Evidence map›Paper›PMID 30530575›Full record

ArticleBMJ open2018

Integrated decision-making model for community-based rehabilitation service utilisation among persons with severe mental illness in China: protocol for a cross-sectional, mixed-methods study.

Ruoxi Wang, Shangfeng Tang, Ian Shaw, Zhanchun Feng, Zhuo Chen, Yuxiong Luo, Hongxun Song, Tailai Wu, Qian Fu, Hang Fu and 3 more

Abstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
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

13 authors.

Ruoxi WangSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0002-9695-0582
Shangfeng TangSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ian ShawSchool of Sociology and Social Policy, University of Nottingham, Nottingham, UK.
Zhanchun FengSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhuo ChenCollege of Public Health, University of Georgia, Athens, Georgia, USA.
Yuxiong LuoNanyou Community Health Service Center, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
Hongxun SongSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tailai WuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qian FuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hang FuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yueying HuangSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiaoyu ChenSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Da FengSchool of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA common problem low-income and middle-income countries face is the scarcity of community-based rehabilitation (CBR) resources and low service utilisation among persons with severe mental illness (SMI). Despite this problem, the factors and pathways followed influencing one's decision on service utilisation in China have not been fully comprehended. This study aims to develop a theory-based model that systematically describes the integrated decision-making process of mental health CBR utilisation among persons with SMI in China. METHODS/

designThis cross-sectional, mixed-methods study involves three main stages and is expected to last 3 years, from January 2018 to December 2020. In stage 1, the Social Exchange Theory is deployed as an analytical framework to comprehensively capture factors associated with tendency to use CBR services in China using semistructured interview methodology involving patients with SMI, their primary caregivers and CBR service providers. In stage 2, interpretive structural modelling will be applied to analyse the relationships between factors in different dimensions, at different levels and with different levels of impact. Stage 3 involves a multiregion survey among at least 300 family decision-makers (either the patient or their caregivers) in six communities in three cities to statistically validate the initial model derived in stage 2 using a further structural equation modelling. ETHICS AND DISSEMINATION: Ethical approval was granted by the Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology (No 2017S319). All interviewees will be provided with written information about the study, and a signed consent will be retrieved prior to the interview. Rules on confidentiality and anonymity of data will be strictly followed. The findings of this study will be disseminated via international and domestic peer-reviewed journals, reports, conference presentations and symposium discussions. Reports will be submitted to the National Natural Science Foundation of China.

Indexed as

Decision Support TechniquesAdultAttitude to HealthChinaCommunity Mental Health ServicesCross-Sectional StudiesCultural CharacteristicsFemaleHealth Services Needs and DemandHumansIntentionInterview, PsychologicalMaleMental DisordersPatient Acceptance of Health CareSocial Stigmacommunity-based rehabilitationmental healthservice utilisation

Identifiers

PMID30530575
PMCPMC6303639

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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.