Response of Practicing Chiropractors during the Early Phase of the COVID-19 Pandemic: A Descriptive Report
Bibliographic record
Abstract
OBJECTIVE: The coronavirus disease-2019 (COVID-19) pandemic has strained all levels of healthcare and it is not known how chiropractic practitioners have responded to this crisis. The purpose of this report is to describe responses by a sample of chiropractors during the early stages of the COVID-19 pandemic. METHODS: We used a qualitative-constructivist design to understand chiropractic practice during the COVID-19 pandemic, as described by the participants. A sample of chiropractic practitioners (doctors of chiropractic, chiropractors) from various international locations were invited to participate. Each described the public health response to COVID-19 in their location and the actions that they took in their chiropractic practices from April 20 through May 4, 2020. A summary report was created from their responses and common themes were identified. RESULTS: Eighteen chiropractic practitioners representing 17 locations and 11 countries participated. A variety of practice environments were represented in this sample, including, solo practice, mobile practice, private hospital, US Veterans Administration health care, worksite health center, and group practice. They reported that they recognized and abided by changing governmental regulations. They observed their patients experience increased stress and mental health concerns resulting from the pandemic. They adopted innovative strategies, such as telehealth, to do outreach, communicate with, and provide care for patients. They abided by national and World Health Organization recommendations and they adopted creative strategies to maintain connectivity with patients through a people-centered, integrated, and collaborative approach. CONCLUSION: Although the chiropractors in this sample practiced in different cities and countries, their compliance with local regulations, concern for staff and patient safety, and people-centered responses were consistent. This sample covers all 7 World Federation of Chiropractic regions (ie, African, Asian, Eastern Mediterranean, European, Latin American, North American, and Pacific) and provides insights into measures taken by chiropractors during the early stages of the COVID-19 pandemic. This information may assist the chiropractic profession as it prepares for different scenarios as new evidence about this disease evolves.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".