Short-Form Psychoeducation Videos: Process Development Study
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".