Patient attitudes toward ambient artificial intelligence scribes in clinical care: insights from a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: To assess patient attitudes towards ambient artificial intelligence (AI) scribes, including comfort, trust, perceived impact on provider interactions, and willingness for future use, and to examine how sociodemographic, health factors, digital literacy, and privacy concerns shape attitudes. MATERIALS AND METHODS: We analyzed cross-sectional data from an online survey of 12 153 adults (52.4% female; 23.1% aged ≥ 65; 41.2% with chronic conditions) in Canada conducted between February 6 and March 10, 2025. Survey-adjusted ordinal and binary logistic regression models assessed predictors, reporting adjusted odds ratios (aORs), 95% confidence intervals (CIs), and P-values. RESULTS: Most respondents (61.8%) were reluctant to future AI scribe use despite mixed attitudes: 39.3% reported some/very high comfort, 57.4% trusted documentation with human oversight, and 49.5% anticipated positive effects on patient-provider interactions. Awareness of AI scribe use was low (28.3%). Males showed higher odds of favorable comfort (aOR = 1.13, 95% CI, 1.05-1.22, P = .001), trust (aOR = 1.21, 95% CI, 1.10-1.32, P < .001), and future use (aOR = 1.38, 95% CI, 1.27-1.51, P < .001). Chronic conditions showed higher odds of future use (aOR = 1.19, 95% CI, 1.08-1.32, P < .001), whereas poorer general health was associated with lower odds across all outcomes. Fewer emergency room/urgent care visits, lower education, and income levels were associated with less favorable attitudes across outcomes. Higher digital health literacy (aOR = 1.03-1.04, all P < .001) and AI knowledge (aOR = 1.28-1.37, all P < .001) showed associations with higher odds across outcomes; privacy concerns were linked to lower odds (eg, future use: aOR = 0.65, 95% CI, 0.63-0.68, P < .001). DISCUSSION: Findings reveal a paradox-patients expressed conditional trust and comfort yet remained reluctant to adopt AI scribes, with privacy concerns and low awareness as key barriers. CONCLUSION: Targeted interventions addressing digital literacy, privacy safeguards, and clinician-patient communication about AI scribes are needed before widespread adoption.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".