Evidence map›Paper›PMID 40153777›Full record

ArticleJournal of medical Internet research2025

Patterns of Internet Use in People Diagnosed With Severe Mental Illness: Qualitative Interview Study.

Ruth Wadman, Lauren Walker, Olivia Taylor, Paul Heron, Elizabeth Newbronner, Panagiotis Spanakis, Suzanne Crosland, Emily Jane Peckham

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

8 authors.

Ruth Wadman *Department of Health Sciences, University of York, York, United Kingdom.ORCID 0000-0003-4205-0631
Lauren Walker *School of Medical and Health Sciences, Bangor University, Wrexham, United Kingdom.ORCID 0000-0003-2459-7860
Olivia TaylorDepartment of Health Sciences, University of York, York, United Kingdom.ORCID 0000-0001-7043-1795
Paul HeronDepartment of Health Sciences, University of York, York, United Kingdom.ORCID 0000-0003-3529-5737
Elizabeth NewbronnerDepartment of Sociology, University of York, York, United Kingdom.ORCID 0000-0003-2366-9981
Panagiotis SpanakisDepartment of Psychology, University of Crete, Rethymno, Greece.ORCID 0000-0002-2732-8300
Suzanne CroslandDepartment of Health Sciences, University of York, York, United Kingdom.ORCID 0000-0001-6658-6815
Emily Jane PeckhamSchool of Medical and Health Sciences, Bangor University, Bangor, United Kingdom.ORCID 0000-0002-9377-1968

Funding

Medical Research Council MR/V028529Wellcome Trust
6 · The paper itself

Abstract

backgroundPeople with severe mental illness (SMI) face profound health inequalities, which may be exacerbated by increased rates of digital exclusion, especially as health services move to online provision. The activities that people carry out online can affect how they feel about the internet and may determine whether a person has a positive or negative experience when using the internet. This, in turn, could affect their mental health. To support people with SMI in using digital technology and the internet safely, it is important to understand the internet and digital technology use of those with SMI and their perceived positive or negative impact on their mental health.

objectiveThis study aimed to explore the internet and digital technology use of those with SMI, with particular focus on any association between greater use of the internet and poorer self-reported mental health.

methodsWe carried out a qualitative interview study with 16 people with SMI. The sample was drawn from a wider investigation of the impact of the pandemic and its restrictions on the health and well-being of 367 people with SMI. We purposively sampled from the wider study based on age, gender, frequency of internet use, and self-reported mental health. The data were analyzed by 2 researchers using framework analysis.

resultsParticipant experiences fell into 3 broad categories: those who had a positive or neutral internet-based experience, those who had negative or difficult experiences, and low users or those with poor digital literacy. Those who had positive or neutral experiences could be broken down into 2 subcategories: first, those with positive or neutral experiences of the internet who were similar in terms of the activities participated in, feelings reported, and their concerns about the internet, and second, conscious users who were mindful of their interaction with the internet world. Participants with difficult experiences fell into 2 categories: those with worries and fears related to using the internet and those who had difficulty limiting their internet use.

conclusionsPeople with SMI, similarly the general population, are expected to conduct more of their activities of daily living online in the postpandemic world. This research shows that most internet users with SMI have positive or neutral experiences. However, our typology reveals subgroups of the population with SMI for whom there is a relationship between internet use and difficult feelings. These subgroups can be identified by asking questions about online activities; time spent online; feelings, difficulties, or issues experienced; and use of gambling, dating, adult content, and conspiracy theory websites. Our findings point to further work in collaboration with people with lived experience to modify and test this typology.

Indexed as

InternetInternet UseMental DisordersAdultAgedCOVID-19FemaleHumansInterviews as TopicMaleMental HealthMiddle AgedQualitative Researchdigital divideinternet useprotective strategiesqualitativesevere mental illnesstypology

Identifiers

PMID40153777
PMCPMC11992490

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.