Realist evaluation: what works, for whom, and under what circumstances for recipients of Healthy Conversation Skills (HCS) training
Notice bibliographique
Résumé
Making Every Contact Count (MECC) is a person-centred intervention that aims to utilise existing conversations that service providers have with service users to promote health behaviour change. It was initially implemented across NHS settings but has since been applied across a wide variety of settings including the voluntary, community, and social enterprise (VCSE) sector. MECC was a UK-based initiative but has since been applied in Ireland, Australia, South Africa, and Canada, and continues to be a popular national approach to health behaviour change: https://www.rsph.org.uk/our-work/policy/wider-public-health-workforce/what-are-you-talking-about.html. Approaches to MECC training vary considerably. Whilst some training approaches focus on encouraging brief advice, others encourage active listening, asking questions, and supporting goal setting. The broad applicability of MECC means that there are also a wide variety of recipients of MECC training, who have a broad range of different backgrounds and previous experience. Our previous work demonstrated that the specific MECC training approach called Healthy Conversation Skills (HCS) training, which supports service users in identifying their own solutions as opposed to providing advice, appears to be the most acceptable approach to MECC delivery in VCSE settings. Multiple previous studies have demonstrated that HCS training increases the confidence and ability of trainees to deliver MECC. However, the available evidence is focused on staff from healthcare and local authority settings. It is therefore unknown whether the existing approach to HCS training is appropriate and sufficient for service providers from the VCSE, who are unlikely to have a healthcare background. Therefore, the aim of this study is to assess the appropriateness of HCS training for service providers from the VCSE, by exploring and comparing their training experiences with pharmacy students (a comparison group with a healthcare background). To do this, we will conduct a mixed-methods realist evaluation to assess whether HCS equips VCSE providers to deliver MECC effectively. The findings will allow us to make recommendations about whether HCS training should be adapted depending on the setting and if so, what changes are required. The collection of both data streams will utilise existing delivery of HCS training by public health practitioner Robert Anderson-Weaver from Portsmouth City Council. Portsmouth was selected as the study location as it covers a diverse area and is the epicentre of advanced implementation of HCS training.
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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 | 0,010 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
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