Can Geriatric Psychiatry Patients Complete Symptoms Self-Reports Using Tablets? A Randomized Study
Bibliographic record
Abstract
BACKGROUND: With our aging population and limited number of geriatric psychiatrists, innovations must be made in order to meet the growing demands for geriatric psychiatry services. Emerging technologies could greatly improve access to care and systematic data collection. METHODS: This randomized study compared completion rates and time to completion (primary outcomes) when using iPad technology vs. traditional paper forms to complete self-report psychiatric symptoms. Geriatric psychiatry outpatients (n = 72) and adult psychiatry inpatients (n = 50) were recruited to complete the Brief Symptom Inventory (BSI-53), the Activities of Daily Living (ADL), and Patient Health Questionnaire (PHQ-9) questionnaires. RESULTS: = .04) were associated with a shorter time to completion. The effect of questionnaire formats was especially prominent in the inpatient group on time to completion. CONCLUSIONS: Older adults with mental illness demonstrate a similar ability to complete self-report questionnaires whether iPads or paper forms. iPad questionnaires may even require less time to complete in geriatric psychiatry inpatients. Patients also found iPad questionnaires to be easy to use and read. Tablets could potentially be used for psychiatric symptom assessment for clinical, research, and population health purposes.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".