The use of social media among health professionals to facilitate chronic disease self-management with their patients: A systematic review
Bibliographic record
Abstract
OBJECTIVE: The objective of this systematic review was to summarize the evidence pertaining to the use of social media by health professionals to facilitate chronic disease self-management with their patients. METHODS: A systematic approach was used to retrieve and extract relevant data. A total of 5163 citations were identified, of which seven unique studies met criteria for inclusion; one was a randomized controlled trial, two were prospective cohort studies, and four were qualitative studies. The following social media platforms were evaluated: discussion forums (6 studies) and collaborative project (1 study). RESULTS: The available evidence suggests that health professionals perceived discussion forums and collaborative projects to be useful social media platforms to facilitate chronic disease self-management with patients. No relevant evidence was found regarding the use of other social media platforms. Most studies indicated positive findings regarding health professionals' intention to use discussion forums, while the one study that used a collaborative project also indicated positive findings with its perceived ease of use as health professionals felt that it was useful to facilitate chronic disease self-management with patients. Mixed findings were seen in regards to health professionals' perceived ease of use of discussion forums. The most common barrier to using social media platforms was the lack of time in health professionals' schedules. CONCLUSIONS: Discussion forums and collaborative projects appear to be promising resources for health professionals to assist their patients in self-managing their chronic conditions; however, further research comparing various social media platforms is needed.
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.
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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".