What are the decisions and decisional needs of patients with brain-heart conditions, and their caregivers? A survey study
Notice bibliographique
Résumé
Abstract Purpose People with brain (e.g. stroke, depression) and heart (e.g., heart failure, irregular heart rhythms) conditions often have both together. Little is known about whether people know about this connection, how it impacts health decision-making and their decisional needs. This study sought to identify common decisions and decisional needs of people living with brain-heart conditions or their caregivers. Methods Using a co-production approach, we designed a survey with a team of researchers, clinicians, patients and caregivers. Eligible participants were adults living with a brain-heart condition, or family members/caregivers, who have made a health decision for themselves or their loved one about their condition within the past 12 months. Potential participants were identified using electronic health records from outpatient clinics and advertisements through community health centres, community social media groups, and newsletters of brain-heart and caregiver related organizations. We cross-sectionally assessed and descriptively analyzed decisions and decisional needs using questions informed by the Ottawa Decision Support Framework, including the validated Decision Conflict Scale (DCS) and the Decision Regret Scale (DRS). Results We recruited 48/50 (96%) patients/caregivers from June 2024 to January 2025. Twenty-six (54%) had a combined brain-heart condition and 22(46%) had a heart condition and at risk for a brain condition. Common decisions were about lifestyle changes 14(32%), medications 11(25%), procedures 10(23%), and diagnostic tests 5(11%). Factors making decisions difficult were that brain implications were never part of the conversation for their heart condition (36%), worrying about choosing the wrong option (32%), difficulty discussing the decision with important others (23%) and feeling overloaded with information (23%). Nine participants (22%) had significant decisional conflict (>37.5/100) and 6 participants (17%) had significant decision regret (>25/100). If they had to make the same decision again, 24 (59%) would want to discuss options and their advantages/disadvantages with their clinicians, 18 (44%) would want reliable information about the options, 17 (41%) would desire access to a patient decision aid, and 17 (41%) would want to speak with someone who has made the same decision recently. Conclusion Patients/caregivers in our study reported unmet decisional needs regarding brain-heart health, most notably limited discussion about the brain-heart link. Interviews with a subset of survey respondents are ongoing, and will offer a deeper understanding into their responses. Interventions can be designed to support patients facing brain-heart health-related decisions by targeting their decisional needs.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».