Dwelling characteristics and mental well-being in older adults: A systematic review
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".