‘But they’re happening to you at the wrong time’: Exploring young adult women’s reflections on serious illness through photovoice
Bibliographic record
Abstract
Although serious illness is often associated with aging, many young adults are affected by various life-threatening and chronic illnesses, and thus have experiences that do not correspond to socio-cultural expectations for young adulthood. In this article, we describe a qualitative study exploring young adult women’s experiences of serious illness. Ten participants diagnosed with a life-threatening or chronic illness in the previous three years participated in phenomenological interviews and photovoice project that focused on what it is like to be seriously ill during young adulthood. Our analysis reveals that participants experienced serious illness with respect to their position in the life course; specifically, participants perceived ill health as being inconsistent with young adulthood. This finding is illustrated by three inter-related themes: feeling abnormal and ‘off time,’ realizing vulnerabilities, and renegotiating expectations for young adulthood and the future. We propose that these themes offer evidence of how illness is experienced within the broader socio-cultural context of individuals’ lives. We conclude that social workers involved in supporting this population are well positioned to address life course disruptions brought about by illness and aid in negotiating ill health with respect to expectations for young adulthood.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".