The association of physician assistant/associate demographic and practice characteristics with perceptions of value of certification
Bibliographic record
Abstract
BACKGROUND: To determine physician assistant/associate (PA) perceptions of the value of certification and explore how they vary across demographic and practice characteristics. METHODS: We conducted a cross-sectional online survey between March and April 2020 with PAs participating in the longitudinal pilot program for recertification administered by the National Commission on Certification of Physician Assistants (NCCPA). The survey was distributed to 18,147 PAs, of which 10,965 participated (60.4% response rate). In addition to descriptive statistics, chi-square tests were conducted on demographics and specialty to examine if perceptions of value of certification (1 global and 10 items measuring specific domains) were associated with a particular PA profile. A series of fully adjusted multivariate logistic regressions were performed, exploring the relationship between PA characteristics and the value of certification items. RESULTS: Most PAs strongly agreed/agreed that certification helps with fulfilling licensure requirements (9,578/10,893; 87.9%), helps with updating medical knowledge (9,372/10,897; 86.0%), and provides objective evidence of continued competence (8,875/10,902; 81.4%). The items receiving the lowest percentage of responses for strongly agreeing/agreeing were for certification providing no value (1,925/10,887; 17.7%), helping with professional liability insurance (5,076/10,889; 46.6%), and competing with other providers for clinical positions (5,661/10,905; 51.9%). Age 55 and older and practicing in dermatology and psychiatry were among the strongest predictors of less favorable views. PAs from underrepresented in medicine (URiM) backgrounds had more positive perceptions. CONCLUSIONS: Overall, the findings indicate that PAs value certification; however, perceptions varied by demographics and specialties. PAs who were younger, from URiM backgrounds, and practicing in primary care specialties had among the most favorable perspectives. Continued feedback monitoring is critical in ensuring certification is relevant and meaningful in supporting PAs across demographics and specialties. Measuring PA perceptions of the value of certification is essential to understanding how to support the PA profession's current and future credentialing needs and those who license and hire PAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".