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Record W2903665634 · doi:10.2196/11551

Smartphone and Internet Access and Utilization by People With Schizophrenia in South Australia: Quantitative Survey Study

2018· article· en· W2903665634 on OpenAlexvenueno aff
Kwok Tung Gordon Wong, Dennis Liu, Ryan Balzan, Daniel L. King, Cherrie Galletly

Bibliographic record

VenueJMIR Mental Health · 2018
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetInternet accessPsychological interventionPhoneMobile phoneGerontologyMedicinePsychologyInternet privacyPsychiatryWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Web-based information and interventions for mental illness are increasingly being provided. There is an expectation that citizens have access to the internet and are competent in using technology. People with schizophrenia are often excluded from social engagement, have cognitive impairment, and have very limited income, all of which may reduce their use of technology. OBJECTIVE: This study aimed to investigate technology access, use of digital technology, and confidence in using technology among people with schizophrenia living in the community. METHODS: Face-to-face structured interviews with 50 people with schizophrenia (aged 18-65 years) living in the northern suburbs of Adelaide, South Australia, were conducted using an instrument designed to assess technology access and utilization. RESULTS: Most participants (42/50, 84%) owned a mobile phone, but only 58% (29/50) owned a smartphone. Two-thirds of participants (33/50, 66%) had access to the internet at home, using a smartphone or computer. Moreover, 40% (20/50) of participants used the internet at least daily, but 30% (15/50) of participants had never accessed the internet from any device. Approximately half of the participants (24/50, 48%) had never used Facebook. Participants rarely used community facilities (eg, libraries and cafes) to access the internet. There were no significant differences (P values ranged from .14 to .70) between younger participants (aged 18-34 years) and older participants (aged 35-64 years) in internet or smartphone access or confidence in using technology. CONCLUSIONS: Although the sample size of this study is small, it shows limited technology access, use of digital technology, and confidence in using technology among the participants. This could be a barrier to the online delivery of information and interventions for people with schizophrenia. To better understand the impacts of such technological disadvantage and potential disparities in access and use of online resources, prospective studies should recruit a larger sample size and include control subjects matched for socioeconomic disadvantage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.134
GPT teacher head0.482
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2018
Admission routes1
Has abstractyes

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