Understanding Patients’ Perspectives for Integrating Screening Brief Intervention and Referral for Health Promotion in Diverse Healthcare Settings
Notice bibliographique
Résumé
Background: This study aims to understand patients perspectives on the implementation of screening brief intervention and referral (SBIR) for modifiable risk factors (alcohol, tobacco, and physical inactivity) and their behavior change. Approach: Alberta Health Services is implementing SBIR for modifiable risk factors into the Electronic Health Records (EHR) across acute and ambulatory care settings (Integrated Prevention in EHR (IPiC) Health). Co-design and qualitative descriptive approaches were employed to understand patients SBIR experiences and their stages of change behavior (Transtheoretical Model - TTM). Prior to SBIR implementation: We conducted semi-structured interviews with seven patient advisors (PAs) in three rounds of interviews to understand their perspectives: ) personal and clinical history with factors; 2) approaches to implement each factor and expectations for follow-up; 3) feedback on SBIR handouts and training resources. Interviews lasted 30-60 minutes, audio recorded, transcribed verbatim, and conducted abductive thematic analysis in NVivo 2/4. Findings informed the creation of SBIR materials and care resources (provider training resources for modifiable risk factors, prompts in EHR, referral pathways to resources, and patient survey tools). Additionally, PAs were consulted on strategies to follow-up with primary care providers after receiving SBIR. SBIR Implementation stage: We recruited diverse patients one month after they received SBIR and scored medium/ high risk on factors from intervention sites. We purposively sampled patients for in-depth interviews to ensure equity and diversity (gender, ethnicity, socio-economic status, age, immigration status, risk factor, and clinical site). Data collection and analysis was the same as PAs. The semi-structured interview guide was based on the Consolidated Framework for Implementation Research (CFIR), Health Stigma and Discrimination Framework, and TTM. This iterative form of assessment ensures that SBIR is patient centered and equitable. Conference date October 2024: An additional 2 patient interviews will be completed and analyzed. Results: We have completed 37 interviews with PAs and patients. Preliminary findings indicate barriers are: Patient level: (Need) habitual alcohol use at mealtimes/social gatherings; internalized stigma - failure to stop smoking/ poor health was their fault; perceived stigma - feeling judged for having an alcohol/ health problem. (Capacity): lacked knowledge of negative health consequences from smoking, drinking, and inactivity and strategies to change. (Opportunity) existing co-morbidities limited physical activities outside the home. (Motivation): lacked motivation to change behavior. Local attitudes/values: social acceptance / encouragement of heavy drinking in teen/early adult years; family/ friends with history of smoking / drinking; lack of social support to reduce alcohol and increase physical activity. Connections (referral): providers did not make referrals. (Patient-Centeredness): health condition related stigma - PAs experienced judgement / dismissal/ disregard due to smoking.Reported facilitators to behavior change include: (Patient-Centeredness) trusting relationship with their providers; encouragement to take small steps towards positive health behavior; (Capacity) patient knowledge and awareness of health behavior change benefit their energy levels; and (sociocultural values) socially supported physical activities/alcohol free gatherings. Implications: Patients perspectives contribute to the adaptation of SBIR for modifiable risk factors to ensure health equity, including provider training / communication to destigmatize brief interventions, developing accessible patient referral pathways, and educational resources. The successful implementation of SBIR will addresses patients health challenges related to modifiable risk factors and improves patient health outcomes. Our next steps involve adaption of SBIR across diverse clinical settings for spread, scale, and sustainability.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».