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The meaning of a multimodal approach for children with ADHD: experiences of service professionals

2002· article· en· W2138270981 on OpenAlexaff
E. Hazelwood, T. Bovingdon, Kim Tiemens

Bibliographic record

VenueChild Care Health and Development · 2002
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsIntervention (counseling)PsychologyAmbiguityAttention deficit hyperactivity disorderMeaning (existential)Perspective (graphical)Clinical psychologyPsychotherapistDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood mental disorder characterized by inattention, impulsiveness and overactivity. It is also characterized by heterogeneity and ambiguity. Effective intervention is influenced by these two factors. This pervasive disorder impacts various domains of functioning, including academics, peer relations, familial relationships and self-esteem. A confounding factor is the high rate of comorbidity with diagnoses such as learning disabilities, oppositional defiant disorder or conduct disorder. No one intervention has emerged as maximally effective across all symptoms and domains. Consequently, a multimodal approach is regarded as the favoured method of intervention. However, no clear definition of'multimodal' exists. METHOD: This study explored the meaning of multimodal from the perspective of professionals employed in a tertiary care hospital setting in which children with ADHD are assessed and treated. A qualitative design using a phenomenological approach allowed professionals to speak from their practice experiences. RESULTS AND CONCLUSION: Although no clear definition of multimodal emerged, professionals identified issues key to this approach and proposed a model for intervention.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.046
GPT teacher head0.324
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations14
Published2002
Admission routes1
Has abstractyes

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