Gender, the State, and a lifetime of experience: Understanding mental health dynamics among older adults
Bibliographic record
Abstract
Background There is a well-established relationship between socioeconomic position (SEP) and health among older adults, but a short-coming of existing research is its failure to link the SEP-health relationship in later life to the gendered histories of work and family life and the social contexts in which these histories unfold. Objectives Drawing on life course and welfare state theory, this research investigates the dominant patterns of labour market and family experiences over the life course (19–64 years) for current cohorts of older adults in Britain. It then examines whether mental health dynamics among older adults (65+ years) vary by gender and life course experiences, and assesses whether SEP at age 65 mediates this relationship. Data The data come from the British Household Panel Survey, and individuals born between 1927 and 1940 were included in this study (N=1552). Detailed histories of labour market attachment, occupational class, marriage(s), and dependent children were used to model life course experiences. Mental health in later life was measured using the General Health Questionnaire (GHQ-12). Analytic Approach Life course experiences in the labour market and the family were modelled using a two-stage latent class analysis. Latent growth curve methodology was then employed to model mental health trajectories and their relationship to gender, life course experiences, and SEP. Results Four latent life paths characterised the experiences of the older adults in this sample. Consistent with the social policy context in Britain in the post-World War II years, there was evidence of distinct gender patterns in role configurations at various points across the life course and in the life pathways that link these experiences over time. Mental health trajectories were patterned by life course histories; women who combined marriage and children with family care giving, or care giving followed by a transition to full-time employment, experienced significantly worse mental health at age 65, and the latter group also reported an initial improvement in mental health followed by an accelerated decline. SEP at age 65 mediated part of this relationship. Discussion These findings suggest that health dynamics are tied to life course experiences during the ‘working’ years and that greater attention to the gendered implications of welfare state policies and provisions in particular social contexts is important for understanding the life course processes associated with health inequalities among 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 | 0.004 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| 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".