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Record W2101325

The Effects of Goal Management Training in Undergraduate Students with Problems in Attention Functioning

2011· article· en· W2101325 on OpenAlexaff
Jenny Carstens

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTraining (meteorology)PsychologyApplied psychologyGoal settingMedical educationCognitive psychologyMathematics educationPedagogySocial psychologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Most research on training of executive functions involves older adults or individuals with brain injury. The present study was conducted with 122 undergraduates who reported some difficulties with attention and executive functions. Students either received a fourty-five minute session of Goal Management Training (GMT) or performed a distraction task. Tasks requiring goal management (GM) skills were given before and after this session. There was a significant decrease in completion time of the tasks overall (p < .05), as well as a significantly greater decrease in the experimental group (p < .05). There was a non-significant decrease in errors across both groups with no significant group difference in change. In addition to demonstrating a robust practice effect on GM tasks, the results suggest that brief GMT may be helpful to undergraduates who experience attentional difficulties. Further work is needed to understand the value and essential components of GMT in this population.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.032
GPT teacher head0.286
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2011
Admission routes1
Has abstractyes

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