Measures of social connectedness in adult populations: a systematic review
Bibliographic record
Abstract
BACKGROUND: Poor social connectedness has been identified as a risk factor for poor mental health but there is a lack of standardisation in how it is measured. This systematic review aimed to identify suitable measures of social connectedness for use in UK adult general populations. METHODS: Searches were undertaken in two stages to identify: (1) measures of social connectedness from review articles and grey literature and (2) studies reporting on the psychometric properties of the identified measures. Grey literature and five databases were searched: MEDLINE, Embase and PsycINFO; CINAHL and Web of Science. Studies based on UK adult general populations (16-65 years) or other English language speaking countries with similar cultures (US, Canada, Ireland, Australia and New Zealand) were included. Psychometric evidence was extracted relating to six general domains: conceptual model, content validity, reliability, construct validity, scoring and interpretability, and respondent burden and presentation. A narrative synthesis summarised these psychometric properties. RESULTS: Stage (1) 2,396 studies were retrieved and, 24 possible measures of social connectedness were identified; stage (2) 6,218 studies were identified reporting on psychometrics of identified measures and 22 studies were included. These studies provided psychometric evidence for 10 measures, and we did not find psychometric studies for the other identified measures. Six measures (6/10, 60%) reported assessing loneliness and four (4/10, 40%) reported assessing social support but there was a degree of overlap between the assessments of each concept. There was good evidence of reliability across measures, 90% (9/10) had adequate internal consistency, but evidence of content validity was only available for one scale. Five measures (5/10, 50%) reported on at least half of the psychometric criteria, and these were: UCLA-3 (for loneliness), and MSPSS, F-SozU K-6, SPS-10 and SPS-5 (for social support). CONCLUSIONS: This review identified ten social connectedness measures, and identified UCLA-3, MSPSS, F-SozUK-6, SPS-10, and SPS-5 as having the most robust psychometric properties for the UK adult population. Further testing is required to establish content validity, and to clarify the definition and conceptualisation of social connectedness, to enable standardisation in the approach to measuring social connectedness.
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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 | 0.017 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".