Influence of Social Media on Applicant Perceptions of Anesthesiology Residency Programs During the COVID-19 Pandemic: Quantitative Survey
Bibliographic record
Abstract
BACKGROUND: Social media may be an effective tool in residency recruitment, given its ability to engage a broad audience; however, there are limited data regarding the influence of social media on applicants' evaluation of anesthesiology residency programs. OBJECTIVE: This study evaluates the influence of social media on applicants' perceptions of anesthesiology residency programs during the COVID-19 pandemic to allow programs to evaluate the importance of a social media presence for residency recruitment. The study also sought to understand if there were differences in the use of social media by applicant demographic characteristics (eg, race, ethnicity, gender, and age). We hypothesized that given the COVID-19 pandemic restrictions on visiting rotations and the interview process, the social media presence of anesthesiology residency programs would have a positive impact on the recruitment process and be an effective form of communication about program characteristics. METHODS: All anesthesiology residency applicants who applied to Mayo Clinic Arizona were emailed a survey in October 2020 along with statements regarding the anonymity and optional nature of the survey. The 20-item Qualtrics survey included questions regarding subinternship rotation completion, social media resource use and impact (eg, "residency-based social media accounts positively impacted my opinion of the program"), and applicant demographic characteristics. Descriptive statistics were examined, and perceptions of social media were stratified by gender, race, and ethnicity; a factor analysis was performed, and the resulting scale was regressed on race, ethnicity, age, and gender. RESULTS: The survey was emailed to 1091 individuals who applied to the Mayo Clinic Arizona anesthesiology residency program; there were 640 unique responses recorded (response rate=58.6%). Nearly 65% of applicants reported an inability to complete 2 or more planned subinternships due to COVID-19 restrictions (n=361, 55.9%), with 25% of applicants reporting inability to do any visiting student rotations (n=167). Official program websites (91.5%), Doximity (47.6%), Instagram (38.5%), and Twitter (19.4%) were reported as the most used resources by applicants. The majority of applicants (n=385, 67.3%) agreed that social media was an effective means to inform applicants, and 57.5% (n=328) of them indicated that social media positively impacted their perception of the program. An 8-item scale with good reliability was created, representing the importance of social media (Cronbach α=.838). There was a positive and statistically significant relationship such that male applicants (standardized β=.151; P=.002) and older applicants (β=.159; P<.001) had less trust and reliance in social media for information regarding anesthesiology residency programs. The applicants' race and ethnicity were not associated with the social media scale (β=-.089; P=.08). CONCLUSIONS: Social media was an effective means to inform applicants, and generally positively impacted applicants' perception of programs. Thus, residency programs should consider investing time and resources toward building a social media presence to improve resident recruitment.
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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 | 0.004 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".