The use of digital storytelling of patients’ stories as an approach to translating knowledge: a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A growing interest has centered on digital storytelling in health research, described as a multi-media presentation of a story using technology. The use of digital storytelling in knowledge translation (KT) is emerging as technology advances in healthcare to address the challenging tasks of disseminating and transferring knowledge to key stakeholders. We conducted a scoping review of the literature available on the use of patient digital storytelling as a tool in KT interventions. METHODS: We followed by Arksey and O'Malley (Int J Soc Res Methodol 8(1):19-32, 2005), and Levac et al. (Implement Sci 5(1):69, 2010) recommended steps for scoping reviews. Search strategies were conducted for electronic databases (Medline, CINAHL, Web of Science, ProQuest dissertations and theses global, Clinicaltrials.gov and Psychinfo). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was used to report the review process. RESULTS: Of 4656 citations retrieved, 114 full texts were reviewed, and twenty-one articles included in the review. Included studies were from nine countries and focused on an array of physical and mental health conditions. A broad range of interpretations of digital storytelling and a variety of KT interventions were identified. Digital storytelling was predominately defined as a story in multi-media form, presented as a video, for selective or public viewing and used as educational material for healthcare professionals, patients and families. CONCLUSION: Using digital storytelling as a tool in KT interventions can contribute to shared decision-making in healthcare and increase awareness in patients' health related experiences. Concerns centered on the accuracy and reliability of some of the information available online and the impact of digital storytelling on knowledge action and implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it