Evidence map›Paper›PMID 35292010›Full record

ArticleBMC public health2022

The effect of smartphones on the self-rated health levels of the elderly.

Xian Liang, Feixue Xiong, Fangting Xie

Abstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 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

3 authors.

Xian LiangCollege of Economics and Management, Zhejiang A&F University, 311300, Hangzhou, China.
Feixue XiongSchool of Economics and Management, Jiangxi Agricultural University, 330045, Nanchang, China.
Fangting XieCollege of Economics and Management, Zhejiang A&F University, 311300, Hangzhou, China. fountain_xie@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to the penetration of Internet use and the popularity of "Internet + elderly care" among seniors in recent years, the elderly are gradually integrating into the information society. This study examined the impact of smartphones on the self-rated health levels of the elderly.

methodsWe studied 3042 elderly people over 55 years of age in Jiangxi, China in 2018. The effect of smartphones was measured from three aspects: smartphone usage, smartphone usage ability, and smartphone usage purpose, and the multivariate ordered logistic model was applied. Furthermore, considering the potential endogeneity of the smartphone usage of elderly people, the propensity score matching (PSM) method was used to analyze the net effect of smartphones on the health levels of the elderly.

results(1) The use of smartphones had a significant positive impact on the self-rated health levels of the elderly, with its significance being at the level of 1%. Smartphone usage ability, and using smartphone to learn or search for health information, had significant positive impacts (at the level of 5%) on the self-rated health levels of the elderly. (2) The k-nearest neighbor matching, kernel matching and radius matching methods were used to calculate the net effect of smartphone usage on the self-rated health levels of the elderly. The results were 13.26, 15.33 and 14.80%, respectively. (3) The age of the participants significantly (at the level of 1%) negatively affected their self-rated health levels. Other characteristics of the elderly, including income, education level, living with children or spouse and children's living conditions, significantly (all at the level of 1%) positively affected their self-rated health levels.

conclusionsSmartphone usage, smartphone usage ability, and smartphone usage purposes all improved the self-rated health of the elderly. The Internet factor should be focused on in the process of active aging. We should improve the Internet use ability of the elderly through voluntary training or public lectures.

Indexed as

Health StatusSmartphoneAgedChildChinaHealth ServicesHumansLearningSelf-rated health level of the elderlySmartphone usageSmartphone usage abilitySmartphone usage purpose

Identifiers

PMID35292010
PMCPMC8925210

What OpenQuestion holds

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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.