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Record W4280578275 · doi:10.2196/38126

Women Physicians in Transition Learning to Navigate the Pipeline from Early to Mid-Career: Protocol for a Qualitative Study

2022· article· en· W4280578275 on OpenAlexvenueno aff
Tiffany I. Leung, Karen Wang, Tammy Lin, Geneen T Gin, Sima Pendharkar, Chwen‐Yuen Angie Chen

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsThematic analysisCareer PathwaysQualitative researchMedical educationGrounded theoryCertificationMedicinePsychologyNursingSociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Women physicians face unique obstacles while progressing through their careers, navigating career advancement and seeking balance between professional and personal responsibilities. Systemic changes, along with individual and institutional changes, are needed to overcome obstacles perpetuating physician gender inequities. Developing a deeper understanding of women physicians' experiences during important transition points could reveal both barriers and opportunities for recruitment, retention, and promotion, and inform best practices developed based on these experiences. OBJECTIVE: The aim is to learn from the experiences and perspectives of women physicians as they transition from early to mid-career, then develop best practices that can serve to support women physicians as they advance through their careers. METHODS: Semistructured interviews were conducted with women physicians in the United States in 2020 and 2021. Eligibility criteria included self-identification as a woman who is in the process of transitioning or who recently transitioned from early to mid-career stage. Purposeful sampling facilitated identification of participants who represented diversity in career pathway, practice setting, specialty, and race/ethnicity. Each participant was offered compensation for their participation. Interviews were audio-recorded and professionally transcribed. Interview questions were open-ended, exploring participants' perceptions of this transition. Qualitative thematic analysis will be performed. We will use an open coding and grounded theory approach on interview transcripts. RESULTS: The Ethics Review Committee of the Faculty of Health, Medicine, and Life Sciences at Maastricht University approved the study; Stanford University expedited review approved the study; and the University of California, San Diego certified the study as exempt from review. Twelve in-depth interviews of 50-100 minutes in duration were completed. Preliminary analyses indicate one key theme is a tension resulting from finite time divided between demands from a physician career and demands from family needs. In turn, this results in constant boundary control between these life domains that are inextricable and seemingly competing against each other within a finite space; family needs impinge on planned career goals, if the boundary between them is not carefully managed. To remedy this, women sought resources to help them redistribute home responsibilities, freeing themselves to have more time, especially for children. Women similarly sought resources to help with career advancement, although not with regard to time directly, but to first address foundational knowledge gaps about career milestones and how to achieve them. CONCLUSIONS: Preliminary results provide initial insights about how women identify or activate a career shift and how they marshaled resources and support to navigate barriers they faced. Further analyses are continuing as of March 2022 and are expected to be completed by June 2022. The dissemination plan includes peer-reviewed open-access journal publication of the results and presentation at the annual meeting of the American Medical Association's Women Physicians Section.

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 imitation

Not 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.

metaresearch head score (Codex)0.065
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.065
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.048
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.003
Science and technology studies0.0080.004
Scholarly communication0.0030.004
Open science0.0040.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0500.008

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.

Opus teacher head0.361
GPT teacher head0.592
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreProtocol

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".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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