COVID-19 vaccine attitudes among mental health professionals in the WHO’s global clinical practice network
Bibliographic record
Abstract
Although COVID-19 vaccines have demonstrated efficacy, there is variability in health professionals' attitudes towards these agents. Factors associated with mental health professionals' attitudes towards COVID-19 vaccination are not well understood. We investigated these factors by administering a newly developed measure, the COVID-19 Vaccine Attitudes Questionnaire (C-VAQ), to members of the World Health Organization's Global Clinical Practice Network (GCPN) of mental health professionals. 1,931 GCPN members representing all world regions participated between July 28 and September 7, 2021. Mental health professionals' attitudes towards COVID-19 vaccination were assessed in one of five languages (Chinese, English, French, Japanese, Russian, or Spanish) using the C-VAQ. Internal consistency, factor structure, and predictive validity of the C-VAQ were examined, and a multiple-linear regression model was employed to assess C-VAQ score predictors, including sociodemographic variables (age, gender, WHO region, country income level, profession, and years of professional experience) as well as country mortality rate and the stringency of each country's response to COVID-19. The C-VAQ demonstrated good internal consistency and external validity. Items loaded on to a single factor. Having received a COVID-19 vaccine, higher country mortality rate, and higher stringency index was significantly associated with more positive vaccine attitudes. Lower age, residing in a low-and-middle income country, and living in Asia were all was significantly associated with less positive vaccine attitudes. The C-VAQ scores were negatively correlated with the number of concerns about the COVID-19 vaccination. The C-VAQ was useful in demonstrating the extent to which additional work is needed to improve mental health professionals' attitudes towards COVID-19 vaccines globally. Relatively poorer attitudes toward vaccination among some mental health clinicians around the world suggests the need for broad, multi-pronged interventions.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".