Evidence map›Paper›PMID 42393194›Full record

ArticleNPJ digital medicine2026

Randomized trial of self-adaptive computerized cognitive remediation in schizophrenia.

Yan-Ping Ren, Li-Na Wang, Shuo Lin, Wei-Gang Pan, Xue-Quan Zhu, Yi Liu, Han Wu, Dan-di Zhu, Si-Yuan Lian, Wen Wang and 7 more

Abstract read
PubMed Publisher
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Yan-Ping Ren *Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China. renyanping@ccmu.edu.cn.
Li-Na Wang *Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Shuo Lin *Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Wei-Gang Pan *Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Capital Medical University, Beijing, China.
Xue-Quan ZhuBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Yi LiuBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Han WuBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Dan-di ZhuBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Si-Yuan LianBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Wen WangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Wen-Qing JinBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Zhi-Ming BianBeijing Wispirit Technology Co., Ltd., Beijing, China.
Zi-Heng ZhangBeijing Wispirit Technology Co., Ltd., Beijing, China.
Yi-Lang TangDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
Long-Jun CaiBeijing Wispirit Technology Co., Ltd., Beijing, China. cailongjun@66nao.com.
Gang WangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China. gangwangdoc@ccmu.edu.cn.
Xin MaBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China. maxinanding@ccmu.edu.cn.

Funding

Beijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park D171100007017001
6 · The paper itself

Abstract

Computerized, self-adaptive cognitive training has emerged as a promising digital therapeutic for cognitive impairment; however, its underlying training mechanisms in schizophrenia remain poorly understood. This double-blind, randomized trial compared self-adaptive difficulty (SAD) with fixed-difficulty (FD) computerized cognitive training program, evaluating both domain-specific cognitive and clinical outcomes, and exploring difficulty-performance coupling as a potential active therapeutic mechanism. Seventy-two patients with schizophrenia (SAD = 41, FD = 31) completed 4 weeks of training, and 40 patients (n = 20 per group) were assessed at week 8. Cognitive outcomes were measured using the Cognitive Index (CI) and MATRICS Consensus Cognitive Battery (MCCB), while clinical symptoms were also assessed. Linear mixed-effects models (LMMs) revealed significantly greater and faster cognitive improvements in the SAD compared with the FD group in attention and agility, with faster improvement also observed in thinking. Robust difficulty-performance coupling was observed across all cognitive domains. Additionally, positive symptoms improved significantly in the SAD group compared to the FD group at week 4. Self-adaptive cognitive training enhances and accelerates cognitive improvements in schizophrenia, particularly in attention and processing speed, and also benefits positive symptoms. Difficulty-performance coupling may reflect dynamic load calibration as a key therapeutic mechanism in digital cognitive training. Trial registration: Chictr.org.cn, number, ChiCTR2000040326, registered 2020-11-27.

Identifiers

PMID42393194

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.