Adolescents' Perceptions, Attitudes and Experiences with Cancer in Southwestern Uganda
Bibliographic record
Abstract
Background: Adolescents’ perceptions, attitudes, and lived experiences regarding cancer diagnosis significantly influence their quality of life and treatment adherence. To inform the formulation of tailored interventions, we explored these factors among adolescents receiving care at a sub-Saharan African health facility. Methods: We conducted a qualitative study from July 2022 to December 2022, at Mbarara Regional Referral Hospital in western Uganda. In-depth interviews were held with 30 adolescents aged 10–17 years who had been diagnosed with cancer. Using NVivo 12 software, a codebook and coding framework were developed to generate themes aligned with study objectives. Ethical approval was obtained from the Research and Ethics Committee of Mbarara University of Science and Technology. Results: Participants had a median age of 13.5 years; 19 were male. Diagnoses included leukemia (13), lymphoma (10) solid tumors (7). Initial. perceptions and attitudes towards their diagnosis were predominantly negative but improved over time as they received information and treatment. Perceptions and attitudes were poorer among those responding poorly to treatment and those who had had extremely negative experiences. Negative experiences included body disfigurement, social challenges, emotional distress, physical pain, and interrupted education. Positive experiences included improvement in symptoms and support from health workers and their families. Conclusion: Adolescents initially exhibit poor perceptions and attitudes towards their cancer diagnosis, which tend to improve with treatment and support. Their experiences are mixed, highlighting the need for specialized education and counselling services to address knowledge gaps, reduce negative attitudes, and improve overall care outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 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".