An Awareness, Courage, and Love Online Group Intervention for Chinese Older Adults in the Post-Pandemic Era: Study Protocol for a Randomised Controlled Trial
Bibliographic record
Abstract
Background. Social connections not only contribute to psychological and emotional well-being but also positively impact physical health, with social isolation and loneliness linked to early mortality and detrimental health outcomes. Objectives. This study aims to evaluate an online Awareness, Courage, and Love (ACL) group intervention designed to enhance social connectedness and subjective well-being while reducing loneliness, depression, and anxiety among older adults. Methods. This randomised controlled trial (RCT) will involve an intervention group receiving a 2 h ACL session via videoconferencing. Eligible participants selected after screening will be assigned randomly to either a treatment or waitlist-control group. Participants in both conditions will complete the assessments at three time points, including baseline, post-intervention, and one-month follow-up. Tools for assessing the concerned variables include the Inclusion of Other in the Self Scale, de Jong Gierveld Loneliness Scale, Patient Health Questionnaire-9 (PHQ-9), Generalised Anxiety Disorder 2-item (GAD-2) Scale, and World Health Organisation—Five Well-Being Index (WHO-5). Conclusions. This study will offer a robust framework for investigating the impact of the online ACL intervention on loneliness and social connectedness among Chinese older adults. The result of this study will reach theoretical, empirical, practical, and teaching significance on mental health care strategies for Chinese older adults.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.073 | 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".