Smartphone and Internet Access and Utilization by People With Schizophrenia in South Australia: Quantitative Survey Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".