Contrasting Internet and Face-to-Face Focus Groups for Children with Chronic Health Conditions: Outcomes and Participant Experiences
Bibliographic record
Abstract
In this study the authors examined Internet-mediated qualitative data collection methods among a sample of children with chronic health conditions. Specifically, focus groups via Internet technology were contrasted to traditional face-to-face focus groups. Internet focus groups consisted of asynchronous text-based chat rooms lasting a total of one week in duration. Participants comprised 23 children with cerebral palsy, spina bifida, or cystic fibrosis, who were assigned to either an Internet or face-to-face focus group. Focus group analysis and follow-up participant interviews identified a range of content outcomes and processes as well as participant experiences and preferences. Findings yielded differences in terms of the volume and nature of online and face-to-face data, and participants' affinity to focus group modality appeared to reflect differences in participant expectations for social engagement and interaction. This study identifies both benefits and limitations of asynchronous, text-based online focus groups. Implications and recommendations are discussed.
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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 | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".