AI-Based Personalized Self-Management for Patients With Heart Failure
Effectiveness of AI-Based Personalized Self-Management Intervention on Self-Care Behaviors and Health-Related Quality of Life Among Patients With Heart Failure
This study aims to evaluate the effectiveness of an AI-based personalized self-management intervention on self-care behaviors and health-related quality of life among patients with chronic heart failure. Using a two-phase sequential explanatory mixed-methods design, Phase I consists of a randomized controlled trial comparing a 12-week AI-guided self-management intervention plus usual care with usual care alone. Self-care behaviors and health-related quality of life will be assessed at baseline, 6 weeks, and 12 weeks. Phase II will involve semi-structured interviews with a purposively selected subgroup of intervention participants to explore their experiences with the AI-based intervention and to explain the quantitative findings. The study seeks to generate evidence on the effectiveness and patient acceptability of AI-supported self-management in heart failure care.
Aperçu de l'étude
Statut
Les conditions
Type d'étude
Inscription (Estimé)
Phase
- N'est pas applicable
Contacts et emplacements
Coordonnées de l'étude
- Nom: Mohamed Fakhry Salem, PhD
- Numéro de téléphone: 01286038014
- E-mail: Mohamed.Fakhry@alexu.edu.eg
Sauvegarde des contacts de l'étude
- Nom: Salem
- E-mail: Mohamed.Fakhry@alexu.edu.eg
Lieux d'étude
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Alexandria, Egypte, 21511
- Faculty of Nursing, Alexandria University
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Contact:
- Mohamed Fakhry Salem, PhD
- Numéro de téléphone: 01286038014
- E-mail: Mohamed.Fakhry@alexu.edu.eg
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Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
Accepte les volontaires sains
Sexes éligibles pour l'étude
La description
Eligibility Criteria
Inclusion Criteria:
Adults aged 18 years or older. Confirmed diagnosis of chronic heart failure (NYHA Class II or III). Clinically stable for at least 1 month before enrollment. Able to read and understand Arabic. Own or have regular access to a smartphone compatible with the AI-based application.
Willing and able to provide informed consent and participate throughout the 12-week study period.
Exclusion Criteria:
NYHA Class IV or end-stage heart failure. Severe cognitive impairment or any condition preventing reliable self-reporting or informed consent.
Severe psychiatric illness that may interfere with study participation. Participation in another heart failure self-management or behavioral intervention program during the study period.
Inability to use a smartphone or the study application despite orientation and support.
Any serious medical condition deemed by the investigators to make participation inappropriate or unsafe.
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
- Objectif principal: Soins de soutien
- Répartition: Randomisé
- Modèle interventionnel: Affectation parallèle
- Masquage: Seul
Armes et Interventions
Groupe de participants / Bras |
Intervention / Traitement |
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Expérimental: Experimental: AI-Based Personalized Self-Management Intervention
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Participants receive a smartphone-based AI application delivering personalized self-management support for 12 weeks, including symptom monitoring, individualized self-care recommendations, medication and lifestyle reminders, educational content, and real-time guidance alongside usual care. |
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Comparateur actif: Active Comparator: Usual Care
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Participants receive routine heart failure care, including standard education, outpatient follow-up, and prescribed treatment, without access to the AI-based application. |
Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Description de la mesure |
Délai |
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Primary Outcome Measure 1: Self-Care Behavior (EHFScBS-9)
Délai: Time Frame: Baseline, Week 6, and Week 12
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Description: Change in self-care behavior measured using the 9-item European Heart Failure Self-Care Behaviour Scale (EHFScBS-9). Scores are transformed to a 0-100 scale, with higher scores indicating better self-care behavior. |
Time Frame: Baseline, Week 6, and Week 12
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Primary Outcome Measure 2: Health-Related Quality of Life (RAND-36)
Délai: Time Frame: Baseline, Week 6, and Week 12
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Description: Change in health-related quality of life measured using the RAND 36-Item Health Survey (RAND-36). Scores are transformed to a 0-100 scale, with higher scores indicating better health-related quality of life. |
Time Frame: Baseline, Week 6, and Week 12
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Mesures de résultats secondaires
Mesure des résultats |
Description de la mesure |
Délai |
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Secondary Outcome Measure 1: Technology Acceptance of the AI-Based Intervention
Délai: Time Frame: Week 12
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Description: Technology acceptance measured using an adapted AI Technology Acceptance Questionnaire based on the Modified Technology Acceptance Model (mTAM). The instrument consists of 16 items assessing Perceived Usefulness, Perceived Ease of Use, Behavioral Intention, and User Satisfaction. Items are rated on a 7-point Likert scale, with higher scores indicating greater acceptance of the AI-based intervention. |
Time Frame: Week 12
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Secondary Outcome Measure 2: Participants' Experiences With the AI-Based Intervention
Délai: Time Frame: after completion of the 12-week intervention.
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Description: Participants' experiences, perceived benefits, barriers, facilitators, and recommendations regarding the AI-based personalized self-management intervention, assessed through semi-structured interviews and analyzed using thematic analysis. |
Time Frame: after completion of the 12-week intervention.
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Collaborateurs et enquêteurs
Parrainer
Les enquêteurs
- Chercheur principal: Mohamed Fakhry Salem, PHD, Alexandria University
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Estimé)
Achèvement primaire (Estimé)
Achèvement de l'étude (Estimé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Mots clés
Termes MeSH pertinents supplémentaires
Autres numéros d'identification d'étude
- AIHF-2026-01
Plan pour les données individuelles des participants (IPD)
Prévoyez-vous de partager les données individuelles des participants (DPI) ?
Informations sur les médicaments et les dispositifs, documents d'étude
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