Benefits of TREINI on functional goals of children with myelomeningocele
Bibliographic record
Abstract
Abstract Introduction Children with myelomeningocele (MMC) often experience limitations that affect their daily activities and family routines. Understanding parental priorities and applying effective interventions is essential to optimize functionality and promote the overall development of these children. Objective To characterize the functional goals of children with MMC, organize them according to the F-words framework, and evaluate the effects of the TREINI Program on the improvement in these functional goals. Methods A non-randomized pilot study was con-ducted involving 26 children (ages 2-14) with MMC. The Canadian Occupational Performance Measure (COPM) was used to characterize functional goals and evaluate the benefits of the TREINI program. The protocol consisted of training functional goals in a naturalistic environment combined with the use of a flexible therapeutic suit, over three months, five times a week, for 3-4 hours per day. Descriptive statistics were used to provide the profile of priorities. Pre- and post-intervention data were analyzed using the paired t-test. Results A total of 130 goals were established by parents, among which activities of daily living (ADLs), such as functional mobility, dressing, and personal hygiene, were the most frequently set goals. More goals were associated with the terms “function” (45.8%) and “fitness” (37.5%). The TREINI program resulted in significant improvements in performance and satisfac-tion for most functional priorities (p < 0.05). Conclusion For parents of children with MMC, ADLs were identified as the main treatment priorities. The TREINI program re-sulted in significant improvements in the performance of functional goals and increased parental satisfaction.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".