Evidence map›Paper›PMID 39639260›Full record

SynthesisBMC public health2024

Measures of social connectedness in adult populations: a systematic review.

Ruth Plackett, Joe Hulin, Clara Mukuria, Mark Clowes, Sheena E Ramsay, Liam Spencer, Emma A Adams, Jennifer Dykxhoorn, Kate Walters, David P J Osborn and 3 more

Abstract readSystematic Review
In one paragraph

Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Listening to a Consonant Chord Progression during Live Face-to-Face Gaze Enhances Neural Activity in Social Systems.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  4. Creative ForcesFrontiers in psychiatry · 2026
    Review
  5. Review
  6. Editorial: Pain and relationships.Frontiers in pain research (Lausanne, Switzerland) · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Ruth Plackett *UCL Research Department of Primary Care & Population Health, Royal Free Hospital, University College London, Upper 3rd Floor, Rowland Hill Street, London, NW3 2PF, UK. ruth.plackett.15@ucl.ac.uk.
Joe Hulin *University of Sheffield, Sheffield, UK.
Clara MukuriaUniversity of Sheffield, Sheffield, UK.
Mark ClowesUniversity of Sheffield, Sheffield, UK.
Sheena E RamsayNewcastle University, Newcastle upon Tyne, UK.
Liam SpencerNewcastle University, Newcastle upon Tyne, UK.
Emma A AdamsNewcastle University, Newcastle upon Tyne, UK.
Jennifer DykxhoornUniversity College London, London, UK.
Kate WaltersUniversity College London, London, UK.
David P J OsbornUniversity College London, London, UK.
Victoria ZamperoniMental Health Foundation, London, UK.
Oliver JonesMcPin Foundation, London, UK.
Scott WeichUniversity of Sheffield, Sheffield, UK.

Funding

School for Public Health Research PD-SPH-2015
6 · The paper itself

Abstract

backgroundPoor 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.

methodsSearches 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.

resultsStage (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).

conclusionsThis 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.

Indexed as

PsychometricsAdolescentAdultAgedHumansLonelinessMiddle AgedReproducibility of ResultsSocial SupportUnited KingdomYoung AdultLonelinessPsychometric propertiesPublic healthReviewSocial connectednessSocial support

Identifiers

PMID39639260
PMCPMC11622465

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.