Evidence map›Paper›PMID 33408206›Full record

ArticleBMJ open2021

Translation and validation of the Chinese version of medical maximizer-minimizer scale: a cross-sectional study.

Fenghua Lai, Ling Pei, Shufan Yue, Xiaopei Cao, Haipeng Xiao, Yanbing Li, Jin Li

Abstract read
In one paragraph

Article in BMJ open, 2021. 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

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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.

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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

7 authors.

Fenghua LaiDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID 0000-0002-3562-7132
Ling PeiDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Shufan YueDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xiaopei CaoDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Haipeng XiaoDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yanbing LiDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Jin LiDepartment of Geriatrics, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China lijin8@mail.sysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMedical overutilisation and underutilisation affect optimal healthcare. The Medical Maximizer-Minimizer Scale (MMS) was developed to assess individual medical maximising and minimising tendencies. Despite significant improvement in the healthcare system over the past four decades, no psychometric scales to examine treatment maximising and minimising preferences are available in China. This study aimed to translate the MMS into Chinese and examine its reliability and validity in a Chinese population.

designThis cross-sectional study was conducted in December 2019 through an online survey panel.

methodsThe MMS was translated into a Chinese version (CN-MMS) using a forward-backward translation procedure. Next, a random online survey of the general population in China was conducted. Exploratory factor analysis (EFA) and confirmatory factor analysis were performed to examine the underlying factor structure of the CN-MMS. The internal consistency reliability of the scale was determined using Cronbach's α coefficient and corrected item-total correlation. A multivariate linear regression analysis was used to examine associations between medical maximising and minimising preferences and demographic variables in the Chinese population.

resultsThis study included 984 participants aged 18-80 years. The CN-MMS retained 10 items, and the EFA supported a two-factor structure. The model fit for this two-factor structure of the CN-MMS was acceptable with χ

conclusionsThe CN-MMS showed satisfactory psychometric properties. Therefore, it can be used to investigate the individual medical maximising and minimising tendencies among the general Chinese population.

Indexed as

TranslationsAdolescentAdultAgedAged, 80 and overChinaCross-Sectional StudiesFactor Analysis, StatisticalHumansMiddle AgedPsychometricsReproducibility of ResultsSurveys and QuestionnairesYoung Adulthealth informaticsprimary carequality in health care

Identifiers

PMID33408206
PMCPMC7789444

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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.