Online Tobacco Cessation Training and Competency Assessment for Complementary and Alternative Medicine (CAM) Practitioners: Protocol for the CAM Reach Web Study
Notice bibliographique
Résumé
BACKGROUND: Complementary and alternative medicine (CAM) practitioners, such as chiropractors, acupuncturists, and massage therapists, are a growing presence in the US health care landscape and already provide health and wellness care to significant numbers of patients who use tobacco. For decades, conventional biomedical practitioners have received training to provide evidence-based tobacco cessation brief interventions (BIs) and referrals to cessation services as part of routine clinical care, whereas CAM practitioners have been largely overlooked for BI training. Web-based training has clear potential to meet large-scale training dissemination needs. However, despite the exploding use of Web-based training for health professionals, Web-based evaluation of clinical skills competency remains underdeveloped. OBJECTIVE: In pursuit of a long-term goal of helping CAM practitioners integrate evidence-based practices from US Public Health Service Tobacco Dependence Treatment Guideline into routine clinical care, this pilot protocol aims to develop and test a Web-based tobacco cessation training program tailored for CAM practitioners. METHODS: In preparation for a larger trial to examine the effect of training on CAM practitioner clinical practice behaviors around tobacco cessation, this developmental study will (1) adapt an existing in-person tobacco cessation BI training program that is specifically tailored for CAM therapists for delivery via the Internet; (2) develop a novel, Web-based tool to assess CAM practitioner competence in tobacco cessation BI skills, and conduct a pilot validation study comparing the competency assessment tool to live video role plays with a standardized patient; (3) pilot test the Web-based training with 120 CAM practitioners (40 acupuncturists, 40 chiropractors, 40 massage therapists) for usability, accessibility, acceptability, and effects on practitioner knowledge, self-efficacy, and competency with tobacco cessation; and (4) conduct qualitative and quantitative formative research on factors influencing practitioner tobacco cessation clinical behaviors (eg, practice environment, peer social influence, and insurance reimbursement). RESULTS: Web-training and competency assessment tool development and study enrollment and training activities are complete (N=203 practitioners enrolled). Training completion rates were lower than expected (36.9%, 75/203), necessitating over enrollment to ensure a sufficient number of training completers. Follow-up data collection is in progress. Data analysis will begin immediately after data collection is complete. CONCLUSIONS: To realize CAM practitioners' potential to promote tobacco cessation and use of evidence-based treatments, there is a need to know more about the facilitative and inhibitory factors influencing CAM practitioner tobacco intervention behaviors (eg, social influence and insurance reimbursement). Given marked differences between conventional and CAM practitioners, extant knowledge about factors influencing conventional practitioner adoption of tobacco cessation behaviors cannot be confidently extrapolated to CAM practitioners. The potential impact of this study is to expand tobacco cessation and health promotion infrastructure in a new group of health practitioners who can help combat the continuing epidemic of tobacco use.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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 ».