Content Analysis of Online Focus Group Discussions are a Valid and Feasible Mode When Investigating Sensitive Topics Among Young Persons With a Cancer Experience
Bibliographic record
Abstract
BACKGROUND: Clinical research often lacks participants of young age. Adding to the small amount of scientific studies that focus on the population entering adulthood, there are also difficulties to recruit them. To overcome this, there is a need to develop and scientifically evaluate modes for data collection that are suitable for adolescents and young adults. With this in mind we performed 39 online focus group discussions among young survivors of childhood cancer to explore thoughts and experiences around dating, being intimate with someone, and having children. OBJECTIVE: The aim of the study was to evaluate online focus group discussions as a mode for data collection on sensitive issues among young persons with a cancer experience. METHODS: One hundred thirty-three young persons (16-25 years) previously diagnosed with cancer, participated in 39 synchronous online focus group discussions (response rate 134/369, 36%). The mode of administration was evaluated by analyzing participant characteristics and interactions during discussions, as well as group members' evaluations of the discussions. RESULTS: Persons diagnosed with central nervous tumors (n=30, 27%) participated to a lower extent than those with other cancer types (n=103, 39%; χ 2= 4.89, P=.03). The participants described various health impairments that correspond to what would be expected among cancer survivors including neuropsychiatric conditions and writing disabilities. Even though participants were interested in others' experiences, sexual issues needed more probing by the moderators than did fertility-related issues. Group evaluations revealed that participants appreciated communicating on the suggested topics and thought that it was easier to discuss sex when it was possible to be anonymous toward other group members. CONCLUSIONS: Online focus group discussions, with anonymous participation, are suggested to be a feasible and valid mode for collecting sensitive data among young persons with a cancer experience.
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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 | 0.063 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".