Behavior, RiskNCT03910218
Come As You Are - Assessing the Efficacy of a Nurse Case Management HIV Prevention and Care Intervention Among Homeless Youth
A study testing NCM4HIV in people with Behavior, Risk, run by The University of Texas Health Science Center, Houston at 1 site in United States.
Trial 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). Read more about this study
- Who is it for?
- Ages 16 to 25 years
- Conditions the study is for
- Behavior, Risk
- What is being tested?
- NCM4HIV
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 474 participants
- Where
- 1 siteUnited States
- Study dates
- 11 Nov 2019to 3 Apr 2024
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 16 to 25 years
- All sexes
- No healthy volunteers
- Child, Adult
Who may be able to join
- 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
Who cannot join
- youth with very low literacy
- severe acute mental symptoms
Trial locations and contacts
1 site in 1 country.
United States1 site
The University of Texas Health Science Center at Houston
Houston, Texas, 77030
About this study
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
- Being tested
- NCM4HIV, Usual Care
- Keywords
- HIV prevention, homeless
- Medical subject headings
- Risk-Taking
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
NCM4HIVBehavioural
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
Usual CareBehavioural
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
| Study group | Role | What they receive |
|---|---|---|
| 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 Receives: 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 Receives: Behavioral: Usual Care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of Participants Who Use Preventive Prophylaxis (PrEP)
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 9 months after intervention (Month 12)
Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 9 months after intervention (Month 12)
Secondary outcomes (17)
Mental Health as Measured by the Brief Symptom Index-18
The Brief Symptom Inventory 18 (BSI-18) consists of 18 items on a 5-point (0-4) Likert scale and is designed to assess current psychological distress (over the past 7 days). Total score ranges from 0 to 72, with higher scores indicating greater distress.
Measured: baseline
Mental Health as Measured by the Brief Symptom Index-18
The BSI-18 consists of 18 items on a 5-point (0-4) Likert scale and is designed to assess current psychological distress (over the past 7 days). Total score ranges from 0 to 72, with higher scores indicating greater distress.
Measured: At completion of the 3-month intervention (Month 3)
Mental Health as Measured by the Brief Symptom Index-18
The BSI-18 consists of 18 items on a 5-point (0-4) Likert scale and is designed to assess current psychological distress (over the past 7 days). Total score ranges from 0 to 72, with higher scores indicating greater distress.
Measured: 3 months after intervention (Month 6)
Mental Health as Measured by the Brief Symptom Index-18
The BSI-18 consists of 18 items on a 5-point (0-4) Likert scale and is designed to assess current psychological distress (over the past 7 days). Total score ranges from 0 to 72, with higher scores indicating greater distress.
Measured: 6 months after intervention (Month 9)
Mental Health as Measured by the Brief Symptom Index-18
The BSI-18 consists of 18 items on a 5-point (0-4) Likert scale and is designed to assess current psychological distress (over the past 7 days). Total score ranges from 0 to 72, with higher scores indicating greater distress.
Measured: 9 months after intervention (Month 12)
Housing Status
Participants will be asked if they live in a shelter, apartment/house, with someone, outside, or in a car, etc.
Measured: baseline
Housing Status
Participants will be asked if they live in a shelter, apartment/house, with someone, outside, or in a car, etc.
Measured: At completion of the 3-month intervention (Month 3)
Housing Status
Participants will be asked if they live in a shelter, apartment/house, with someone, outside, or in a car, etc.
Measured: 3 months after intervention (Month 6)
Housing Status
Participants will be asked if they live in a shelter, apartment/house, with someone, outside, or in a car, etc.
Measured: 6 months after intervention (Month 9)
Housing Status
Participants will be asked if they live in a shelter, apartment/house, with someone, outside, or in a car, etc.
Measured: 9 months after intervention (Month 12)
Number of Participants With Substance Use as Measured by Item 11 in the Texas Christian University (TCU) Drug Screen II
An item from the Texas Christian University (TCU) drug screen II was used to assess this outcome. The item listed various drug substances and asked whether any of those listed had been used in the past 30 days. 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.
Measured: At completion of the 3-month intervention (Month 3), 3 months after intervention (Month 6), 6 months after intervention (Month 9), 9 months after intervention (Month 12)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
The Patient Health Questionnaire (PHQ-9) total score ranges from 0 to 27, with higher scores indicating more severe depression
Measured: baseline
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
The Patient Health Questionnaire (PHQ-9) total score ranges from 0 to 27, with higher scores indicating more severe depression.
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.
Measured: At completion of the 3-month intervention (Month 3)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
The Patient Health Questionnaire (PHQ-9) total score ranges from 0 to 27, with higher scores indicating more severe depression.
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.
Measured: 3 months after intervention (Month 6)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
The Patient Health Questionnaire (PHQ-9) total score ranges from 0 to 27, with higher scores indicating more severe depression.
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.
Measured: 6 months after intervention (Month 9)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
The Patient Health Questionnaire (PHQ-9) total score ranges from 0 to 27, with higher scores indicating more severe depression.
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.
Measured: 9 months after intervention (Month 12)
Number of Participants With Substance Use as Measured by Item 11 in the Texas Christian University (TCU) Drug Screen II
An item from the Texas Christian University (TCU) drug screen II was used to assess this outcome. The item listed various drug substances and asked whether any of those listed had been used in the past 30 days. The number of participants who answered yes is reported.
Measured: baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Apr 2019
- Study start11 Nov 2019
- Primary completion3 Apr 2024
- Study completion3 Apr 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Behavior, RiskStudies of the same condition, open and under way.
- More trials run by The University of Texas Health Science Center, HoustonThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Investigator
- Enrolment
- 474 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of Nursing Research (NINR)
- Responsible party
- Principal investigator, Diane Santa Maria, The University of Texas Health Science Center, Houston
- Investigators
- Diane Santa Maria, DrPH, Principal investigator, The University of Texas Health Science Center, Houston
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03910218
- Sponsor's protocol ID
- HSC-SN-18-0993
- Status last verified
- Jun 2025
- First submitted
- 8 Apr 2019
- Last updated
- 26 Jun 2025
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Fernandez-Sanchez H, Jones J, Arandhara U, Padhye N, Nyamathi A, Lightfoot M, Quadri Y, Paul M, Businelle MS, Maria DS. Prevalence and characteristics of sex trafficking among youth experiencing homelessness: A cross-sectional study. PLoS One. 2026 Aug 26;21(8):e0357091. doi: 10.1371/journal.pone.0357091. eCollection 2026.
PubMed 42647548Maria 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.
PubMed 39531116Santa 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.
PubMed 38809559
Study at a glance
From the registry record, last updated by the sponsor on 26 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Come As You Are - Assessing the Efficacy of a Nurse Case Management HIV Prevention and Care Intervention Among Homeless Youth
- ClinicalTrials.gov ID
- NCT03910218
- Acronym / sponsor ID
- HSC-SN-18-0993
- Conditions
- Behavior, Risk
- Keywords
- HIV prevention, homeless
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 474 participants (actual)
- Lead sponsor
- The University of Texas Health Science Center, HoustonUniversity, hospital or other
- Collaborators
- National Institute of Nursing Research (NINR)
- Study start
- 11 Nov 2019 (actual)
- Primary completion
- 3 Apr 2024 (actual)
- Study completion
- 3 Apr 2024 (actual)
- First posted
- 10 Apr 2019 (actual)
- Results
- Posted 26 Jun 2025
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (investigator)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| NCM4HIV | Experimental | Behavioral: NCM4HIVParticipant 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 |
| Usual care | Placebo comparator | Behavioral: Usual CareParticipants 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 |
Who may qualify
- Ages
- 16 to 25 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (2 listed)
- youth with very low literacy
- severe acute mental symptoms
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| NCM4HIVParticipant 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 | Behavioural | NCM4HIV |
| Usual CareParticipant 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 | Behavioural | Usual care |
Primary outcome
Number of Participants Who Use Preventive Prophylaxis (PrEP)
Time frame: baseline
Number of Participants Who Use Preventive Prophylaxis (PrEP)
Time frame: At completion of the 3-month intervention (Month 3)
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.
Number of Participants Who Use Preventive Prophylaxis (PrEP)
Time frame: 3 months after intervention (Month 6)
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.
Number of Participants Who Use Preventive Prophylaxis (PrEP)
Time frame: 6 months after intervention (Month 9)
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.
Number of Participants Who Use Preventive Prophylaxis (PrEP)
Time frame: 9 months after intervention (Month 12)
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.
Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)
Time frame: baseline
Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)
Time frame: At completion of the 3-month intervention (Month 3)
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.
Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)
Time frame: 3 months after intervention (Month 6)
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.
Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)
Time frame: 6 months after intervention (Month 9)
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.
Number of Participants Who Use Non-occupational Post-exposure Prophylaxis (nPEP)
Time frame: 9 months after intervention (Month 12)
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.
Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey
Time frame: baseline
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.
Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey
Time frame: At completion of the 3-month intervention (Month 3)
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.
Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey
Time frame: 3 months after intervention (Month 6)
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.
Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey
Time frame: 6 months after intervention (Month 9)
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.
Number of Participants Who Use Condoms at Last Sex as Measured by the Youth Risk Behavior Survey
Time frame: 9 months after intervention (Month 12)
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.
Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)
Time frame: Baseline
Sexually Transmitted Infection tested includes syphilis, chlamydia and gonorrhea.
Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)
Time frame: At completion of the 3-month intervention (Month 3)
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.
Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)
Time frame: 3 months after intervention (Month 6)
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.
Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)
Time frame: 6 months after intervention (Month 9)
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.
Number of Participants Who Tested Positive for HIV or Sexually Transmitted Infection (STI)
Time frame: 9 months after intervention (Month 12)
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.
17 secondary outcomes
Mental Health as Measured by the Brief Symptom Index-18
Time frame: baseline
Mental Health as Measured by the Brief Symptom Index-18
Time frame: At completion of the 3-month intervention (Month 3)
Mental Health as Measured by the Brief Symptom Index-18
Time frame: 3 months after intervention (Month 6)
Mental Health as Measured by the Brief Symptom Index-18
Time frame: 6 months after intervention (Month 9)
Mental Health as Measured by the Brief Symptom Index-18
Time frame: 9 months after intervention (Month 12)
Housing Status
Time frame: baseline
Housing Status
Time frame: At completion of the 3-month intervention (Month 3)
Housing Status
Time frame: 3 months after intervention (Month 6)
Housing Status
Time frame: 6 months after intervention (Month 9)
Housing Status
Time frame: 9 months after intervention (Month 12)
Number of Participants With Substance Use as Measured by Item 11 in the Texas Christian University (TCU) Drug Screen II
Time frame: At completion of the 3-month intervention (Month 3), 3 months after intervention (Month 6), 6 months after intervention (Month 9), 9 months after intervention (Month 12)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
Time frame: baseline
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
Time frame: At completion of the 3-month intervention (Month 3)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
Time frame: 3 months after intervention (Month 6)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
Time frame: 6 months after intervention (Month 9)
Mental Health as Measured by the Patient Health Questionnaire (PHQ-9)
Time frame: 9 months after intervention (Month 12)
Number of Participants With Substance Use as Measured by Item 11 in the Texas Christian University (TCU) Drug Screen II
Time frame: baseline
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Jun 2025.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Derived from this study: PubMed 42647548Fernandez-Sanchez H, Jones J, Arandhara U, Padhye N, Nyamathi A, Lightfoot M, Quadri Y, Paul M, Businelle MS, Maria DS. Prevalence and characteristics of sex trafficking among youth experiencing homelessness: A cross-sectional study. PLoS One. 2026 Aug 26;21(8):e0357091. doi: 10.1371/journal.pone.0357091. eCollection 2026.
- Derived from this study: PubMed 39531116Maria 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.
- Derived from this study: PubMed 38809559Santa 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Diane Santa Maria, DrPH principal investigator
The University of Texas Health Science Center, Houston
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing NCM4HIV in people with Behavior, Risk, run by The University of Texas Health Science Center, Houston at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 26 Jun 2025). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of Participants Who Use Preventive Prophylaxis (PrEP) (time frame: baseline). The study lists 20 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03910218, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Jun 2025.