Emotional health and coping in spina bifida after goal management training: A randomized controlled trial.
Bibliographic record
Abstract
OBJECTIVE: Executive function impairments are common after spina bifida (SB) and potentially have a detrimental effect on the individual's emotional health and coping. Goal management training (GMT) is a cognitive rehabilitation method for improving executive function. The purpose of this study was to determine the efficacy of GMT on aspects of perceived emotional health and coping in individuals with SB. METHOD: Thirty-eight adult subjects with SB were included in this randomized controlled trial. Inclusion was based upon the presence of executive functioning complaints. Experimental subjects (n = 24) received 21 hr of GMT, with efficacy of GMT being compared with results of subjects in a wait-list condition (n = 14). Four self-report questionnaires assessing emotional health and coping were utilized as outcome measures. All subjects were assessed at baseline, postintervention, and at 6-month follow-up. RESULTS: Findings indicated positive effects of GMT relative to the control group on measures of emotional health. Of note, the GMT group showed significant improvement, compared with control subjects, on a self-report inventory of depressive and anxiety symptoms after training, lasting at least 6 months posttreatment. Furthermore, both groups showed improvements after training on mental health components of health-related quality of life. Finally, the GMT group showed a significant increase in task-focused coping and a decrease in avoidant coping after training compared with pretreatment baseline assessment scores. CONCLUSIONS: Overall, findings indicate that by us a compensatory intervention to manage executive dysfunction, effective and lasting benefits can be achieved with regard to aspects of perceived emotional health and coping.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".