Efficacy of Online Goal Management Training for Age-Associated Executive Impairment
Bibliographic record
Abstract
Abstract Goal Management Training® (GMT) is a standardized cognitive rehabilitation program that enhances individuals’ awareness of executive function impairments and trains them to regularly monitor and manage their goals. In-person GMT is well-validated among numerous subpopulations, including people experiencing age-related cognitive impairment or acquired brain injury, and people with psychiatric disorders. The goal of this study was to evaluate the efficacy and usability of online GMT relative to computerized “brain training” in a registered randomized controlled trial (protocol NCT03602768 at Trials.gov). Both interventions were administered in a self-paced format, with background therapist support provided for GMT. Primary outcomes were measured as self-reported executive impairment on standardized measures (the Dysexecutive Questionnaire and the Cognitive Failures Questionnaire) at pre-, immediate post-, and 6 weeks post-intervention. 62 older adults without psychiatric or neurological diagnoses completed the trial (online GMT: n = 37, age[mean] = 69 years; computerized brain training: n = 25, age[mean] = 64 years; both groups: 76% female). Improvements on the primary outcomes were observed post-intervention and were maintained at follow-up. GMT and computerized brain training groups could not be differentiated statistically, possibly due to restriction of range in the outcome measures at baseline. Additionally, the self-paced format prolonged the intervention beyond the recommended duration, which may have diluted efficacy. GMT was well-received, with participants reporting frequent use of the trained metacognitive strategies. Future studies will examine online GMT’s effectiveness in samples with documented executive impairment and with additional supports to promote engagement for this virtual program.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".