Development of the Adolescent Cancer Suffering Scale
Bibliographic record
Abstract
BACKGROUND: While mortality due to pediatric cancer has decreased, suffering has increased due to complex and lengthy treatments. Cancer in adolescence has repercussions on personal and physical development. Although suffering can impede recovery, there is no validated scale in French or English to measure suffering in adolescents with cancer. OBJECTIVE: To develop an objective scale to measure suffering in adolescents with cancer. METHODS: A methodological design for instrument development was used. Following a MEDLINE search, semistructured interviews were conducted with adolescents 12 to 19 years of age who had undergone four to six weeks of cancer treatment, and with a multidisciplinary cohort of health care professionals. Adolescents with advanced terminal cancer or cognitive impairment were excluded. Enrollment proceeded from the hematology-oncology department⁄clinic in Montreal, Quebec, from December 2011 to March 2012. Content validity was assessed by five health care professionals and four adolescents with cancer. RESULTS: Interviews with 19 adolescents and 16 health care professionals identified six realms of suffering: physical, psychological, spiritual, social, cognitive and global. Through iterative feedback, the Adolescent Cancer Suffering Scale (ACSS) was developed, comprising 41 questions on a four-point Likert scale and one open-ended question. Content validity was 0.98, and inter-rater agreement among professionals was 88% for relevance and 86% for clarity. Adolescents considered the scale to be representative of their suffering. CONCLUSIONS: The ACSS is the first questionnaire to measure suffering in adolescents with cancer. In future research, the questionnaire should be validated extensively and interventions developed. Once validated, the ACSS will contribute to promote a holistic approach to health with appropriate intervention or referral.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".