Subjective Happiness, Health and Quality of Life and Their Sociocultural Correlates among Younger Population in Malawi
Bibliographic record
Abstract
Public health research and policy in sub-Saharan Africa are generally disease-oriented, with the focus being largely confined within the biological determinants of health. So far, little attention has been given to developing a more health-oriented approach by emphasising the psychosocial dimensions of health, especially among the younger population. To this regard, we conducted the present study to assess the prevalence and sociocultural correlates of perceived happiness, health, and life satisfaction among the adolescent and young (15–24 years) population in Malawi. We analysed cross-sectional data on 12,610 men and women based on a Malawi multiple indicator cluster survey conducted in 2013–2014. Data were analysed using descriptive and multivariable regression methods. According to the findings, more than 80% of the men and women reported being satisfied about happiness, health, and life. Multivariate analysis showed an inverse relationship between being currently or formerly married and perceived happiness. Ethnic disparities in perceived health and happiness were more pronounced in men, whereas that of life satisfaction was more pronounced in women. Living in households of the highest wealth quintile was positively associated with health and life satisfaction, but not with happiness. These findings highlight the need for prioritising the psychosocial needs of the adolescent and youth populations in designing health and social policy in Malawi. The findings need to be interpreted in light of the factors specific to the sociocultural environment in Malawi.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".