Sleep Wake DisordersNCT07894042
AI-Powered Sleep Hygiene Mentor for Adults Living With HIV
A study testing AI-powered sleep hygiene mentor in people with Sleep Wake Disorders and Sleep Initiation and Maintenance Disorders, run by Universitas Indonesia at 1 site in Indonesia.
Trial summary
Poor sleep is common among people living with HIV and is linked to fatigue, psychological distress and poorer adherence to antiretroviral therapy. This study develops a mobile sleep hygiene mentor that uses artificial intelligence to give personalised sleep recommendations, with a dashboard that lets nurses follow… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sleep Wake Disorders, Sleep Initiation and Maintenance Disorders, HIV Infections
- What is being tested?
- AI-powered sleep hygiene mentor
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 100 participants
- Where
- 1 siteIndonesia
- Study dates
- Mar 2027to Dec 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Aged 18 years or older
- HIV diagnosis confirmed by the peer support community or HIV service
- Receiving antiretroviral therapy for at least 6 months and clinically stable
- Poor sleep: Pittsburgh Sleep Quality Index global score above 5 or Insomnia Severity Index score of 8 to 21
- Owns a smartphone with internet access
- Willing to take part in all study steps and provides written informed consent
Who cannot join
- Uncontrolled severe psychiatric illness, such as psychosis or severe depression with high suicide risk
- Sleep disturbance secondary to an acute medical condition, such as severe infection or a severe neurological disorder
- Currently taking part in another sleep or intensive psychological programme
- Unable to use a smartphone
- Physical or cognitive condition that prevents participation
- Insomnia Severity Index score of 22 or more, or signs of sleep apnoea (referred for clinical assessment)
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Indonesia1 site
Faculty of Nursing, Universitas Indonesia
Depok, West Java, 16424
About this study
Official title: AI-Powered Sleep Hygiene Mentor With a Nurse Dashboard to Improve Sleep Quality Among Adults Living With HIV in Indonesia: A Bilateral Strategic Action Research Study
Poor sleep is common among people living with HIV and is linked to fatigue, psychological distress and poorer adherence to antiretroviral therapy. This study develops a mobile sleep hygiene mentor that uses artificial intelligence to give personalised sleep recommendations, with a dashboard that lets nurses follow participants and respond to risks. The mentor is built with adults living with HIV and HIV nurses and then tested for usability and feasibility. In the main evaluation, about 70 adults living with HIV with poor sleep use the mentor daily for four weeks, with two online nurse sessions, and are followed up four weeks later. The study measures sleep quality, insomnia severity, depression, anxiety and stress, fatigue, adherence to antiretroviral therapy, technology acceptance, engagement and safety.
Read the detailed description
The study uses bilateral strategic action research in three plan, act, observe and reflect cycles over about 12 months. In Cycle 1, focus groups with adults living with HIV and interviews with HIV nurses and informatics experts define the requirements of the mentor, a prototype of the mobile mentor and the nurse dashboard is built, and experts validate its content and recommendations. Cycle 1 does not involve use of the mentor by participants. In Cycle 2, about 30 adults living with HIV use the prototype for four weeks with two nurse monitoring sessions, and usability (System Usability Scale), usage logs, system errors and interviews are collected. A joint reflection with the international partner, nurses and community representatives decides on changes, and the version of the mentor (content library, machine learning model and alert rules) is then frozen. In Cycle 3, about 70 adults living with HIV use the frozen version for four weeks (weeks 1 to 4), with nurse monitoring sessions in weeks 2 and 4, and complete questionnaires at baseline and at week 8. The mentor selects recommendations only from an expert-validated library, does not give advice on medicines, and sends alerts to nurses for severe insomnia, possible sleep apnoea, high distress, missed doses and inactivity. Feasibility is judged against prespecified progression criteria for a future randomised controlled trial. About 10 to 15 participants and the nurses are interviewed at follow-up.
- Being tested
- AI-powered sleep hygiene mentor
- Keywords
- sleep hygiene, artificial intelligence, mobile health, nurse dashboard, action research, feasibility study, Indonesia
- Medical subject headings
- Sleep Wake Disorders, Sleep Initiation and Maintenance Disorders, HIV Infections, Sleep Hygiene
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-powered sleep hygiene mentorBehavioural
Also called Sleep Hygiene Mentor, AI sleep mentor
A mobile application with a daily check-in of 5 to 10 minutes on sleep, daily habits, stress and the time antiretroviral medicine was taken. A machine learning model selects one to three recommendations a day from an expert-validated sleep hygiene library and explains why each was chosen. Educational modules cover sleep and HIV, a regular sleep schedule, the sleep environment, caffeine and alcohol, evening screen use, relaxation and worry management, and links between sleep, mood and adherence. Trained nurses monitor participants through a dashboard with rule-based alerts and hold two online sessions of 20 to 30 minutes in weeks 2 and 4. An optional online peer support group may be offered.
| Study group | Role | What they receive |
|---|---|---|
| AI-powered sleep hygiene mentor | Experimental | Four weeks of daily use of the mobile sleep hygiene mentor with nurse oversight through a dashboard and two online nurse monitoring sessions (weeks 2 and 4). Receives: Behavioral: AI-powered sleep hygiene mentor |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in sleep quality
Change from baseline in the Pittsburgh Sleep Quality Index global score. Range 0 to 21; higher scores indicate poorer sleep quality.
Measured: Baseline (week 0) and week 8
Secondary outcomes (15)
Insomnia severity
Insomnia Severity Index total score. Range 0 to 28; higher scores indicate more severe insomnia.
Measured: Weeks 0 and 8
Depression
Depression subscale of the 21-item Depression Anxiety Stress Scales, multiplied by 2. Range 0 to 42; higher scores indicate more depression.
Measured: Weeks 0 and 8
Anxiety
Anxiety subscale of the 21-item Depression Anxiety Stress Scales, multiplied by 2. Range 0 to 42; higher scores indicate more anxiety.
Measured: Weeks 0 and 8
Stress
Stress subscale of the 21-item Depression Anxiety Stress Scales, multiplied by 2. Range 0 to 42; higher scores indicate more stress.
Measured: Weeks 0 and 8
Fatigue
FACIT-Fatigue subscale score. Range 0 to 52; higher scores indicate less fatigue.
Measured: Weeks 0 and 8
Adherence to antiretroviral therapy
Three-item self-report adherence scale for the past 30 days. Range 0 to 100; higher scores indicate better adherence.
Measured: Weeks 0 and 8
Perceived usefulness of the mentor
Mean score of study-specific Technology Acceptance Model items on perceived usefulness, developed and validated in Cycle 1; higher scores indicate greater perceived usefulness.
Measured: Weeks 0 and 8
Perceived ease of use of the mentor
Mean score of study-specific Technology Acceptance Model items on perceived ease of use, developed and validated in Cycle 1; higher scores indicate greater ease of use.
Measured: Weeks 0 and 8
Health beliefs about sleep
Mean score of study-specific Health Belief Model items on sleep, developed and validated in Cycle 1; higher scores indicate stronger beliefs supporting healthy sleep behaviour.
Measured: Weeks 0 and 8
Usability of the mentor
System Usability Scale total score. Range 0 to 100; higher scores indicate better usability.
Measured: Week 4 (Cycle 2) and week 8 (Cycle 3)
Engagement with the mentor
Number of days with a completed daily check-in, from app usage logs.
Measured: Weeks 1 to 4
Recruitment rate
Number of participants enrolled in Cycle 3, expressed as a percentage of the target sample of 70.
Measured: 3 months from the start of Cycle 3 recruitment
Retention to follow-up
Percentage of enrolled Cycle 3 participants who complete the week 8 assessment.
Measured: Week 8
Attendance at nurse monitoring sessions
Percentage of participants who attend at least 1 of the 2 nurse monitoring sessions.
Measured: Weeks 2 and 4
Number of participants with adverse events
Number of participants with at least one adverse event, including events possibly related to the mentor.
Measured: Weeks 0 to 8
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Oct 2026
- Study startMar 2027 (estimated)
- Primary completionNov 2027 (estimated)
- Study completionDec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Sleep Wake DisordersStudies of the same condition, open and under way.
- More trials run by Universitas IndonesiaThe 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
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- Participants in Cycle 2 (pilot, about 30) and Cycle 3 (feasibility evaluation, about 70) use the mentor for four weeks. Cycle 3 participants complete assessments at baseline and at week 8.
- Masking
- None (open label)
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Universitas Indonesia
- Sponsor type
- University, hospital or other
- Collaborators
- Shinawatra University, Indonesian Endowment Fund for Education (LPDP)
- Responsible party
- Sponsor
- Investigators
- Hening Pujasari, PhD, Principal investigator, Universitas Indonesia
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07894042
- Sponsor's protocol ID
- FONUI-KET-60-2026
- Other IDs
- PKS-13/UN2.R3/HKP.05.00/2025
- Status last verified
- Oct 2026
- First submitted
- 18 Oct 2026
- Last updated
- 26 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified individual participant data underlying the published results will be shared.
Study at a glance
From the registry record, last updated by the sponsor on 26 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-Powered Sleep Hygiene Mentor With a Nurse Dashboard to Improve Sleep Quality Among Adults Living With HIV in Indonesia: A Bilateral Strategic Action Research Study
- ClinicalTrials.gov ID
- NCT07894042
- Acronym / sponsor ID
- FONUI-KET-60-2026
- Keywords
- sleep hygiene, artificial intelligence, mobile health, nurse dashboard, action research, feasibility study, Indonesia
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Universitas IndonesiaUniversity, hospital or other
- Collaborators
- Shinawatra University, Indonesian Endowment Fund for Education (LPDP)
- Study start
- Mar 2027 (estimated)
- Primary completion
- Nov 2027 (estimated)
- Study completion
- Dec 2027 (estimated)
- First posted
- 26 Oct 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Poor sleep is common among people living with HIV and is linked to fatigue, psychological distress and poorer adherence to antiretroviral therapy. This study develops a mobile sleep hygiene mentor that uses artificial intelligence to give personalised sleep recommendations, with a dashboard that lets nurses follow participants and respond to risks. The mentor is built with adults living with HIV and HIV nurses and then tested for usability and feasibility. In the main evaluation, about 70 adults living with HIV with poor sleep use the mentor daily for four weeks, with two online nurse sessions, and are followed up four weeks later. The study measures sleep quality, insomnia severity, depression, anxiety and stress, fatigue, adherence to antiretroviral therapy, technology acceptance, engagement and safety.
Detailed description
The study uses bilateral strategic action research in three plan, act, observe and reflect cycles over about 12 months. In Cycle 1, focus groups with adults living with HIV and interviews with HIV nurses and informatics experts define the requirements of the mentor, a prototype of the mobile mentor and the nurse dashboard is built, and experts validate its content and recommendations. Cycle 1 does not involve use of the mentor by participants. In Cycle 2, about 30 adults living with HIV use the prototype for four weeks with two nurse monitoring sessions, and usability (System Usability Scale), usage logs, system errors and interviews are collected. A joint reflection with the international partner, nurses and community representatives decides on changes, and the version of the mentor (content library, machine learning model and alert rules) is then frozen. In Cycle 3, about 70 adults living with HIV use the frozen version for four weeks (weeks 1 to 4), with nurse monitoring sessions in weeks 2 and 4, and complete questionnaires at baseline and at week 8. The mentor selects recommendations only from an expert-validated library, does not give advice on medicines, and sends alerts to nurses for severe insomnia, possible sleep apnoea, high distress, missed doses and inactivity. Feasibility is judged against prespecified progression criteria for a future randomised controlled trial. About 10 to 15 participants and the nurses are interviewed at follow-up.
Study design
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- Participants in Cycle 2 (pilot, about 30) and Cycle 3 (feasibility evaluation, about 70) use the mentor for four weeks. Cycle 3 participants complete assessments at baseline and at week 8.
| Arm | Type | Receives |
|---|---|---|
| AI-powered sleep hygiene mentor | Experimental | Behavioral: AI-powered sleep hygiene mentorFour weeks of daily use of the mobile sleep hygiene mentor with nurse oversight through a dashboard and two online nurse monitoring sessions (weeks 2 and 4). |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Aged 18 years or older
- HIV diagnosis confirmed by the peer support community or HIV service
- Receiving antiretroviral therapy for at least 6 months and clinically stable
- Poor sleep: Pittsburgh Sleep Quality Index global score above 5 or Insomnia Severity Index score of 8 to 21
- Owns a smartphone with internet access
Key exclusion criteria (6 listed)
- Uncontrolled severe psychiatric illness, such as psychosis or severe depression with high suicide risk
- Sleep disturbance secondary to an acute medical condition, such as severe infection or a severe neurological disorder
- Currently taking part in another sleep or intensive psychological programme
- Unable to use a smartphone
- Physical or cognitive condition that prevents participation
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 |
|---|---|---|
| AI-powered sleep hygiene mentorAlso: Sleep Hygiene Mentor, AI sleep mentorA mobile application with a daily check-in of 5 to 10 minutes on sleep, daily habits, stress and the time antiretroviral medicine was taken. A machine learning model selects one to three recommendations a day from an expert-validated sleep hygiene library and explains why each was chosen. Educational modules cover sleep and HIV, a regular sleep schedule, the sleep environment, caffeine and alcohol, evening screen use, relaxation and worry management, and links between sleep, mood and adherence. Trained nurses monitor participants through a dashboard with rule-based alerts and hold two online sessions of 20 to 30 minutes in weeks 2 and 4. An optional online peer support group may be offered. | Behavioural | AI-powered sleep hygiene mentor |
Primary outcome
Change in sleep quality
Time frame: Baseline (week 0) and week 8
Change from baseline in the Pittsburgh Sleep Quality Index global score. Range 0 to 21; higher scores indicate poorer sleep quality.
15 secondary outcomes
Insomnia severity
Time frame: Weeks 0 and 8
Depression
Time frame: Weeks 0 and 8
Anxiety
Time frame: Weeks 0 and 8
Stress
Time frame: Weeks 0 and 8
Fatigue
Time frame: Weeks 0 and 8
Adherence to antiretroviral therapy
Time frame: Weeks 0 and 8
Perceived usefulness of the mentor
Time frame: Weeks 0 and 8
Perceived ease of use of the mentor
Time frame: Weeks 0 and 8
Health beliefs about sleep
Time frame: Weeks 0 and 8
Usability of the mentor
Time frame: Week 4 (Cycle 2) and week 8 (Cycle 3)
Engagement with the mentor
Time frame: Weeks 1 to 4
Recruitment rate
Time frame: 3 months from the start of Cycle 3 recruitment
Retention to follow-up
Time frame: Week 8
Attendance at nurse monitoring sessions
Time frame: Weeks 2 and 4
Number of participants with adverse events
Time frame: Weeks 0 to 8
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Oct 2026.
- Individual participant dataSharing planned: Yes. De-identified individual participant data underlying the published results will be shared.
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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.
Hening Pujasari, PhD principal investigator
Universitas Indonesia
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-powered sleep hygiene mentor in people with Sleep Wake Disorders and Sleep Initiation and Maintenance Disorders, run by Universitas Indonesia at 1 site in Indonesia.
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 6 inclusion and 6 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: opening soon, as of the sponsor's last update on 26 Oct 2026. 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 Indonesia. 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. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hening Pujasari, PhD (+62 858 4844 7209, pujasari@ui.ac.id), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in sleep quality (time frame: Baseline (week 0) and week 8). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 Oct 2026.