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Record W4401520502 · doi:10.1111/hex.14167

‘If It Was Easy Somebody Would Have Fixed It’: An Exploration of Loneliness and Social Isolation Amongst People Who Frequently Call Ambulance Services

2024· article· en· W4401520502 on OpenAlexaff
Lisa Moseley, Jason Scott, Gayle Fidler, Gina Agarwal, Cathy Clarke, Jonathan Hammond‐Williams, Carrie Ingram, Aidan McDonnell, Tracy Collins

Bibliographic record

VenueHealth Expectations · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsMcMaster University
FundersDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsLonelinessSocial isolationIsolation (microbiology)Service (business)Social workPsychologySocial supportMedicineNursingSocial psychologyBusinessPsychiatryPolitical science

Abstract

fetched live from OpenAlex

INTRODUCTION: The aim of the study was to explore social isolation and loneliness in those who frequently contacted the ambulance service, what factors contributed to this and how unmet needs could be addressed. METHODS: Semi-structured interviews with staff from the ambulance service and service users who were identified as frequently contacting the ambulance service. Service users also completed the UCLA loneliness scale and personal community maps. Data were analysed thematically before triangulation with the UCLA loneliness scale and personal community maps. RESULTS: The final analysis was drawn from 15 staff and seven service user participants. The relationship between social isolation and loneliness and contacting the ambulance service was a contributing, but not the driving, factor in contacting the ambulance service. For service users, we identified three key themes: (1) impact on activities of daily living and loneliness and/or isolation as a result of a health condition; (2) accessing appropriate health and social care services to meet needs; (3) the link between social isolation and/or loneliness and contact with the ambulance service. The analysis of staff data also highlighted three key themes: (1) social isolation and/or loneliness in their role; (2) access to other appropriate health and social care services; (3) the impact of austerity and Covid-19 on social isolation and/or loneliness. CONCLUSIONS: Our research emphasises the complex nature of social isolation and loneliness, including the cyclic nature of poor health and social isolation and loneliness, and how this contributes to contact with the ambulance service. PATIENT OR PUBLIC CONTRIBUTION: The advisory group for the study was supported by a public and patient representative who contributed to the design of the study documentation, data analysis and authorship.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.397
Teacher spread0.333 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations8
Published2024
Admission routes1
Has abstractyes

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