HOW YOUNG PEOPLE COPE WITH CHRONIC KIDNEY DISEASE: LITERATURE REVIEW
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) is a complex, long-term condition occurring in all age groups. It has been reported that the incidence of renal replacement therapy in young people is 7-8 per million population. Notwithstanding those individuals who may receive a donor kidney, many individuals may be disenfranchised by perceptions of helplessness and feelings of powerlessness against a backdrop of diminished health outlook, consequently impacting on capacity for effective coping. AIM: The aim of this review is to explore how young people cope with CKD. METHODS: Three hundred and thirty-seven abstracts were identified. Sixty-three papers were cross-examined using a Critical Appraisal Skills Checklist Tool. RESULTS: Young people face various demands; these may be episodic or ongoing, depending on health and circumstance. The themes this review uncovers are: 'Lack of a Coping Definition'; 'Coping Strategies in Young People'; and 'Barriers to the Understanding of Coping in Young People'. CONCLUSION: More qualitative research is vital to retrieve 'real-life' perceptions from young people coping with kidney disease to identify how care should be made more explicit for them.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".