Digitally Assisted Peer Recovery Coach to Facilitate Linkage to Outpatient Treatment Following Inpatient Alcohol Withdrawal Treatment: Proof-of-Concept Pilot Study
Notice bibliographique
Résumé
Background Alcohol use disorder (AUD), associated with significant morbidity and mortality, continues to be a major public health problem. The COVID-19 pandemic exacerbated the impact of AUD, with a 25% increase in alcohol-related mortality from 2019 to 2020. Thus, innovative treatments for AUD are urgently needed. While inpatient alcohol withdrawal management (detoxification) is often an entry point for recovery, most do not successfully link to ongoing treatment. Transitions between inpatient and outpatient treatment pose many challenges to successful treatment continuation. Peer recovery coaches—individuals with the lived experience of recovery who obtain training to be coaches—are increasingly used to assist individuals with AUD and may provide a degree of continuity during this transition. Objective We aimed to evaluate the feasibility of using an existing care coordination app (Lifeguard) to assist peer recovery coaches in supporting patients after discharge and facilitating linkage to care. Methods This study was conducted on an American Society of Addiction Medicine–Level IV inpatient withdrawal management unit within an academic medical center in Boston, MA. After providing informed consent, participants were contacted by the coach through the app, and after discharge, received daily prompts to complete a modified version of the brief addiction monitor (BAM). The BAM inquired about alcohol use, risky, and protective factors. The coach sent daily motivational texts and appointment reminders and checked in if BAM responses were concerning. Postdischarge follow-up continued for 30 days. The following feasibility outcomes were evaluated: (1) proportion of participants engaging with the coach before discharge, (2) proportion of participants and the number of days engaging with the coach after discharge, (3) proportion of participants and the number of days responding to BAM prompts, and (4) proportion of participants successfully linking with addiction treatment by 30-day follow-up. Results All 10 participants were men, averaged 50.5 years old, and were mostly White (n=6), non-Hispanic (n=9), and single (n=8). Overall, 8 participants successfully engaged with the coach prior to discharge. Following discharge, 6 participants continued to engage with the coach, doing so on an average of 5.3 days (SD 7.3, range 0-20 days); 5 participants responded to the BAM prompts during the follow-up, doing so on an average of 4.6 days (SD 6.9, range 0-21 days). Half (n=5) successfully linked with ongoing addiction treatment during the follow-up. The participants who engaged with the coach post discharge, compared to those who did not, were significantly more likely to link with treatment (83% vs 0%, χ2=6.67, P=.01). Conclusions The results demonstrated that a digitally assisted peer recovery coach may be feasible in facilitating linkage to care following discharge from inpatient withdrawal management treatment. Further research is warranted to evaluate the potential role for peer recovery coaches in improving postdischarge outcomes. Trial Registration ClinicalTrials.gov NCT05393544; https://www.clinicaltrials.gov/ct2/show/NCT05393544
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| 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 | 0,001 |
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 tête enseignante, pas un consensus.
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