P66: A systematic review of measures of social connection for people living in long-term care homes
Bibliographic record
Abstract
Background:Social connection is important for health, quality of life and care in long-term care (LTC) homes. However, research on how to improve social connection in LTC has been limited by lack of consensus on best approaches to measurement.Research Objective:We will present a systematic review of measures of social connection developed for use in LTC residents, which aims to identify all existing measures and evaluate their measurement properties including structural validity, internal consistency, reliability and construct validity.Method:We are following Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) systematic review methods. We searched multiple bibliographic databases from inception to November 2021 for studies that were conducted in LTC resident populations, quantified any aspect(s) of social connection, and reported at least one psychometric property for the measure(s) of social connection. We conducted a second targeted search in April 2022 based on our list of identified measures, supplemented with a list of measures used in previous research in this population. We are currently evaluating the measurement properties reported for each identified measure in accordance with COSMIN guidelines.Preliminary results of the ongoing study:We have identified 68 studies reporting on 35 measures used to assess multiple aspects of social connection in LTC homes. The majority (n=25) were measures of quality of life, wellbeing or life satisfaction, which included a social connection subdomain, whilst only 10 measures specifically target social connection. From our pooled evaluation of 20 measures to date, we have found that 20% (n=4) have sufficient evidence of structural validity, 15% (n=3) have sufficient internal consistency, 25% (n=5) have sufficient reliability, and 15% (n=3) have sufficient construct validity.Conclusion:Many measures have been used to assess social connection in LTC settings, but few are specifically designed for this purpose and they often have insufficient evidence for psychometric properties. This review will provide detailed evidence of the quality of these measures to enable future researchers to prioritise higher quality tools and will inform our development of a new person-centred social connection measurement tool for LTC residents in the Social Connection in Long-Term Care Home Residents (SONNET) study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".