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Record W4295990477 · doi:10.2196/41255

Older Adults Living in Disadvantaged Areas: Protocol for a Mixed Methods Baseline Study on Homes, Quality of Life, and Participation in Transitioning Neighborhoods

2022· article· en· W4295990477 on OpenAlexvenueno aff
Marianne Granbom, Håkan Jönson, Anders Kottorp

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantagedContext (archaeology)Quality of life (healthcare)GerontologyPsychologyQualitative researchQualitative propertyMedicineGeographySociologyEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Swedish policy states that older adults should be able to age safely with continued independence and lead active lives. However, this plays out differently in different Swedish municipalities depending upon degree of demographic change, globalization, and urbanization. Internationally, older adults living in disadvantaged areas have worse physical and mental health, activity restrictions, and reduced life expectancy. In Sweden, research on how disadvantaged areas impact older adults' quality of life is virtually nonexistent. We argue that disadvantaged areas exist in both urban and rural contexts. OBJECTIVE: We aimed to investigate how older adults' homes and neighborhoods influence their community participation, quality of life, identity, and belonging in urban and rural disadvantaged areas in Sweden, and how these person-context dynamics are experienced by older adults in transitioning neighborhoods. METHODS: The study has a mixed methods design and includes 3 phases. Adults 65 years and older living in certain urban and rural disadvantaged areas in the south of Sweden will be included. Phase 1 is an interview study in which qualitative data are collected on neighborhood attachment, identity, and belonging through semistructured interviews and photo-elicitation interviews with 40 subjects. A variety of qualitative data analysis procedures are used. In phase 2, a survey study will be conducted to explore associations between observable and self-rated aspects of housing and neighborhood (physical, social, and emotional), participation, and quality of life; 400 subjects will be recruited and added to the 40 phase-1 subjects for a total of 440. The survey will include standardized measures and study-specific questions. Survey data will be analyzed with mainstream statistical analyses and structural equation modeling to understand the interactions between quality of life, home and neighborhood factors, and sociodemographic factors. In phase 3, the integration study, survey data from the 40 participants who participated in both data collections will be analyzed together with qualitative data with a mixed methods analysis approach. RESULTS: As of the submission of this protocol (August 2022), recruitment for the interview study is complete (N=39), and 267 participants have been recruited and have completed data collection in the survey study. We expect recruitment and data collection to be finalized by December 2022. CONCLUSIONS: With an increasing proportion of older adults, an increasing number of disadvantaged areas, and an increasing dependency ratio in more than 50% of Swedish municipalities, these municipalities are transforming and becoming increasingly segregated. This study will add unique knowledge on what it is like to be older in a disadvantaged area and deepen knowledge on housing and health dynamics in later life. Further, the design of the current study will allow future follow-up studies to facilitate longitudinal analysis (if funding is granted) on aging in a transforming societal context. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41255.

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)0.023
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.558
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.223
GPT teacher head0.618
Teacher spread0.395 · 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 designObservational
Domainnot available
GenreProtocol

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

Citations7
Published2022
Admission routes1
Has abstractyes

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