Trajectories of social isolation in adult survivors of childhood cancer
Bibliographic record
Abstract
PURPOSE: Long-term childhood cancer survivors may be at increased risk for poor social outcomes as a result of their cancer treatment, as well as physical and psychological health problems. Yet, important challenges, namely social isolation, are not well understood. Moreover, survivors' perspectives of social isolation as well as the ways in which this might evolve through young adulthood have yet to be investigated. The purpose of this research was to describe the trajectories of social isolation experienced by adult survivors of a childhood cancer. METHODS: Data from 30 in-depth interviews with survivors (9 to 38 years after diagnosis, currently 22 to 43 years of age, 60 % women) were analyzed using qualitative, constant comparative methods. RESULTS: Experiences of social isolation evolved over time as survivors grew through childhood, adolescence and young adulthood. Eleven survivors never experienced social isolation after their cancer treatment, nor to the present day. Social isolation among 19 survivors followed one of three trajectories; (1) diminishing social isolation: it got somewhat better, (2) persistent social isolation: it never got better or (3) delayed social isolation: it hit me later on. CONCLUSIONS: Knowledge of when social isolation begins and how it evolves over time for different survivors is an important consideration for the development of interventions that prevent or mitigate this challenge. IMPLICATIONS FOR CANCER SURVIVORS: Assessing and addressing social outcomes, including isolation, might promote comprehensive long-term follow-up care for childhood cancer survivors.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".