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Record W4402731786 · doi:10.1002/trc2.12488

Assessing social connection for long‐term care home residents: A scoping review of measure content

2024· review· en· W4402731786 on OpenAlexafffund
Madalena P. Liougas, Andrew Sommerlad, Hannah M. O’Rourke, Hannah Chapman, Neha Dewan, Katherine S. McGilton, Jennifer Bethell

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2024
Typereview
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of AlbertaToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersUniversity of TorontoHealth CanadaUniversity College LondonToronto Rehabilitation InstituteNational Institute for Health and Care ResearchNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchFondation Brain CanadaCanadian Bee Research FundGovernment of CanadaAlzheimer's Association
KeywordsTerm (time)Measure (data warehouse)Long-term careContent (measure theory)Connection (principal bundle)GerontologyPsychologyMedicineNursingComputer scienceEngineeringData miningMathematics

Abstract

fetched live from OpenAlex

INTRODUCTION: Social connection comprises distinct but interrelated aspects describing how individuals connect to each other. Various measures have assessed multiple aspects of social connection in long-term care (LTC) home populations, but they use inconsistent terminology, making it unclear what aspects are measured. This scoping review describes how social connection is assessed by measures that have been used in LTC home residents. METHODS: This review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Two systematic literature searches combining search terms for social connection AND LTC home residents AND measurement properties were conducted in eight electronic databases from inception to April 2022. Included studies reported the development or psychometric testing of measures which assessed social connection in LTC home residents. A content analysis with a deductive-inductive approach was used to analyze the measures' content and an adapted Framework Method was used for data management. Findings report each measure's items and the assessed aspects of social connection. Dementia and non-dementia-specific measures had content, administration, and scoring compared. RESULTS: From 8753 records, 58 studies reporting on 14 dementia-specific and 28 non-dementia-specific social connection measures were identified, including complete measures, subscales, and single items. These measures assessed social network (52.4%), social isolation (11.9%), social interaction (47.6%), social engagement (31.0%), social support (33.3%), social connectedness (21.4%), and loneliness (9.5%). A total of 27 (64.3%) of the measures included more than one aspect of social connection. Dementia-specific measures most often assessed social interaction whereas non-dementia-specific measures most often assessed social network, social interaction, and social support. Dementia-specific measures typically relied on a proxy response, whereas non-dementia-specific measures more often used self-report. DISCUSSION: Existing social connection measures in LTC home settings operationalize seven aspects of social connection and differ according to the target population (dementia or non-dementia-specific). These findings will inform future measure selection and development. Highlights: Social connection is important to long-term care (LTC) home residents' quality of life.Social connection has been assessed by quantifying/describing relationships.Existing measures usually assess more than one aspect of social connection.These aspects cover several interlinked observed or experienced domains.Dementia and non-dementia-specific measures differ in assessing social connection.

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)0.049
metaresearch head score (Gemma)0.166
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.049
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.166
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.010
Bibliometrics0.0300.027
Science and technology studies0.0020.003
Scholarly communication0.0050.006
Open science0.0030.004
Research integrity0.0030.002
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 head0.795
GPT teacher head0.686
Teacher spread0.109 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations6
Published2024
Admission routes2
Has abstractyes

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