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Record W2769505068 · doi:10.5430/jnep.v8n4p10

Coaching nursing students with attention deficit hyperactivity disorder in clinical settings: A case study

2017· article· en· W2769505068 on OpenAlexaffvenue
Kathleen M. Davidson, Liam Rourke, Kara Sealock, Wai Yin Mak

Bibliographic record

VenueJournal of Nursing Education and Practice · 2017
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsCoachingIntervention (counseling)PsychologyAttention deficit hyperactivity disorderTask (project management)PrioritizationClinical PracticeNursingMedical educationMedicinePsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Up to 18% of undergraduate students have some form of learning disability, with Attention Deficit Hyperactivity Disorder (ADHD) being the most common subtype. Some of these students enter nursing programs. Post-secondary institutions are developing processes to help students overcome traditional academic challenges, however, the demands of clinical practice courses are not easily modified. Effective performance in clinical settings requires nursing students to develop sophisticated executive functions for organization, prioritization, and managing distractions, all of which present considerable challenges for students with ADHD. We present a case study to illustrate the coaching intervention we adapted from the education literature for a nursing student with ADHD who was struggling in clinical practice courses. The most effective coaching strategies helped the student to harness his energy and enhance focus on the task at hand.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0070.003
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.117
GPT teacher head0.518
Teacher spread0.401 · 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 designCase report
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

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Nursing Education and Practice→Same topicAttention Deficit Hyperactivity Disorder→French-language works237,207→