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Record W4380883239 · doi:10.1002/alz.060012

Measurement of social connection in people with dementia living in care homes

2023· article· en· W4380883239 on OpenAlexaffabout
Andrew Sommerlad, Madalena P. Liougas, Gill Livingston, Katherine S. McGilton, Hannah M. O’Rourke, Jennifer Bethell

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of AlbertaUniversity Health NetworkToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsLonelinessPsychologyChecklistThematic analysisApplied psychologyQuality of life (healthcare)Social engagementReliability (semiconductor)GerontologyContent validityPsychometricsMedicineClinical psychologySocial psychologyQualitative researchCognitive psychologySociologyPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Background Social connection is a fundamental human need. For those living in long‐term care (LTC) settings, social connection influences quality of life and care. However, social connection has not been clearly conceptualized, nor is it routinely measured, in LTC. LTC residents have complex health needs, and are separated from previous social networks while residing in communal care environments, so measurement instruments need to be tailored and tested in these settings. Currently, there is no evidence‐based consensus on the best approaches to defining or measuring social connection in LTC homes. In this project, funded by an Alzheimer’s Association/Brain Canada Advancing Research on Care and Outcome Measurement grant, we aim to systematically describe all previous of social connection measures in LTC residents and evaluate their psychometric properties. Methods We searched eight databases until November 18th, 2021. We used the COnsensus‐based Standards for the selection of health Measurement INstruments (COSMIN) filter to identify studies reporting instrument measurement properties. We included primary studies reporting ≥1 psychometric property (including validity, reliability, internal consistency, responsiveness) of a measure of social connection (including social engagement/ support/ networks/ isolation, loneliness, and other related constructs), tested among LTC residents. Two reviewers will independently screen titles and abstracts and then conduct full text review. To assess measure form and content, we will describe the measures and their target settings, and conduct a thematic content analysis on all items. To evaluate psychometric properties, we will assess each measure using the COSMIN risk of bias checklist and summarize the evidence for the nine measurement properties. We will rate the measure overall using a Grading of Recommendations Assessment, Development, and Evaluation approach. Results After removing duplicates, our search yielded 5945 studies. We excluded 5818 studies after screening titles and abstracts, leaving 127 papers for full text review. Conclusions We will present results of this ongoing systematic review on content and psychometric properties of social connection measures in LTC residents. Through this presentation, we will elicit feedback from stakeholders on our findings to date. This feedback will inform our development of a new measure to assess social connection in people living in LTC homes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.076
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0140.013
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.039
GPT teacher head0.312
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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