Quality of life of older adults in two contrasting neighbourhoods in Accra, Ghana
Bibliographic record
Abstract
As is the case elsewhere in sub-Saharan Africa, Ghana is experiencing a rapid increase in the population of older adults. Despite their rising numbers, the living conditions and wellbeing of older Ghanaians remain woefully understudied. This paper presents the results of a study exploring the quality of life (QoL) of older adults in two contrasting neighbourhoods in Accra, Ghana. The objectives of the study were to: (1) explore and compare the QoL of older slum and non-slum dwellers in Ghana; and (2) determine the extent of QoL disparities between slum and non-slum older adults. To accomplish these objectives, we undertook a cross-sectional survey of older adults (N = 603) residing in a slum and non-slum neighbourhood. QoL was self-assessed in four domains - physical, psychological, social, and environment - using the World Health Organization (WHO) QoL assessment tool (WHOQoL-BREF). Multivariable linear regression analyses of the data revealed no statistically significant difference between the slum and non-slum respondents in physical (coeff: 0.5; 95% CI: -1.7, 2.8; p = 0.642) and psychological (coeff: -0.2; 95% CI: -3.0, 2.6; p = 0.893) QoL. However, the slum respondents reported significantly higher social QoL than the non-slum respondents (coeff: -3.2; 95% CI: -5.6, -0.8; p = 0.010), while the reverse was true in environmental QoL (coeff: 4.2; 95% CI: 2.3, 6.2; p < 0.001). The existence of strong social support systems in the slum and better housing and neighbourhood environmental conditions in the non-slum may have accounted for the observed variation in social and environmental QoL. Thus, contrary to popular discourses that vilify slums as health-damaging milieus, these findings offer a more nuanced picture, and suggest that some features of slums may constitute important health resources for older adults.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".