Keep in touch (KIT): perspectives on introducing internet-based communication and information technologies in palliative care
Bibliographic record
Abstract
BACKGROUND: Hospitalized palliative patients need to keep in touch with their loved ones. Regular social contact may be especially difficult for individuals on palliative care in-patient units due to the isolating nature of hospital settings. Technology can help mitigate isolation by facilitating social connection. This study aimed to explore the acceptability of introducing internet-based communication and information technologies for patients on a palliative care in-patient unit. METHODS: In the first phase of the Keep in Touch (KIT) project, a diverse group of key informants were consulted regarding their perspectives on web-based communication on in-patient palliative care units. Participants included palliative patients, family members, direct care providers, communication and information technology experts, and institutional administrators. Data was collected through focus groups, interviews and drop-in consultations, and was analyzed for themes, consensus, and major differences across participant groups. RESULTS: Hospitalized palliative patients and their family members described the challenges of keeping in touch with family and friends. Participants identified numerous examples of ways that communication and information technologies could benefit patients' quality of life and care. Patients and family members saw few drawbacks associated with the use of such technology. While generally supportive, direct care providers were concerned that patient requests for assistance in using the technology would place increased demands on their time. Administrators and IT experts recognized issues such as privacy and costs related to offering these technologies throughout an organization and in the larger health care system. CONCLUSIONS: This study affirmed the acceptability of offering internet-based communication and information technologies on palliative care in-patient units. It provides the foundation for trialing these technologies on a palliative in-patient unit. Further study is needed to confirm the feasibility of offering these technologies at the bedside.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".