Transient Elastography and Video Recovery Narrative Access to Support Recovery From Alcohol Misuse: Development of a Novel Intervention for Use in Community Alcohol Treatment Services
Notice bibliographique
Résumé
BACKGROUND: Mortality from alcohol-related liver disease has risen significantly for 3 decades. Transient elastography (TE) is a noninvasive test providing a numerical marker of liver disease. Preliminary evidence suggests that TE can reduce alcohol consumption. The KLIFAD (does knowledge of liver fibrosis affect high-risk drinking behavior?) study has developed a complex intervention wherein people receiving alcohol treatment are provided with access to TE, accompanied by scripted feedback tailored to their disease state, and access to video narratives describing alcohol misuse recovery after receiving TE. Recovery narratives are included due to preliminary evidence from mental health studies which suggest that access to digital narratives describing recovery from mental health problems can help people affected by mental health problems, including through mechanisms with the potential to be transferable to an alcohol treatment setting, for example, by increasing hope for the future, enabling learning from the experience of others, or promoting help-seeking behaviors. OBJECTIVE: We aimed to develop the KLIFAD intervention to the point that it could be delivered in a feasibility trial and to produce knowledge relevant to clinicians and researchers developing interventions making use of biomarkers of disease. METHODS: In research activity 1, standardized scripted feedback was developed by this study, and then iterated through focus groups with people who had experienced alcohol misuse and TE, and key alcohol workers with experience in delivering TE. We report critical design considerations identified through focus groups, in the form of sensitizing concepts. In research activity 2, a video production guide was coproduced to help produce impactful video-based recovery narratives, and a patient and public involvement (PPI) panel was consulted for recommendations on how best to integrate recovery narratives into an alcohol treatment setting. We report PPI recommendations and an overview of video form and content. RESULTS: Through research activity 1, we learnt that patient feedback has not been standardized in prior use of TE, that receiving a numeric marker can provide an objective target that motivates and rewards recovery, and that key alcohol workers regularly tailor information to their clients. Through research activity 2, we developed a video production guide asking narrators what recovery means to them, what helped their recovery, and what they have learned about recovery. We produced 10 recovery narratives and collected PPI recommendations on maximizing impact and safety. These led to the production of unplanned videos presenting caregiver and clinician perspectives, and a choice to limit narrative availability to alcohol treatment settings, where support is available around distressing content. These choices have been evaluated through a feasibility randomized controlled trial [ISRCTN16922410]. CONCLUSIONS: Providing an objective target that motivates and rewards recovery is a candidate change mechanism for complex interventions integrating biomarkers of disease. Recovery narratives can contain distressing content; intervention developers should attend to safe usage. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-054954.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,001 |
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 ».