Impact of a Digital Counselling Program with an Integrated Social Support Network for Self-care on Mental Health in Chronic Kidney Disease and Chronic Heart Failure
Bibliographic record
Abstract
ODYSSEE-vCHAT is a novel intervention combining digital counselling (ODYSSEE) with social network support (vCHAT) to increase self-care behaviours to improve patient prognosis and psychological well-being. The role of social support in digital self-care programs is understudied. The primary objective was to assess the impact of vCHAT engagement on mental health at 4 months using the Mental Component Summary (MCS) of the 36-Item Short-Form Survey. Secondary outcomes included the MCS subscales, the 9-Item Patient Health Questionnaire, the Revised 6-Item UCLA Loneliness Scale, and the ENRICHD Social Support Instrument. Greater engagement was associated with higher composite and Vitality and Role-Emotional MCS scores. Individuals with greater vCHAT usage were less likely to express depressive symptoms. This study demonstrated the therapeutic benefit of vCHAT on psychological well-being. It added to our understanding of digital health interventions aimed at optimizing patient health-related quality-of-life. These findings will support a large-scale randomized controlled trial.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".