Evidence map›Paper›PMID 36419692›Full record

ArticleIndustrial psychiatry journal

Affective symptoms as a predictor of internet addiction among young adults.

Nitin Anand, Manoj K Sharma, Palaniappan Marimuthu, Ravish Huchegowda, Pranjali C Thakur, Akash Vishwakarma, Ashwini Tadpatrikar, Ishita Mondal, K M Azhagannan, Vikas S Rawat

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Industrial psychiatry journal. 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
1.6field-weighted citation impact, top 13% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

10 authors at 1 institution in 1 country.

Nitin AnandDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Manoj K SharmaDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Palaniappan MarimuthuDepartment of Biostatistics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Ravish HuchegowdaDepartment of Neurochemistry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Pranjali C ThakurDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Akash VishwakarmaDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Ashwini TadpatrikarDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Ishita MondalDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
K M AzhagannanDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
Vikas S RawatDepartment of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India.
National Institute of Mental Health and Neurosciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Mental health difficulties have been found to be associated with internet addiction, which makes it a multifaceted problem. The current study aimed to examine the relationship between internet addiction and affective states (depression, anxiety, and stress). Material and Methods: The study sample consisted of 731 individuals (403 males and 328 females) ranging in age from 18 to 25 years. We used an observational survey design to study participants with an internet addiction test and depression, anxiety, and stress scale. Results: The mean age ± standard deviation of the sample was 22.58 ± 2.80 years. Stress and depression were found to play a major role in internet addiction in the regression analysis. Conclusions: The study supports the association between internet use and stress and depression. The findings imply the need for early identification and intervention of affective states in the context of unhealthy internet use.

Indexed as

Anxietydepressioninternet addictionstress

Identifiers

PMID36419692
PMCPMC9678147
OpenAlexW4293566934

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.