Computer-Mediated Support for Adolescents With Cerebral Palsy or Spina Bifida
Bibliographic record
Abstract
Social support plays a key role in improving health outcomes for children with chronic conditions. Internet connections are an important component of adolescents' social networks and may overcome geographic and environmental barriers for those with disabilities. This article focuses on the processes associated with a 6-month online support intervention for adolescents with cerebral palsy or spina bifida. Specifically, the purpose was to determine the extent to which adolescents used an online peer support intervention, the processes used, and the perceived benefits and satisfaction with the intervention. Five peer mentors with the same disabilities provided information, affirmation, and emotional support. The online environment created a safe space to foster reciprocal interpersonal connections and appropriate social comparison. Two-thirds of the participants viewed the computer-mediated support intervention as fun. Factors influencing the perceived utility of the intervention included typing speed, cognitive skills, and perceived need for additional support. Girls were significantly more likely to contribute messages than were boys. Peer mentors wished that this type of support program had been available when they were teens, appreciated the supportive elements, and reported learning from the teen participants. Health professionals wanting to implement online support need to consider the age and ability levels of participants and the optimal length and format of the support program.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".