An Electronically Delivered Person-Centered Narrative Intervention for Persons Receiving Palliative Care: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: In the health care setting, electronic health records (EHRs) are one of the primary modes of communication about patients, but most of this information is clinician centered. There is a need to consider the patient as a person and integrate their perspectives into their health record. Incorporating a patient's narrative into the EHR provides an opportunity to communicate patients' cultural values and beliefs to the health care team and has the potential to improve patient-clinician communication. This paper describes the protocol to evaluate the integration of an adapted person-centered narrative intervention (PCNI). This adaptation builds on our previous research centered on the implementation of PCNIs. The adaptation for this study includes an all-electronic delivery of a PCNI in an outpatient clinical setting. OBJECTIVE: This research protocol aims to evaluate the feasibility, usability, and effects of the all-electronic delivery of a PCNI in an outpatient setting on patient-reported outcomes. The first objective of this study is to identify the barriers and facilitators of an internet-based-delivered PCNI from the perspectives of persons living with serious illness and their clinicians. The second objective is to conduct acceptability, usability, and intervention fidelity testing to determine the essential requirements for the EHR integration of an internet-based-delivered PCNI. The third objective is to test the feasibility of the PCNI in an outpatient clinic setting. METHODS: Using a mixed method design, this single-arm intervention feasibility study was delivered over approximately 3 to 4 weeks. Patient participant recruitment was conducted via screening outpatient palliative care clinic schedules weekly for upcoming new palliative care patient visits and then emailing potential patient participants to notify them about the study. The PCNI was delivered via email and Zoom app. Patient-reported outcome measures were completed by patient participants at baseline, 24 to 48 hours after PCNI, and after the initial palliative care clinic visit, approximately 1 month after baseline. Inclusion criteria included having the capacity to give consent and having an upcoming initial outpatient palliative care clinic visit. RESULTS: The recruitment of participants began in April 2021. A total of 189 potential patient participants were approached via email, and 20 patient participants were enrolled, with data having been collected from May 2021 to September 2022. A total of 7 clinician participants were enrolled, with a total of 3 clinician exit interviews and 1 focus group (n=5), which was conducted in October 2022. Data analysis is expected to be completed by the end of June 2023. CONCLUSIONS: The findings from this study, combined with those from other PCNI studies conducted in acute care settings, have the potential to influence clinical practices and policies and provide innovative avenues to integrate more person-centered care delivery. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41787.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.051 | 0.007 |
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 source (direct Gemma or distilled Codex), 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".