Uptake of telehealth in Parkinson's disease clinical care and research during the COVID-19 pandemic
Bibliographic record
Abstract
INTRODUCTION: Traditionally, medical care and research in Parkinson's disease (PD) have been conducted with in-person encounters. The recent COVID-19 pandemic has profoundly impacted the delivery of in-person clinical care and clinical research. We conducted an online survey of active clinician members of the Parkinson Study Group (PSG) to evaluate the adoption of various non-face-to-face methods in clinical practice and research in PD during the COVID-19 pandemic. METHODS: We conducted a survey using the open-access online SurveyMonkey tool (http://www.surveymonkey.com). The survey had 27 items and was designed to elucidate clinical/research care before and during the COVID-19 pandemic. The survey was sent to 414 active PSG members with weekly reminders and it remained accessible for 30 days from May 2020. RESULTS: We received 142 responses, of which 133 (93.7%) provided demographic data. The clinical use of virtual visits via synchronous video conferencing increased from 39.5% pre-COVID-19 to 94.6% during the COVID-19 pandemic. Lack of access for patients (68.2%) and patient resistance (51.4%) were the top barriers for its use. Approximately 70% respondents stated that 75-100% of their research activities were suspended during the COVID-19 pandemic. Many sites had to fill out protocol deviations (38.2%), protocol exceptions (25.5%) or change their research profile due to layoffs (16.8%). The overall use of video conferencing increased from 30.3% to 64.1%. CONCLUSION: The current results suggest a need for flexibility in conducting office visits and clinical trials in PD patients. Technology has the potential to enhance patient care and convenience, when in-person visits can be challenging.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".