Exploring patient experiences with a telehealth approach for the PRO-ACTIVE trial intervention in head and neck cancer patients
Bibliographic record
Abstract
INTRODUCTION: Following the COVID-19 directive to cease non-essential services, a rapid shift was made in the delivery of Speech Language Pathology (SLP) dysphagia management in the 3-arm, randomized PRO-ACTIVE trial. To inform future programs, this study explored patients' experiences with telehealth when the planned in-person SLP intervention was moved to a telehealth modality. METHODS: A theory-guided qualitative descriptive approach was used. Willing participants who had received at least one telehealth swallowing therapy session participated in a one-time semi-structured interview. Interview transcripts were subjected to a standard qualitative content/theme analysis. Researchers reviewed all transcripts and used a multi-step analysis process to build a coding framework through consensus discussion. Summaries and key messages were generated for each code. RESULTS: Eleven participants recounted their telehealth experiences and reported feeling satisfied, comfortable and confident with the session(s). They identified that previous experience with teleconferencing, access to optimal technical equipment, clinician skill, and caregiver assistance facilitated their telehealth participation. Participants highlighted that telehealth was beneficial as it reduced commuting time, COVID-19 exposure and fatigue from travel; and also allowed caregiver participation particularly during COVID. In comparing their in-person SLP sessions to telehealth sessions, limitations were also identified, including: lack of previous experience with and/or poor access to technology, and less opportunity for personalization. Participants indicated that use of phone alone was less preferred than an audio/video platform. DISCUSSION: Patients reported that overall, telehealth sessions did not compromise their learning experience when compared to in-person sessions. Patients benefited from use of telehealth in several ways despite some limitations of the use of technology. Patient feedback about telehealth provides an important perspective that may be critical to inform best practices for care delivery.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".