Using videos and films with people with major cognitive disorder living in care settings: A scoping review
Bibliographic record
Abstract
Background: The use of videos and films may improve the well-being of people with major cognitive disorder.Most literature about the use is within the community.There is a literature gap in the use in care settings.Exploring this gap is particularly timely during the COVID-19 pandemic, considering the lockdown of many care settings and the potential support that videos and films can be provided to people with the major cognitive disorder in these settings.In addition, compared with more complex technologies, videos and films are relatively inexpensive and easy to implement, making them more accessible.Objective: This scoping review aims to understand the facilitators and barriers to implementing videos and films with people with the major cognitive disorder in care settings, as well as the benefits and drawbacks of using this technology with this population.Method: This scoping review followed the Joanna Briggs Institute scoping review methodology.It was conducted between May and July 2022.It followed a three-step search strategy: (1) identifying keywords from an initial broad search using two databases CINAHL and AgeLine; (2) doing a second search using all identified keywords and index terms across chosen databases (CINAHL, AgeLine, MEDLINE, PsycINFO, Web of Science, Pro-Quest, and Google); and (3) hand-searching the reference lists of all selected articles for additional literature. Results:The final results included ten articles.Content analysis was conducted.Facilitators and barriers to implementing videos and films with people with the major cognitive disorder in care settings were identified.The benefits and drawbacks of using videos and films with this population were also identified.Conclusion: This scoping review presents current evidence on facilitators and barriers to implementing videos and films with people with the major cognitive disorder in care settings, and the benefits and drawbacks of using videos and films with this population.
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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 | 0.020 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".