Evidence map›Paper›PMID 37179658›Full record

ArticleInnovation in aging2023

Social Media Use May Not Be As Bad As Some Suggest: Implication for Older Adults.

Shelia R Cotten, Reza Ghaiumy Anaraky, Amy M Schuster

Abstract read
In one paragraph

Article in Innovation in aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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.

Shelia R CottenDepartment of Sociology, Anthropology, and Criminal Justice, Clemson University, Clemson, South Carolina, USA.ORCID https://orcid.org/0000-0002-8657-8262
Reza Ghaiumy AnarakyDepartment of Technology Management and Innovation, Tandon School of Engineering, New York University, New York City, New York, USA.
Amy M SchusterDepartment of Sociology, Anthropology, and Criminal Justice, Clemson University, Clemson, South Carolina, USA.ORCID https://orcid.org/0000-0002-4472-0283

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Social media use (SMU) has increased over the past decade among older adults. Cross-sectional studies report SMU is related to negative mental health outcomes (i.e., depression). Given depression is the most common mental health issue for older adults and increases the risk of morbidity and mortality, determining longitudinally whether SMU is related to increased depression is critical. This study examined the longitudinal relationship between SMU and depression. Research Design and Methods: Data from 6 waves (2015-20) of the National Health and Aging Trends Study (NHATS) were analyzed. Participants included a nationally representative sample of U.S. older adults, aged 65 years and older ( Results: No pattern was found of SMU predicting depression symptoms, or depression symptoms predicting SMU. The major driver of SMU in each wave was SMU in the previous wave. On average, our model accounted for 3.03% of the variance in SMU. The major predictor of depression in each wave was the pre-existing depression. Our model accounted for an average of 22.81% of the variance in depressive symptoms. Discussion and Implications: The results suggest that SMU and depressive symptoms are driven by the previous patterns of SMU and depression, respectively. We did not find any patterns of SMU and depression influencing each other. NHATS measures SMU with a binary instrument. Future longitudinal research should employ measures that account for SMU duration, type, and purpose. These findings suggest that SMU may not be related to negative health outcomes, in this case, depression, for older adults.

Indexed as

DepressionInternet useSocial media effectsTechnology

Identifiers

PMID37179658
PMCPMC10168587

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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.