Management of social isolation and loneliness in community-dwelling older adults: protocol for a network meta-analysis of randomised controlled trials
Bibliographic record
Abstract
INTRODUCTION: Social isolation and loneliness in older adults are significant public health issues. Various interventions such as exercise programmes or social activities are used in the management of social isolation and loneliness in older adults. Network meta-analysis (NMA) provides effect estimates for all comparisons by considering the relative efficacy of multiple intervention alternatives. Therefore, this study will determine the comparative efficacy of intervention to alleviate social isolation and loneliness of older adults in community dwelling by comparing direct and indirect interventions through systematic review and NMA. METHODS AND ANALYSIS: We will include all relevant randomised controlled trials for interventions of social isolation and loneliness in older adults written in English without any limitation of publication date through electronic databases: MEDLINE via OVID, EMBASE, Cochrane Central Registry of Controlled Trials (CENTRAL), PsycINFO and CINAHL. Independent teams of reviewers will screen trial eligibility, collect data, identify duplication and assess risk of bias, by using the Cochrane revised risk of bias tool. The interventions for the management of social isolation and loneliness will be included. The primary outcome is social isolation. The secondary outcomes are loneliness and health-related quality of life. We will conduct an NMA through a Bayesian hierarchical model, by testing assumption (ie, transitivity) for NMA. We will also estimate the ranking probabilities for all interventions at each possible rank for each intervention. For estimation of each intervention efficacy, we will assess the certainty and credibility using the Grading of Recommendations Assessment, Development and Evaluation approach. ETHICS AND DISSEMINATION: Ethics approval will not be obtained for this systematic review as it will be conducted with published papers. The review results will be presented at a field-specific conference and published in a relevant peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42020155789.
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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 | 0.103 | 0.191 |
| Meta-epidemiology (narrow) | 0.009 | 0.006 |
| Meta-epidemiology (broad) | 0.027 | 0.037 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.081 | 0.010 |
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".