e-Health Interventions for Healthy Aging: A Systematic Review
Bibliographic record
Abstract
Abstract BackgroundHealthy 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.MethodsA 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. In almost all the cases, e-Health interventions have strengthened or improved altogether physical activity outcome (e.g. walking), psychological outcome (e.g. memory) and promoted healthy behavior (e.g. healthy eating). Finally, significant improvements in clinical parameters (e.g. blood pressure) were found.ConclusionsThis systematic review synthesizes current evidence on the effectiveness of e-Health interventions in supporting HA.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".