Evidence map›Paper›PMID 33882865›Full record

ArticleBMC geriatrics2021

Does digital technology reduce health disparity? Investigating difference of depression stemming from socioeconomic status among Chinese older adults.

Aruhan Mu, Zhaohua Deng, Xiang Wu, Liqin Zhou

Abstract read
In one paragraph

Article in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed, 2 syntheses or guidelines 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

4 authors.

Aruhan MuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Zhaohua DengSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Xiang WuSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Liqin ZhouSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China. zhouliqin@hust.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrior studies on health disparity have shown that socioeconomic status is critical to inequality of health outcomes such as depression. However, two questions await further investigation: whether disparity in depression correlated with socioeconomic status will become larger when depression becomes severer, and whether digital technology will reduce the disparity in depression correlated with socioeconomic status. Our study aims to answer the above two questions.

methodsBy using the dataset from China Health and Retirement Longitudinal Study 2015, we use quantile regression models to examine the association between socioeconomic status and depression across different quantiles, and test the moderating effect of digital technology.

resultsOur study obtains four key findings. First, the negative effects of socioeconomic status on depression present an increasing trend at high quantiles. Second, Internet usage exacerbates the disparity in depression associated with education level on average, but reduces this disparity associated with education level at high quantiles. Third, Internet usage reduces the disparity in depression associated with income on average and at high quantiles. Fourth, mobile phone ownership has almost no moderating effect on the relationship between socioeconomic status and depression.

conclusionsOur findings suggest the potential use of digital technology in reducing disparity in depression correlated with socioeconomic status among middle-aged and aged individuals in developing countries.

Indexed as

DepressionDigital TechnologyAgedChinaHealth Status DisparitiesHumansLongitudinal StudiesMiddle AgedSocial ClassSocioeconomic FactorsDigital technologyDiversity in agingMental health

Identifiers

PMID33882865
PMCPMC8059190

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LicenceCC BY
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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.