Effect of personalised citizen assistance for social participation (APIC) on older adults’ health and social participation: study protocol for a pragmatic multicentre randomised controlled trial (RCT)
Bibliographic record
Abstract
Introduction The challenges of global ageing and the growing burden of chronic diseases require innovative interventions acting on health determinants like social participation. Many older adults do not have equitable opportunities to achieve full social participation, and interventions might underempower their personal and environmental resources and only reach a minority. To optimise current practices, the Accompagnement-citoyen Personnalisé d’Intégration Communautaire (APIC), an intervention demonstrated as being feasible and having positive impacts, needs further evaluation. Methods and analysis A pragmatic multicentre, prospective, two-armed, randomised controlled trial will evaluate: (1) the short-term and long-term effects of the APIC on older adults’ health, social participation, life satisfaction and healthcare services utilisation and (2) its cost-effectiveness. A total of 376 participants restricted in at least one instrumental activity of daily living and living in three large cities in the province of Quebec, Canada, will be randomly assigned to the experimental or control group using a centralised computer-generated random number sequence procedure. The experimental group will receive weekly 3-hour personalised stimulation sessions given by a trained volunteer over the first 12 months. Sessions will encourage empowerment, gradual mobilisation of personal and environmental resources and community integration. The control group will receive the publicly funded universal healthcare services available to all Quebecers. Over 2 years (baseline and 12, 18 and 24 months later), self-administered questionnaires will assess physical and mental health (primary outcome; version 2 of the 36-item Short-Form Health Survey, converted to SF-6D utility scores for quality-adjusted life years), social participation (Social Participation Scale) and life satisfaction (Life Satisfaction Index-Z). Healthcare services utilisation will be recorded and costs of each intervention calculated. Ethics and dissemination The Research Ethics Committee of the CIUSSS Estrie – CHUS has approved the study (MP-31-2018-2424). An informed consent form will be read and signed by all study participants. Findings will be published and presented at conferences. Trial registration number NCT03161860 ; Pre-results.
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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 | 0.056 | 0.049 |
| Meta-epidemiology (narrow) | 0.009 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.075 | 0.013 |
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".