Spanish-Speaking Hispanic Patients’ Information-Sharing Preferences During Hospitalization: An Exploratory Pilot Study
Bibliographic record
Abstract
BACKGROUND: Self-management of chronic conditions, such as cancer or diabetes, requires the coordination of care across multiple care settings. Current patient-centered, hospital-based care initiatives, including bedside nursing handoff and multidisciplinary rounds, often focus on provider information exchange and roles but fall short of the goals of participatory medicine, which recognize the right of patients to partner in their own care and play an active role in self-management. OBJECTIVE: This study aimed to elicit Spanish-speaking Hispanic patients' perspectives on the exchange and sharing of information during hospitalization. METHODS: This exploratory pilot study incorporated a qualitative descriptive approach by using Spanish language focus groups, posthospitalization, to determine patient-identified information needs during hospitalization. RESULTS: Participants preferred paper-based Spanish language medical information. Doctors and nurses were key information providers and communicated with participants verbally, usually with the assistance of a translator. Participants expressed a desire to be informed about medication and treatments, including side effects and why there were changes in medication during hospitalization. In addition, they expressed interest in knowing about the progress of their condition and when they could expect to go home. Emotional readiness to receive information about their condition and prognosis was identified as an individual barrier to asking questions and seeking additional information about their condition(s). CONCLUSIONS: Overall, participants shared positive experiences with providers during hospitalization and the usefulness of self-care instructions. Language was not recognized as a barrier by any of the participants. Nevertheless, future research on the influence of emotional readiness on the timing of medical information is needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".