Teen online problem solving for teens with traumatic brain injury: Rationale, methods, and preliminary feasibility of a teen only intervention.
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: To describe the Teen Online Problem Solving-Teen Only (TOPS-TO) intervention relative to the original Teen Online Problem Solving-Family (TOPS-F) intervention, to describe a randomized controlled trial to assess intervention efficacy, and to report feasibility and acceptability of the TOPS-TO intervention. Research method and design: This is a multisite randomized controlled trial, including 152 teens (49 TOPS-F, 51 TOPS-TO, 52 IRC) between the ages of 11-18 who were hospitalized for a moderate to severe traumatic brain injury in the previous 18 months. Assessments were completed at baseline, 6-months post baseline, and 12-months post baseline. Data discussed include adherence and satisfaction data collected at the 6-month assessment (treatment completion) for TOPS-F and TOPS-TO. RESULTS: Adherence measures (sessions completed, dropout rates, duration of treatment engagement, and rates of program completion) were similar across treatment groups. Overall, teen and parent reported satisfaction was high and similar across groups. Teens spent a similar amount of time on the TOPS website across groups, and parents in the TOPS-F spent more time on the TOPS website than those in the TOPS-TO group (p = .002). Parents in the TOPS-F group rated the TOPS website as more helpful than those in the TOPS-TO group (p = .05). CONCLUSIONS/IMPLICATIONS: TOPS-TO intervention is a feasible and acceptable intervention approach. Parents may perceive greater benefit from the family based intervention. Further examination is required to understand the comparative efficacy in improving child and family outcomes, and who is likely to benefit from each approach. (PsycINFO Database Record
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".