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Record W3113356692 · doi:10.2147/rmhp.s283145

<p>Current Status and Challenges of Community-Based Elderly Care Centers in Chongqing, China: A Cross-Sectional Study</p>

2020· article· en· W3113356692 on OpenAlexaboutno aff
Ziyi Yang, Yi Jiang, Min Wang, Huan Zeng

Bibliographic record

VenueRisk Management and Healthcare Policy · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
Fundersnot available
KeywordsChinaApartmentCluster samplingSocioeconomicsPopulationQuarter (Canadian coin)GeographyGovernment (linguistics)Environmental healthDescriptive statisticsBusinessGerontologyMedicineEngineeringStatisticsCivil engineeringMathematicsSociology

Abstract

fetched live from OpenAlex

PURPOSE: China is facing various societal pressures owing to its rapidly aging population. In order to provide evidence-based suggestions to promote elderly care, this study investigated the community-based elderly care centres (CBECCs) in Chongqing of China, focusing on the site selections, physical environment, facilities, and operation. METHODS: All CBECCs in a district of Chongqing were analysed via a single-stage cluster sampling survey design. Descriptive statistics were used to analyse the data. RESULTS: A total of 69 CBECCs (60 government-run and 9 collective-run centres) were identified and analysed. Most site selections were reasonable. CBECCs that were located inside of apartment complexes with entrance guards, not located on main roads, and near a market were more popular. Only 4 (13.3%) CBECCs that were not located on the ground floor were equipped with elevators. A small number of CBECCs were near a noise pollution (10.1%) or far from a medical institution (11.6%). Nearly half (42.7%) of CBECCs only had an indoor area of <200 m2. Nearly all CBECCs had sufficient ventilation, natural lighting, and sufficient floor-to-floor height. 51.5% and 88.4% of the CBECCs fully met the criteria of 'four rooms and one canteen' and 'eight functional zones', but no significant difference was found in terms of the number of people served per month between the CBECCs that met the criteria and those that did not. A quarter of the CBECCs were operated by part-time staff. Only half provided home services (54.5%). The median of average number of people they served every month was 100 (interquartile range = 10-300). CONCLUSION: Certain problems existed in the current CBECCs. Better elderly care especially calls for adequate elevator establishment, sufficient indoor and outdoor space, appropriate facilities and service, qualified managers and caregivers. A feasible and evidence-based plan to optimize the physical environment and facilities, functional layout and service provision is crucial to improve the CBECC service.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.047
GPT teacher head0.358
Teacher spread0.311 · 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
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

Citations16
Published2020
Admission routes1
Has abstractyes

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