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

12. september 2026 oppdatert av: 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.

Studieoversikt

Status

Rekruttering

Forhold

Intervensjon / Behandling

Detaljert 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.

Studietype

Intervensjonell

Registrering (Antatt)

120

Fase

  • Ikke aktuelt

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Studiesteder

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

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Voksen
  • Eldre voksen

Tar imot friske frivillige

Nei

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

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Støttende omsorg
  • Tildeling: Randomisert
  • Intervensjonsmodell: Parallell tildeling
  • Masking: Enkelt

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Eksperimentell: 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.
Atferdsmessig: 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.
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.
Atferdsmessig: 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.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
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.
Baseline and six weeks after randomization

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
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.
Baseline and six weeks after randomization
Heat-Health Knowledge, Attitudes and Practices (KAP) Score
Tidsramme: 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
Tidsramme: 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

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

National University of Medical Sciences, Pakistan

Etterforskere

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

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

1. september 2026

Primær fullføring (Antatt)

13. oktober 2026

Studiet fullført (Antatt)

30. oktober 2026

Datoer for studieregistrering

Først innsendt

12. september 2026

Først innsendt som oppfylte QC-kriteriene

12. september 2026

Først lagt ut (Faktiske)

17. september 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

17. september 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

12. september 2026

Sist bekreftet

1. september 2026

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • 757-AAA-ERC-AFPGMI

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

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.

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

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