The impact of eHealth group interventions on the mental, behavioral, and physical health of adults: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: COVID-19 has resulted in an increased demand for eHealth services globally. There is emerging evidence for the efficacy for group eHealth interventions that support population-based mental health and wellbeing, but a systematic review is lacking. The primary objective of this systematic review is to summarize the evidence for eHealth group counseling and coaching programs for adults. A second objective is to assess, within studies selected for our primary objective, the impact of programs that encourage PA on outcomes compared to those that do not. METHODS: Randomized controlled trials that assess the impact of eHealth group counseling or coaching programs on mental health, health behavior, or physical health activity among community-dwelling adults will be included. We will search the following electronic databases (from January 2005 onwards): MEDLINE, PsycINFO, CINHAL, and the Central Register of Controlled Trials. The primary outcomes will be changes in mental health conditions (e.g., depression, anxiety, stress, quality of life), behavioral health conditions (e.g., substance use, smoking, sexual behavior, eating behavior, medication adherence), and physical health conditions (e.g., coping with cancer, menopausal symptoms, arthritis pain). Secondary outcomes will be changes in physical activity. Two reviewers will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion with a third reviewer. A narrative synthesis without meta-analysis will be conducted. The strength of the body of evidence will be assessed using GRADE. The risk of bias in individual studies will be appraised using the Cochrane Risk of Bias 2.0 tool. Potential sources of gender bias in included studies will be considered at all stages of the planned review. DISCUSSION: This review will contribute to the literature by providing evidence on the effectiveness of eHealth counseling and coaching programs delivered to adults in a group format. SYSTEMATIC REVIEW REGISTRATION: The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO: CRD42020187551 ).
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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 | 0.088 | 0.095 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.026 | 0.017 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.008 |
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".