e-Health interventions for healthy aging: a systematic 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: Healthy aging (HA) is a contemporary challenge for population health worldwide. Electronic health (e-Health) interventions have the potential to support empowerment and education of adults aged 50 and over. OBJECTIVES: To summarize evidence on the effectiveness of e-Health interventions on HA and explore how specific e-Health interventions and their characteristics effectively impact HA. METHODS: A systematic review was conducted based on the Cochrane Collaboration methods including any experimental study design published in French, Dutch, Spanish, and English from 2000 to 2018. RESULTS: Fourteen studies comparing various e-Health interventions to multiple components controls were included. The target population, type of interventions, and outcomes measured were very heterogeneous across studies; thus, a meta-analysis was not possible. However, effect estimates indicate that e-Health interventions could improve physical activity. Positive effects were also found for other healthy behaviors (e.g., healthy eating), psychological outcomes (e.g., memory), and clinical parameters (e.g., blood pressure). Given the low certainty of the evidence related to most outcomes, these results should be interpreted cautiously. CONCLUSIONS: This systematic review found limited evidence supporting the effectiveness of e-Health interventions, although the majority of studies show positive effects of these interventions for improving physical activity in older adults. Thus, better quality evidence is needed regarding the effects of e-Health on the physiological, psychological, and social dimensions of HA. SYSTEMATIC REVIEW REGISTRATION: The review protocol was registered in PROSPERO (registration number: CRD42016033163).
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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 | 0.026 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.030 | 0.007 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it