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Record W4391480337 · doi:10.1017/s1041610223001795

Social connection in long-term care homes

2023· article· en· W4391480337 on OpenAlexaffabout
Jennifer Bethell, Andrew Sommerlad, Hannah Chapman, Neha Dewan, Madalena P. Liougas, Hannah M. O’Rourke, Katherine S. McGilton

Bibliographic record

VenueInternational Psychogeriatrics · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of AlbertaToronto Rehabilitation InstituteUniversity of TorontoAlberta Health ServicesUniversity Health Network
Fundersnot available
KeywordsLonelinessGerontologyPsychologyLong-term careQuality of life (healthcare)Social supportSocial isolationMental healthMedicineNursingSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Background:Social connection is a basic human need and is important for quality of life and care for residents in long-term care (LTC) homes. Research has established associations between aspects of social connection (e.g., social engagement, social support and loneliness) and mental health outcomes (e.g., depression). Yet, despite living in a congregate setting, those in LTC homes often experience poor social connection. Social connection has unique considerations for LTC homes, including that most residents are living with cognitive impairment or dementia, which requires a customized measurement approach.Research Objective:The social connection in long-term care home residents (SONNET) study aims to improve measurement of social connection in LTC homes by addressing three specific questions: (1) What existing measures assess social connection in LTC homes and what are their psychometric properties? (2) What do residents, families, staff and clinicians consider to be the important elements of social connection in LTC homes? (3) Can a new measure accurately assess social connection in LTC home residents?Method:The three study questions will be addressed through: (1) A systematic review of existing measures, where measures will be characterized using content analysis and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methods; (2) Qualitative interviews with residents, families, staff and clinicians to understand important aspects of social connection, and, (3) Development and testing of a new measure of social connection in Canada and the UK.Preliminary results of the ongoing study:Previous research will be discussed, including a scoping review summarizing research evidence linking social connection to mental health outcomes as well as strategies to build and maintain social connection during the COVID-19 pandemic. The SONNET study update will include preliminary findings from the systematic review and qualitative interviews, as well as development of a conceptual model and key considerations for a new measure.Conclusion:Social connection is an important concept in LTC homes. A robust measure of social connection, developed specifically for this setting, will enable researchers and care settings to test the effects of interventions and to report outcomes at the individual-, home- and system-level.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.043
GPT teacher head0.443
Teacher spread0.400 · 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 teacher head, not a consensus.

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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