completion of the 3-month intervention (Month 3)

• Mental Health as Measured by the Brief Symptom Index-18

  3 months after intervention (Month 6)

• Mental Health as Measured by the Brief Symptom Index-18

  6 months after intervention (Month 9)

• Mental Health as Measured by the Brief Symptom Index-18

  9 months after intervention (Month 12)

Study Arms (2)

NCM4HIV

EXPERIMENTAL

Participant will receive NCM4HIV intervention which includes Personalized HIV prevention education, behavior goal-setting,behavioral self-monitoring,Pre exposure prophylaxis (PrEP) eligibility screening,PrEP/non occupational post exposure prophylaxis(nPEP)services (labs, medication), healthcare planning/coordination, Motivational Interviewing (MI) counseling approach, assisting with cognitive appraisals (clarifying misconceptions),promoting health seeking and coping behaviors that incorporate the situational, personal, social, and resource needs affecting health

Behavioral: NCM4HIV

Usual care

PLACEBO COMPARATOR

Participants will receive the usual care which includes Housing, food, and clothing needs,health assessment, basic healthcare, limited anticipatory guidance, mental health counseling,substance use treatment referrals,PrEP/nPEP referrals

Behavioral: Usual Care

Interventions

NCM4HIV BEHAVIORAL

Participant will receive NCM4HIV intervention which includes Personalized HIV prevention education, behavior goal-setting,behavioral self-monitoring, PrEP eligibility screening,PrEP/nPEP services (labs, medication), healthcare planning/coordination, MI counseling approach, assisting with cognitive appraisals (clarifying misconceptions),promoting health seeking and coping behaviors that incorporate the situational, personal, social, and resource needs affecting health

NCM4HIV

Usual Care BEHAVIORAL

Participant will receive usual care which includes Housing, food, and clothing needs,health assessment, basic healthcare, limited anticipatory guidance, mental health counseling, substance use treatment referrals, PrEP/nPEP referrals

Usual care

Eligibility Criteria

• Age: 16 Years - 25 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64)

You may qualify if:

• youth engaged in high-risk sexual activity or intravenous drug use
• speak English
• homeless
• not planning to move out of the metro area during the study

You may not qualify if:

• youth with very low literacy
• severe acute mental symptoms

Sponsors & Collaborators

• The University of Texas Health Science Center, Houston: lead
• National Institute of Nursing Research (NINR): collaborator

Study Sites (1)

The University of Texas Health Science Center at Houston

Houston, Texas, 77030, United States

Location

Related Publications (2)

• Maria DS, Nyamathi A, Lightfoot M, Paul M, Quadri Y, Padhye N, Businelle M, Fernandez-Sanchez H, Jones JT. Results of a Randomized Wait-List Controlled Trial of CAYA: A Nurse Case Management HIV Prevention Intervention for Youth Experiencing Homelessness. AIDS Behav. 2025 Feb;29(2):613-625. doi: 10.1007/s10461-024-04544-3. Epub 2024 Nov 12.

  PMID: 39531116 DERIVED

• Santa Maria DM, Padhye N, Ostrosky-Zeichner L, Grimes CZ, Nyamathi A, Lightfoot M, Quadri Y, Paul ME, Jones JT. COVID-19 Vaccination Uptake, Infection Rates, and Seropositivity Among Youth Experiencing Homelessness in the United States. Nurs Res. 2024 Sep-Oct 01;73(5):373-380. doi: 10.1097/NNR.0000000000000747. Epub 2024 May 10.

  PMID: 38809559 DERIVED

MeSH Terms

Conditions

Risk-Taking

Condition Hierarchy (Ancestors)

Behavior

Results Point of Contact

• Title: Diane Santa Maria, DrPH
• Organization: The University of Texas Health Science Center at Houston

diane.m.santamaria@uth.tmc.edu

713-500-2187

Study Officials

• Diane Santa Maria, DrPH

  The University of Texas Health Science Center, Houston

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: INVESTIGATOR
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: April 8, 2019
• First Posted: April 10, 2019
• Study Start: November 11, 2019
• Primary Completion: April 3, 2024
• Study Completion: April 3, 2024
• Last Updated: June 26, 2025
• Results First Posted: June 26, 2025

Record last verified: 2025-06

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)