Mobile phone access and preferences among medical inpatients at an urban Canadian hospital for post-discharge planning: A pre-COVID-19 cross-sectional survey
Bibliographic record
Abstract
Background: Digital health interventions are increasingly used for patient care, yet little data is available on the phone access type and usage preferences amongst medical ward inpatients to inform the most appropriate digital interventions post-discharge. Methods: To identify mobile phone ownership, internet access, and cellular use preferences among medical inpatients, we conducted a researcher-administered survey of patients admitted to five internal medicine units at Vancouver General Hospital (VGH) in January 2020. The survey was administered over 2 days separated by a 2-week period. Results: a proxy (or an authorized third-party) such as a family member. All participants with mobile phone access had cellular plans (i.e., phone and text); however, a quarter of respondents did not have data plans with internet access. Survey showed that 71.1% of males owned a mobile phone compared to only 52.8% of females. All participants at a "high" risk of readmission had access to a mobile phone, either as phone-owners or proxy-dependent users. Conclusion: Access to mobile phones among medical ward inpatients, 85.2%, was comparable to smartphone penetration rates amongst Canadians in 2019, 85.1%. More patients had cellular than data plans (i.e., internet and applications). Understanding patient-specific access is key to informing potential uptake of digital health interventions aimed at using patients' mobile phones (mHealth) from an effectiveness and equity lens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".