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Record W2028611712 · doi:10.1177/1087054713516490

Working Memory Training in College Students With ADHD or LD

2014· article· en· W2028611712 on OpenAlexaff
Rachel Gropper, Howell Gotlieb, Reena Kronitz, Rosemary Tannock

Bibliographic record

VenueJournal of Attention Disorders · 2014
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsSickKids FoundationHospital for Sick ChildrenInstitute for Christian Studies
FundersPurdue PharmaEli Lilly and Company
KeywordsPsychologyWorking memoryWorking memory trainingCognitionCognitive trainingAudiologyClinical psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to determine the feasibility and effectiveness of working memory (WM) training in college students with ADHD or learning disabilities (LD). METHOD: A total of 62 students (21 males, 41 females) were randomized to a 5-week intensive WM training program or a wait-list control group. Participants were evaluated before treatment, 3 weeks after completion, and at 2-month follow-up. The criterion measures were standardized tests of auditory-verbal and visual-spatial WM. Near transfer measures included other cognitive tasks; far transfer measures included academic tasks and behavioral rating scales. RESULTS: Intent-to-treat analysis revealed that participants receiving WM training showed significantly greater improvements on the criterion WM measures and self-reported fewer ADHD symptoms and cognitive failures. The follow-up assessment indicated that gains in WM were maintained, as were improvements in cognitive failures. CONCLUSION: Computerized WM training is a feasible and possibly viable approach for enhancing WM in college students with ADHD or LD.

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 score0.009

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 integrity0.0000.000
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 head0.052
GPT teacher head0.339
Teacher spread0.287 · 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

Citations67
Published2014
Admission routes1
Has abstractyes

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