Are There Barriers for Professional Development of Women Dentists? A Qualitative Study in Saudi Arabia
Bibliographic record
Abstract
Globally, there is an upward trend in the number of women applying to dental schools and entering the profession of dentistry. Women dentists aim to advance their careers; however, differences exist between men and women dentists regarding leadership positions and work titles. For example, in Saudi Arabia, women usually occupy lower ranked positions than men in the Saudi public sector, and they are, therefore, paid less than their male counterparts. This study aimed to explore the possible barriers to Saudi women dentists' professional advancement using a qualitative descriptive study design. Specifically, semistructured in-depth interviews were conducted with 13 women practicing dentistry in the Makkah region of Saudi Arabia. The interviews were audio-recorded and transcribed verbatim, and the data were interpreted using qualitative content analysis (NVivo 11; QRS International). The results revealed 4 challenges that might delay the participants' career development. These include family-related challenges, sociocultural challenges, workplace challenges, and transportation issues. From this perspective, some perceived barriers to the professional development of women dentists were found that might not be unique to Saudi Arabia, and the article's suggestions and recommendations aim to minimize the effects of these barriers impeding women's advancement in dentistry in Saudi Arabia. Knowledge Transfer Statement: This study makes an important contribution to knowledge on this topic. These results will aid policy makers' efforts to create supportive work environments through gender-specific incentives that meet the current professional and family needs of women dentists, particularly those in Saudi Arabia.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".