Evidence map›Paper›PMID 35182242›Full record

Trial reportEuropean child & adolescent psychiatry2023

A randomized controlled study of remote computerized cognitive, neurofeedback, and combined training in the treatment of children with attention-deficit/hyperactivity disorder.

Xiangsheng Luo, Xiaojie Guo, Qihua Zhao, Yu Zhu, Yanbo Chen, Dawei Zhang, Han Jiang, Yufeng Wang, Stuart Johnstone, Li Sun

Open access · bronzeAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in European child & adolescent psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 4 pooled it
6.0field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 4 syntheses or guidelines pooled it, 42 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Xiangsheng Luo *Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China.
Xiaojie Guo *Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China.
Qihua ZhaoPeking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China.
Yu ZhuPeking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China.
Yanbo ChenPeking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China.
Dawei ZhangDepartment of Psychology, School of Educational Science, Yangzhou University, Jiangsu, People's Republic of China.
Han JiangSchool of Special Education, Zhejiang Normal University, Hangzhou, People's Republic of China.
Yufeng WangPeking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China.
Stuart JohnstoneSchool of Psychology, University of Wollongong, Wollongong, NSW, Australia. sjohnsto@uow.edu.au.
Li SunPeking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, People's Republic of China. sunlioh@bjmu.edu.cn.ORCID http://orcid.org/0000-0002-2330-6622
Peking University · CNUniversity of Wollongong · AUYangzhou University · CNZhejiang Normal University · CN

Funding

the Beijing Municipal Science and Technology Program Z171100001017089the Key scientific research projects of capital health development 2020-1-4111the National Natural Sciences Foundation of China 81771479the National Natural Sciences Foundation of China 81971284
6 · The paper itself

Abstract

There is an increasing interest in non-pharmacological treatments for children with attention-deficit/hyperactivity disorder (AD/HD), especially digital techniques that can be remotely delivered, such as neurofeedback (NFT) and computerized cognitive training (CCT). In this study, a randomized controlled design was used to compare training outcomes between remotely delivered NFT, CCT, and combined NFT/CCT training approaches. A total of 121 children with AD/HD were randomly assigned to the NFT, CCT, or NFT/CCT training groups, with 80 children completing the training program. Pre- and post-training symptoms (primary outcome), executive and daily functions were measured using questionnaires as well as resting EEG during eyes-closed (EC) and eyes-open (EO) conditions. After 3 months of training, the inattentive and hyperactive/impulsive symptoms, inhibition, working memory, learning and life skills of the three groups of children were significantly improved. The objective EEG activity showed a consistent increase in the relative alpha power in the EO condition among the three training groups. Training differences were not observed between groups. There was a positive correlation between pre-training EO relative alpha power and symptom improvement scores of inattention and hyperactivity/impulsivity, as well as a negative correlation between pre-training inattention scores and change in EO relative alpha. This study verified the training effects of NFT, CCT, and combined NFT/CCT training in children with AD/HD and revealed an objective therapeutic role for individual relative alpha activity. The verified feasibility and effectiveness of home-based digital training support promotion and application of digital remote training.

Indexed as

Attention Deficit Disorder with HyperactivityNeurofeedbackChildCognitionElectroencephalographyHumansLearningResearch DesignAD/HDComputerized cognitive trainingElectroencephalogramNeurofeedbackNon-pharmacological treatments

Identifiers

PMID35182242
PMCPMC8857637
OpenAlexW4213026568

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.