A qualitative study of the costs experienced by caregivers of children being treated for cancer in New Delhi, India
Bibliographic record
Abstract
Abstract Background The allocation of time and other resources is essential to enable the treatment of children with cancer. Evidence derived from high‐income countries showcases the significant costs families may incur impacting their finances and lifestyle. However, there is a paucity of research examining the costs of childhood cancer in India, which may impact families' decision to abandon their child's treatment. Aim The aim of this study was to explore the costs experiences by caregivers of children undergoing pediatric cancer treatment in New Delhi, India. Methods A qualitative descriptive study was conducted in three cancer institutions in New Delhi. Semistructured interviews were conducted with caregivers of children with cancer in English or Hindi. Interviews were transcribed verbatim, translated into English, and analyzed using a thematic approach. Results In total, 25 caregivers of 24 children diagnosed with cancer participated in the study. Caregivers described direct, indirect, and psychosocial costs associated with their child's treatment. The primary sources of direct costs were hospital admissions, medications, food, and travel expenses. Indirect costs involved managing their child's treatment, affecting caregivers' sleep, work hours, and time spent with other family members. Psychosocial costs included coping with the uncertainty caused by a cancer diagnosis, feelings of guilt, and sadness as well as having to watch their children suffer. Caregivers accessed a network of support to cope with their child's treatment. No families abandoned treatment or indicated that they intended to do so. Conclusions The results of this study provide avenues for health care professionals and institutions to develop interventions aimed at reducing the costs associated with cancer treatment. Further research into the relationship between various costs and treatment abandonment is needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".