Evidence map›Paper›PMID 39100120›Full record

ArticleIndian journal of psychiatry2024

Navigating the digital landscape: Relationship between type of internet use and well-being among students-A mediation and moderation analysis.

Sapam Kiran Dolly, Narendra Nath Samantaray

Abstract read
In one paragraph

Article in Indian journal of psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Sapam Kiran DollyDepartment of Clinical Psychology, School of Medical and Paramedical Science, Mizoram University, Aizawl, Mizoram, India.
Narendra Nath SamantarayCommunity Mental Health Unit, Department of Clinical Psychology, National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road, Bengaluru, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The amount and frequency of internet use are often used to forecast its pros and cons, with mixed findings. After COVID-19, technological advances and sociological upheavals have shown the internet's ability to support numerous activities, necessitating a change in internet use. Beyond internet use frequency, it has been advised to examine why people use it and how it affects their well-being. Hence, we aimed to investigate the various mediators and moderators in the relationship between the quality of internet use (type of activity) and well-being. Further, we investigated whether user attributes such as initial age and frequency of internet use moderate the influence of internet use quality on problematic internet use, loneliness, and well-being. Methods: 131 students in Manipur who were 18 years old were included in this cross-sectional study. Self-rated measures of the Adult Internet Usage questionnaire, Internet Addiction Test, and Mental Health Continuum-Short Form assessed internet use, dependence, and well-being. Results: Loneliness mediates the association between well-being and internet behaviors related to personal use-self-actualization (BootSE = .53, BootLLCI = .10, BootULCI = 2.18), cultural use-belonging (BootSE =.57, BootLLCI = -2.23, BootULCI = -.02). Average online hours moderate economic use-education, loneliness, and well-being (BootSE =.13, BootLLCI = -.55, BootULCI = -.04). Conclusion: To conclude, the effectiveness of internet use affects well-being differently depending on the type of activity. After a certain point, even seemingly good internet activities may have diminishing returns.

Indexed as

Conditional process analysislonelinessmediationproblematic internet usewell-being

Identifiers

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LicenceCC BY-NC-SA
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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.