Cyberbullying Among Traditional and Complementary Medicine Practitioners in the Workplace: Protocol for a Cross-sectional Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Cyberbullying is becoming prevalent among health care professionals and may cause a variety of mental health issues. Traditional and complementary medicine practitioners remain an important pillar of the health care system in Malaysia. OBJECTIVE: This paper presents a study protocol for an online survey (Cyberbullying Among Traditional and Complementary Medicine Practitioner [TCMPs]) that will collect the first nationwide representative data on cyberbullying behavior among traditional and complementary medicine practitioners in Malaysia. The objectives of the survey are to (1) evaluate the cyberbullying behavior among traditional and complementary medicine practitioners in Malaysia, (2) identify sociodemographic and social factors related to cyberbullying, and (3) evaluate the association between cyberbullying behavior, sociodemographic, and social factors. METHODS: A snowball sampling strategy will be applied. Traditional and complementary medicine practitioners who are permanent Malaysian residents will be randomly selected and invited to participate in the survey (N=1023). Cyberbullying behavior will be measured using the Cyberbullying Behavior Questionnaire (CBQ). Data on the following items will be collected: work-related bullying, person-related bullying, aggressively worded messages, distortion of messages, sending offensive photos/videos, hacking computers or sending a virus or rude message, and threatening messages about personal life or family members. We will also collect data on participants' sociodemographic characteristics, social factors, and substance abuse behavior. RESULTS: This cross-sectional descriptive study was registered with Research Registry (Unique Identifying Number 6216; November 05, 2020). This research work (substudy) is planned under a phase 1 study approved by the Research Management Centre, Xiamen University Malaysia. This substudy has been approved by the Research Ethics Committee of Xiamen University Malaysia (REC-2011.01). The cross-sectional survey will be conducted from July 01, 2021, to June 30, 2022. Data preparation and statistical analyses are planned from January 2022 onward. CONCLUSIONS: The current research can contribute to identify the prevalence of workplace cyberbullying among Malaysian traditional and complementary medicine practitioners. The results will help government stakeholders, health professionals, and education professionals to understand the psychological well-being of Malaysian traditional and complementary medicine practitioners. TRIAL REGISTRATION: Research Registry Unique Identifying Number 6216; https://tinyurl.com/3rsmxs7u. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/29582.
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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 | 0.010 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".