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Record W4410266043 · doi:10.2196/70505

Continuous Rural High School Educational Outreach and Lasting Impact on Health Care Career Attitudes: Qualitative Pilot Study

2025· article· en· W4410266043 on OpenAlexvenueno aff
Rebecca M. Bolen, Meagan Flesch, Jerrica Dennis, Logan Shouse, Mark E. Payton, David Ross

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintOutreachMedical educationHealth carePsychologyPeer reviewMedicineNursingPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Background: Rural communities face persistent challenges in recruiting and retaining health care professionals. Research has shown that individuals from rural backgrounds are more likely to return to practice in these areas, yet most existing pipeline programs focus on undergraduate and medical students rather than high school students. Early exposure to health care careers is essential, as many students have already selected their career paths by the time they enter college. A previous study conducted in 2020 analyzed the effects of a single educational workshop at a rural high school in New Hampshire. The results suggested that students had a better understanding of the health care field. Objective: This study evaluates the impact of an ongoing educational outreach program designed to introduce rural high school students to diverse health care professions. Methods: This study was conducted at West Grand High School, a rural high school in Kremmling, Colorado, between September and December 2023. The intervention consisted of 4 monthly sessions, each focusing on a different medical specialty-primary care, sports medicine, dermatology, and neurology. These sessions, led by second-year medical students, provided an overview of common conditions, treatment approaches, and various health care roles involved in patient care. Participants completed pre- and postsession surveys assessing their interest in health care careers, perceived barriers, and likelihood of returning to their rural hometown to practice. A follow-up survey was conducted 4 months after the final session to assess long-term impact. Results: While individual session surveys showed no significant changes, overall interest in and likelihood of pursuing a health care career increased significantly over the course of the presentation series (P=.03 and P=.04, respectively). However, there was no significant change in students' likelihood of returning to their rural hometowns to practice or their perceived access to resources for a health care career. Financial constraints (43/66, 65%) were identified as the most significant barrier, followed by lack of exposure (19/66, 29%) and support (17/66, 26%), while interest and education were least likely perceived as obstacles. Conclusions: This study highlights the importance of early and sustained outreach efforts in rural communities to increase awareness of diverse health care career pathways. While short-term educational interventions can positively influence career interest, long-term mentorship and structured support systems are essential for fostering a sustained commitment to rural health care careers. Future initiatives should integrate financial counseling, ongoing mentorship, and collaborations with existing rural pipeline programs to enhance the effectiveness of such interventions.

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)0.011
metaresearch head score (Gemma)0.009
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0020.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.150
GPT teacher head0.614
Teacher spread0.465 · 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
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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