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AI-Assisted Personalized Heat-Risk Alerts (HEAT-CARE)

12 september 2026 bijgewerkt door: 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.

Studie Overzicht

Toestand

Werving

Conditie

Interventie / Behandeling

Gedetailleerde beschrijving

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.

Studietype

Ingrijpend

Inschrijving (Geschat)

120

Fase

  • Niet toepasbaar

Contacten en locaties

In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.

Studiecontact

Studie Locaties

  • Pakistan
    • Punjab Province
      • Gujranwala, Punjab Province, Pakistan, 52250
        • Werving
        • Gondal Medical Complex

Deelname Criteria

Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.

Geschiktheidscriteria

Leeftijden die in aanmerking komen voor studie

  • Volwassen
  • Oudere volwassene

Accepteert gezonde vrijwilligers

Nee

Beschrijving

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.

Studie plan

Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.

Hoe is de studie opgezet?

Ontwerpdetails

  • Primair doel: Ondersteunende zorg
  • Toewijzing: Gerandomiseerd
  • Interventioneel model: Parallelle opdracht
  • Masker: Enkel

Wapens en interventies

Deelnemersgroep / Arm
Interventie / Behandeling
Experimenteel: 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.
Gedragsmatig: AI-Assisted Personalized Heat-Risk Alert System
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.
Actieve vergelijker: 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.
Gedragsmatig: Generic PMD Heat-Health Advisory
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.

Wat meet het onderzoek?

Primaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Heat-Related Illness Symptom Score (HRISS)
Tijdsspanne: 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.
Baseline and six weeks after randomization

Secundaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Heat-Health Protective Behavior Checklist (HPBC)
Tijdsspanne: 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.
Baseline and six weeks after randomization
Heat-Health Knowledge, Attitudes and Practices (KAP) Score
Tijdsspanne: Baseline and six weeks after randomization
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.
Baseline and six weeks after randomization
Heat-related hospital admissions
Tijdsspanne: From randomization through six weeks
Number of unplanned hospital admissions attributable to heat-related illness during the six-week intervention period.
From randomization through six weeks

Medewerkers en onderzoekers

Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.

Sponsor

National University of Medical Sciences, Pakistan

Onderzoekers

  • Hoofdonderzoeker: Shamaila Mohsin, PhD Public Health, Armed Forces Post Graduate Medical Institute, AFPGMI, NUMS, Rawalpindi

Studie record data

Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.

Bestudeer belangrijke data

Studie start (Werkelijk)

1 september 2026

Primaire voltooiing (Geschat)

13 oktober 2026

Studie voltooiing (Geschat)

30 oktober 2026

Studieregistratiedata

Eerst ingediend

12 september 2026

Eerst ingediend dat voldeed aan de QC-criteria

12 september 2026

Eerst geplaatst (Werkelijk)

17 september 2026

Updates van studierecords

Laatste update geplaatst (Werkelijk)

17 september 2026

Laatste update ingediend die voldeed aan QC-criteria

12 september 2026

Laatst geverifieerd

1 september 2026

Meer informatie

Termen gerelateerd aan deze studie

Trefwoorden

Aanvullende relevante MeSH-voorwaarden

Andere studie-ID-nummers

  • 757-AAA-ERC-AFPGMI

Plan Individuele Deelnemersgegevens (IPD)

Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?

NEE

Beschrijving IPD-plan

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.

Informatie over medicijnen en apparaten, studiedocumenten

Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel

Nee

Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct

Nee

Deze informatie is zonder wijzigingen rechtstreeks van de website clinicaltrials.gov gehaald. Als u verzoeken heeft om uw onderzoeksgegevens te wijzigen, te verwijderen of bij te werken, neem dan contact op met register@clinicaltrials.gov. Zodra er een wijziging wordt doorgevoerd op clinicaltrials.gov, wordt deze ook automatisch bijgewerkt op onze website .

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