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Record W4402422965 · doi:10.1016/j.heliyon.2024.e37676

Dwelling characteristics and mental well-being in older adults: A systematic review

2024· review· en· W4402422965 on OpenAlexaboutno aff
Sina Sharifi, Hadis Mosafer, Mahmoud Rahmati, Kimia Babaei Khorzoughi, Akram Parandeh

Bibliographic record

VenueHeliyon · 2024
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsGerontologyPsychologyMental healthMedicinePsychotherapist

Abstract

fetched live from OpenAlex

The increasing prevalence of mental health challenges in older adults underscores the need for a comprehensive understanding of the interplay between dwelling characteristics and mental health outcomes. This systematic review aims to investigate house characteristics associated with mental well-being in older adults. The review meticulously explores existing literature from databases such as PubMed, Scopus, Web of Science, and the Google Scholar search engine. The Newcastle-Ottawa Scale (NOS) was utilized to assess the quality of the included articles. Out of an initial 1182 references, 21 pertinent articles published between 2002 and 2023 were included in the study. While the geographical scope was global, a notable concentration of studies was observed in China. The synthesis of studies reveals that specific attributes of dwelling characteristics, such as high-rise and multi-floor houses, larger house size, high house quality, bathing facilities, and the use of clean fuels for heating and cooking, positively impact mental health outcomes in older adults. However, inconsistent results were found regarding the impact of construction materials on mental health outcomes. Further research is warranted to deepen our understanding of the intricate relationship between construction materials and mental health outcomes. These findings underscore the importance of considering specific dwelling characteristics in designing interventions to enhance the mental well-being of older adults, necessitating targeted strategies for creating age-friendly living environments.

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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.136
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.331
Teacher spread0.309 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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