Short-Form Psychoeducation Videos: Process Development Study
Notice bibliographique
Résumé
Background: Every year, around 1.8 million people in the United Kingdom are referred to NHS Talking Therapies, predominantly for cognitive behavioral therapy (CBT), which is the first-line treatment for common affective and anxiety disorders. However, more than a million of these do not complete their course. Supporting this "missing million" to attend and complete CBT is a policy priority. Objective: We aimed to coproduce a series of video resources to help patients better prepare for and complete their CBT sessions. Methods: We structured this project around a development cycle and documented outcomes against the Template for Intervention Description and Replication (TIDieR) checklist to ensure transparent intervention reporting. We assembled an interdisciplinary team to undertake an iterative video development process, composed of 3 subteams. An expert contributor subteam of 21 therapists shared their priorities and preferences for video content and style. A creative subteam of 4 members was responsible for scripting, filming, and editing video content. A project management subteam comprising 4 members (2 project managers, 1 designer, and 1 psychiatrist) distilled insights from the expert contributors and shared them with the creative team; they also presented video content to expert contributors and collected feedback. The process was terminated when expert contributors were satisfied that the videos developed could be shared with their patients. Results: We conducted 2 development cycles over 7 months between February and August 2024. In total, we produced 12 short-form videos, each 1 minute 14 seconds to 4 minutes 46 seconds long, across 4 distinct presentation styles (animation, patient narrative, therapist vignette, and expert interview). Videos covered topics such as the format of CBT (eg, why there is work to do between therapy sessions) and the psychological content (the value of developing healthy habits). Between 4 and 11 expert contributors reviewed any given batch of videos. Based on early feedback, we removed checklist formats in favor of positive storytelling, slowed pacing, and added subtitles to ensure readability and reduce cognitive load. The termination condition was achieved; expert contributors agreed to share videos with their patients. Conclusions: We successfully collaborated to produce a series of psychoeducation videos. A major strength of this process was the large number of people from different professional backgrounds involved; this diversity boosted both the validity of the content and the creativeness of the videos. This approach was well-suited to the setting of psychotherapy, where therapists have a detailed understanding of the anxieties and uncertainties of their patients, but we would advise caution in fields where professionals are less attuned to their patients' needs. Support to engage the "missing million" is urgently needed, and psychoeducational videos provide one suitable approach.
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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 | 0,023 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
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 ».