Evidence map›Paper›PMID 33362979›Full record

ArticlePeerJ2020

WeChat-based mHealth intention and preferences among people living with schizophrenia.

Shuiyuan Xiao, Tongxin Li, Wei Zhou, Minxue Shen, Yu Yu

Abstract read
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Social Media Use for Health Purposes: Systematic Review.Journal of medical Internet research · 2021
    Pooled it
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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

5 authors.

Shuiyuan XiaoDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.
Tongxin LiDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.
Wei ZhouSchool of Public Administration, Hunan University, Changsha, Hunan, China.
Minxue ShenDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.
Yu YuDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe past few decades have seen a rapid expansion of mHealth programs among people with serious mental illness, yet mHealth for schizophrenia is in a much earlier stage of development. This study examined the intention of WeChat-based mHealth programs among people living with schizophrenia (PLS) and evaluated correlates of the intention.

methodsA total of 400 PLS aged 18-77 completed a cross-sectional survey by face-to-face interviews. The survey included a general question asking about participants' willingness to attend WeChat-based mHealth programs, followed by preferences of three specific WeChat-based programs: psychoeducation, peer support, and professional support. PLS symptoms, functioning and disability were measured using the 18-item Brief Psychiatric Rating Scale (BPRS-18), the Global Assessment of Functioning (GAF), and the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), respectively. A multivariate logistic regression was used to determine correlates of program participation intention.

resultsOver forty percent (43%,

conclusionThe findings provide guidance for further development of WeChat-based mHealth programs among PLS in China, and targeted at those who are younger, well-educated and with lower disability.

Indexed as

ChineseIntentionmHealthPreferencesSchizophreniaWeChat

Identifiers

PMID33362979
PMCPMC7749651

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Registered trials

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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.