AI-Assisted Personalized Heat-Risk Alerts (HEAT-CARE)
12. september 2026 opdateret af: Prof. Dr. Shamaila Mohsin, PhD, National University of Medical Sciences, Pakistan
Effectiveness of an Artificial Intelligence-Assisted Personalized Heat-Risk Alert System in Reducing Heat-Related Illness Among Adults With Chronic Conditions: A Randomized Controlled Trial in Pakistan
This two-arm randomized controlled trial will evaluate whether an artificial intelligence-assisted personalized heat-risk alert system reduces heat-related illness symptom burden among adults with chronic conditions.
The intervention will integrate prespecified clinical characteristics with the Pakistan Meteorological Department's same-day forecast maximum temperature to classify individual heat-related acute clinical-event risk and deliver personalized alerts through a mobile application.
The control group will receive a generic PMD heat-health advisory through the same application.
Studieoversigt
Status
Rekruttering
Betingelser
Detaljeret beskrivelse
Extreme heat poses increased health risks for adults living with chronic conditions. Conventional heat-health warning systems generally provide population-level advisories and may not account for individual clinical vulnerability. This study will evaluate an artificial intelligence-assisted personalized heat-risk alert system designed to integrate individual clinical characteristics with environmental exposure information.
The trial will enroll 120 adults with hypertension, type 2 diabetes, chronic kidney disease, cardiovascular disease, and/or obesity from the outpatient department of a selected tertiary-care hospital in Gujranwala, Pakistan. Participants will be randomized 1:1 to an intervention or control group and followed for six weeks.
On days when the Pakistan Meteorological Department same-day forecast maximum temperature is ≥36°C, the intervention system will process prespecified clinical characteristics and the temperature forecast through a locked AI Prediction Model. Participants will be classified into low, moderate, or high heat-related acute clinical-event risk categories, with corresponding personalized heat-health messaging. The control group will receive a generic PMD heat-health advisory through the same patient-facing mobile application without AI-based risk stratification or clinical personalization.
The primary outcome is Heat-Related Illness Symptom Score (HRISS) at Week 6. Secondary outcomes include heat-protective behaviors, heat-health knowledge, attitudes and practices, heat-related emergency department visits and hospital admissions, and application engagement. The AI model will be developed and internally validated using a separate historical hospital dataset containing heat-related emergency department visits/admissions and will be locked before intervention delivery.
Undersøgelsestype
Interventionel
Tilmelding (Anslået)
120
Fase
- Ikke anvendelig
Kontakter og lokationer
Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.
Studiekontakt
- Navn: Mubra Noor, MS Public Health
- Telefonnummer: +92- 321-6143378
- E-mail: mubranoor111@gmail.com
Studiesteder
-
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Punjab Province
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Gujranwala, Punjab Province, Pakistan, 52250
- Rekruttering
- Gondal Medical Complex
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-
Deltagelseskriterier
Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.
Berettigelseskriterier
Aldre berettiget til at studere
- Voksen
- Ældre voksen
Tager imod sunde frivillige
Ingen
Beskrivelse
Inclusion Criteria:
- Adults aged 18 years or older attending the outpatient department of the selected tertiary-care hospital during the recruitment period.
- Have a documented diagnosis of at least one chronic non-communicable disease associated with increased susceptibility to heat-related illness, including hypertension, type 2 diabetes mellitus, chronic kidney disease, cardiovascular disease, or obesity (BMI ≥30 kg/m²).
- Have access to a personal smartphone capable of receiving study heat-risk alert notifications.
- Be able to read Urdu or English, or have a household member/caregiver available to read and explain study alerts when required.
- Be willing and able to provide written informed consent.
- Intend to remain within the study catchment area for the duration of the six-week study period to facilitate follow-up.
Exclusion Criteria:
- Patients requiring immediate emergency treatment or hospital admission at the time of recruitment.
- Individuals with severe cognitive impairment, dementia, psychotic illness, or another medical condition that limits their ability to understand study procedures or provide informed consent.
- Patients with terminal illness or those receiving palliative care.
- Individuals with severe visual, hearing, or communication impairments that prevent effective receipt of the study alert intervention and outcome assessment without a reliable caregiver.
- Pregnant women, because pregnancy has distinct physiological responses to heat exposure and would require separate clinical risk stratification beyond the scope of this study.
- Participants currently enrolled in another clinical trial or structured behavioral intervention related to heat-health, climate adaptation, or chronic disease self-management.
- Participants who are unable or unwilling to comply with study procedures or complete the required follow-up assessment.
Studieplan
Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
- Primært formål: Støttende pleje
- Tildeling: Randomiseret
- Interventionel model: Parallel tildeling
- Maskning: Enkelt
Våben og indgreb
Deltagergruppe / Arm |
Intervention / Behandling |
|---|---|
|
Eksperimentel: AI-Assisted Personalized Heat-Risk Alert
Participants will receive AI-assisted personalized heat-risk alerts through the patient-facing mobile application on days when the Pakistan Meteorological Department's same-day forecast maximum temperature is ≥36°C.
A locked AI prediction model will integrate prespecified clinical characteristics and the same-day temperature forecast to classify heat-related acute clinical-event risk as low, moderate, or high.
Risk-category-specific heat-health messaging will then be delivered through the application.
|
A mobile application-based heat-health alert system that uses a locked AI prediction engine to integrate prespecified individual clinical characteristics with the Pakistan Meteorological Department's same-day forecast maximum temperature (≥36°C) and classify participants into low, moderate, or high heat-related acute clinical-event risk categories.
The application delivers corresponding personalized heat-health messages.
|
|
Aktiv komparator: Generic PMD Heat-Health Advisory
Participants will receive a generic Pakistan Meteorological Department heat-health advisory through the same patient-facing mobile application on days when the same-day forecast maximum temperature is ≥36°C.
The control condition will not include AI-based risk stratification, individualized risk classification, or disease-specific personalization.
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Generic Pakistan Meteorological Department heat-health advisory delivered through the same patient-facing mobile application when the same-day forecast maximum temperature is ≥36°C, without AI-based risk stratification or individualized clinical personalization.
|
Hvad måler undersøgelsen?
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Heat-Related Illness Symptom Score (HRISS)
Tidsramme: Baseline and six weeks after randomization
|
The total HRISS score ranges from 0 to 20, based on 10 heat-related illness symptom items assessed for the preceding 7 days; higher scores indicate greater heat-related illness symptom burden.
HRISS will be assessed at baseline and Week 6, with the primary analysis comparing Week-6 HRISS between groups after adjustment for baseline HRISS.
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Baseline and six weeks after randomization
|
Sekundære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
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Heat-Health Protective Behavior Checklist (HPBC)
Tidsramme: Baseline and six weeks after randomization
|
The total score on the 10-item Heat-Health Protective Behavior Checklist (HPBC) ranges from 0 to 10, with higher scores indicating greater adoption of heat-protective behaviors.
HPBC will be assessed at baseline and Week 6, with the between-group comparison based on the Week-6 score adjusted for baseline.
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Baseline and six weeks after randomization
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Heat-Health Knowledge, Attitudes and Practices (KAP) Score
Tidsramme: Baseline and six weeks after randomization
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Heat-health knowledge, attitudes, and practices will be assessed using the study's 20-item heat-health KAP questionnaire.
The questionnaire will be administered at baseline and Week 6, with the prespecified between-group comparison based on the Week 6 assessment, adjusted for baseline values.
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Baseline and six weeks after randomization
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Heat-related hospital admissions
Tidsramme: From randomization through six weeks
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Number of unplanned hospital admissions attributable to heat-related illness during the six-week intervention period.
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From randomization through six weeks
|
Samarbejdspartnere og efterforskere
Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.
Efterforskere
- Ledende efterforsker: Shamaila Mohsin, PhD Public Health, Armed Forces Post Graduate Medical Institute, AFPGMI, NUMS, Rawalpindi
Datoer for undersøgelser
Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.
Studer store datoer
Studiestart (Faktiske)
1. september 2026
Primær færdiggørelse (Anslået)
13. oktober 2026
Studieafslutning (Anslået)
30. oktober 2026
Datoer for studieregistrering
Først indsendt
12. september 2026
Først indsendt, der opfyldte QC-kriterier
12. september 2026
Først opslået (Faktiske)
17. september 2026
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
17. september 2026
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
12. september 2026
Sidst verificeret
1. september 2026
Mere information
Begreber relateret til denne undersøgelse
Yderligere relevante MeSH-vilkår
Andre undersøgelses-id-numre
- 757-AAA-ERC-AFPGMI
Plan for individuelle deltagerdata (IPD)
Planlægger du at dele individuelle deltagerdata (IPD)?
INGEN
IPD-planbeskrivelse
Individual participant-level data will not be made publicly available because the study involves sensitive clinical and health-related information from the participant population.
Data will be retained and managed in accordance with the approved study protocol, institutional requirements, and applicable ethical and privacy requirements.
De-identified aggregate findings will be reported in publications and other appropriate dissemination outputs.
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