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“We see each other from a distance”: Neighbourhood social relationships during the COVID-19 pandemic matter for older adults’ social connectedness

2022· article· en· W4281741718 on OpenAlexaffabout
Callista A. Ottoni, Meghan Winters, Joanie Sims‐Gould

Bibliographic record

VenueHealth & Place · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityVancouver Coastal Health
Fundersnot available
KeywordsSocial connectednessLonelinessNeighbourhood (mathematics)PsychologySocial isolationInterpersonal tiesSocial distanceSocial psychologyInterpersonal communicationCoronavirus disease 2019 (COVID-19)PandemicGerontologySociologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: We extend previous research to illustrate how individual, interpersonal and neighbourhood factors in a high-density urban setting in Vancouver, Canada, shape social connectedness experiences of community-dwelling older adults during the first wave of the COVID-19 pandemic. METHODS: We conducted 31 semi-structured interviews and collected objective measures of loneliness and social connectedness (surveys). RESULTS: Three dimensions of the neighbourhood environment influenced social connectedness: (i) interactions with neighbours, (ii) involvement with neighbourhood-based organizations, and (ii) outdoor pedestrian spaces. Seventy-one percent of participants felt a strong sense of belonging to their local community, while 39% were classified as high or extremely lonely. SUMMARY: Many participants leveraged pre-existing social ties to maintain connections during the pandemic. However, volunteer outreach was vital for more isolated older adults. Although many participants felt lonely and isolated at times, the relative ease and accessibility with which they could connect with others in their neighbourhood environment, may have helped mitigate persistent loneliness. CONCLUSION: Strategies that foster social connectedness over the longer term, need to prioritize the needs of older adults who face multiple barriers to equitable social participation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0150.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.364
Teacher spread0.296 · 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

Citations46
Published2022
Admission routes2
Has abstractyes

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