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Record W2116208712 · doi:10.1542/pir.32-2-e18

Complementary, Holistic, and Integrative Medicine: Therapies for Learning Disabilities

2011· review· en· W2116208712 on OpenAlexaffabout
Elaine Galicia-Connolly, Larissa Shamseer, Sunita Vohra

Bibliographic record

VenuePediatrics in Review · 2011
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsStollery Children's Hospital
FundersJapan Agency for Medical Research and Development
KeywordsIntegrative medicineHolistic healthMedicineAlternative medicineHolistic nursingComplementary medicinePsychologyPsychotherapistNursing

Abstract

fetched live from OpenAlex

1. Elaine Z. Galicia-Connolly, MD* 2. Larissa Shamseer, MSc† 3. Sunita Vohra, MD† 1. *Former Clinical Fellow, University of Alberta, Stollery Children's Hospital CARE Program, Edmonton, Alberta, Canada. 2. †Complementary and Alternative Medicine Research and Education (CARE) Program, Department of Pediatrics, Faculty of Medicine, University of Alberta on behalf of the American Academy of Pediatrics Section on Complementary and Integrative Medicine. Between 5% and 10% of schoolchildren have learning disabilities (LD), and up to 80% of such children have some form of dyslexia. (1) The diagnosis is based on significantly lower academic achievement than the intelligence quotient (IQ) would suggest. (2) Although disorders of learning and attention frequently occur together, this review specifically examines the effectiveness of complementary and alternative medicine (CAM) interventions for children who have LD. The studies might include children who have comorbid conditions such as attention-deficit/hyperactivity disorder (ADHD). Existing interventions for LD focus on remedial teaching in the early years and offering compensatory mechanisms and lifestyle adjustments at later ages. The most robust predictive factors correlating with the success of LD interventions are attention and behavior, general verbal ability, prior level of component reading skills, and total IQ. (1) In a survey of 148 schoolchildren who had dyslexia, Bull found that 55.4% had used CAM for dyslexia, most commonly nutritional supplements or special diets, homeopathy, and osteopathy or chiropractic manipulation. (3) We conducted a search for articles related to learning disabilities and CAM therapies on MEDLINE, Embase, AMED, PsycInfo, the Cochrane Database of Systematic Reviews, and Cochrane's Central Register of Controlled Trials. Search terms were: (learning disorders OR learning disabilities) AND (complementary therapies), with terms varying by database and no limits on language or date. Studies were included if they examined a strictly pediatric population (0 to 18 years) of individuals who had LD and who experienced CAM as the intervention. Eleven articles were relevant …

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
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)0.0010.000

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 head0.272
GPT teacher head0.474
Teacher spread0.202 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2011
Admission routes2
Has abstractyes

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