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Record W3131602977 · doi:10.1097/md.0000000000023953

Efficacy and safety of acupuncture on childhood attention deficit hyperactivity disorder

2021· article· en· W3131602977 on OpenAlexaff
Yong Lin, Hongjiao Jin, Bo Huang, N. Zhao, Zhu Li, Jiao Mao, Changda Chen, Jie Xu, Jun Zhang, Biqin Shuai

Bibliographic record

VenueMedicine · 2021
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsCAE (Canada)
FundersNational Natural Science Foundation of China
KeywordsMedicineRandomized controlled trialMEDLINEMeta-analysisChecklistData extractionAttention deficit hyperactivity disorderRating scaleCBCLPsychiatryPsychologyDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The purpose of this paper is to evaluate the efficacy and safety of acupuncture in the treatment of childhood attention deficit hyperactivity disorder (ADHD). METHODS AND ANALYSIS: We will electronically search PubMed, Medline, Embase, Web of Science, the Cochrane Central Register of Controlled Trial, China National Knowledge Infrastructure, China Biomedical Literature Database, China Science Journal Database, and Wan-fang Database from their inception. Also, we will manually retrieve other resources, including reference lists of identified publications, conference articles, and grey literature. The clinical randomized controlled trials or quasi-randomized controlled trials related to acupuncture treating pediatric ADHD will be included in the study. The language is limited to Chinese and English. Research selection, data extraction, and research quality assessment will be independently completed by 2 researchers. Data were synthesized by using a fixed effect model or random effect model depend on the heterogeneity test. The scores of Revised Conners' Parent Rating Scale (CPRS-R), Conners Teacher Rating Scale (CTRS-R), and Child Behavior Checklist (CBCL) will be the primary outcomes. Besides, the scores of the Conners Continuous Performance Test, Internal Restlessness Scale, and Behavior Assessment System for Children (BASC), and the possible adverse events will also be assessed as secondary outcomes. RevMan V.5.3 statistical software will be used for meta-analysis, and the level of evidence will be assessed by Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Continuous data will be expressed in the form of weighted mean difference or standardized mean difference with 95% confidence intervals (CIs), while dichotomous data will be expressed in the form of relative risk with 95% CIs. ETHICS AND DISSEMINATION: The protocol of this systematic review (SR) does not require ethical approval because it does not involve humans. We will publish this article in peer-reviewed journals and presented at relevant conferences. SYSTEMATIC REVIEW REGISTRATION: OSF Registries, DOI: 10.17605/OSF.IO/XVYP9 (https://osf.io/xvyp9).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.307
Teacher spread0.293 · 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 designObservational
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

Citations4
Published2021
Admission routes1
Has abstractyes

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