Self-management eHealth solutions for menopause – a systematic 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
OBJECTIVE: The purpose of this scoping review was to highlight the current scientific evidence on eHealth-based information tools for menopause in terms of quality, requirements and previous intervention outcomes. METHODS: We systematically searched electronic databases (Embase, CINAHL, Cochrane Library, Global Health Database [Ovid], Web of Science, ClinicalTrials.gov [NLM], LIVIVO Search Portal [ZB MED] and Google Scholar) from 1974 to March 2022 for relevant records. RESULTS: Our search yielded 1773 records, of which 28 met our inclusion criteria. Thirteen of 28 selected studies were cross-sectional with qualitative content analysis of websites about menopause; 9 studies were cohort studies examining the impact of an eHealth intervention; two studies were randomized controlled trials comparing eHealth tools with conventional ones; and four studies were non-systematic literature reviews. CONCLUSION: This scoping review highlights the potential of eHealth-based information tools for the management of menopause and shows that most eHealth-based information tools are inadequate in terms of readability and the balanced view on information. Providers of eHealth-based information tools should pay attention to a participatory design, readability, balance of content and the use of multimedia tools for information delivery to improve understanding.
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 | 0.005 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it