Job Satisfaction of Research Personnel in Orthopaedic Trauma Surgery
Bibliographic record
Abstract
Background: The role of research personnel (e.g., research assistants, research coordinators, research managers, etc.) is critical to the success of clinical trials in orthopaedic surgery. Retention of research personnel is a challenge faced by many academic surgical researchers. Limited investigation has been conducted to identify and quantify factors that lead to low retention rates, especially in the field of orthopaedic surgery clinical research. Methods: We developed an electronic survey, containing the validated Job Satisfaction Survey (JSS), to evaluate job satisfaction, career path, and educational pathways in the context of long-term retention of research personnel working in orthopaedic surgery. We distributed the anonymized survey to research personnel who currently or had previously participated in at least 1 orthopaedic trauma clinical trial coordinated by a university-affiliated surgical methods center. Results: Seventy-two research personnel working on clinical orthopaedic studies completed the survey (43%). Using the JSS, overall respondent scores (mean 143.8, SD 26.6) fell on the border of the ambivalent and satisfaction categories. The lowest mean scores, representing dissatisfaction (scores <12), were seen within the promotion (11.4, SD 4.9) and pay (11.9, SD 5.1) subscales. Higher pay was the most common factor that would increase respondents' satisfaction in their current position (72%). Almost half (46%) expressed funding being a barrier to accessing continuing education, and 54% were unsure or considered clinical research in orthopaedic trauma a temporary position. Four main themes arose from the qualitative portion of the survey: (1) appreciation and involvement, (2) institutional barriers, (3) training, and (4) support from the principal investigator. Conclusions: Research personnel in clinical orthopaedic trauma surgery are a highly motivated group with job satisfaction bordering ambivalence into satisfaction. Despite the desire to grow in their positions, pay and inadequate funding to support continuing education opportunities are barriers. The qualitative findings provide additional insights into how job satisfaction and retention can be improved among clinical research personnel in orthopaedic trauma surgery. Level of Evidence: Level III. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".