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Record W2193377030 · doi:10.2196/mededu.4576

A Novel Service-Oriented Professional Development Program for Research Assistants at an Academic Hospital: A Web-Based Survey

2015· article· en· W2193377030 on OpenAlexvenueno aff
Robert Li Kitts, Kyle John Koleoglou, Jennifer Elysia Holland, Eliza Haapaniemi Hutchinson, Quincy Nang, Clare M. Mehta, Chau Minh Tran, Laurie N. Fishman

Bibliographic record

VenueJMIR Medical Education · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationProfessional developmentService (business)Health professionalsQuality (philosophy)MedicineHealth careBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: Research assistants (RAs) are hired at academic centers to staff the research and quality improvement projects that advance evidence-based medical practice. Considered a transient population, these young professionals may view their positions as stepping-stones along their path to graduate programs in medicine or public health. OBJECTIVE: To address the needs of these future health professionals, a novel program-Program for Research Assistant Development and Achievement (PRADA)-was developed to facilitate the development of desirable professional skill sets (ie, leadership, teamwork, communication) through participation in peer-driven service and advocacy initiatives directed toward the hospital and surrounding communities. The authors hope that by reporting on the low-cost benefits of the program that other institutions might consider the utility of implementing such a program and recognize the importance of acknowledging the professional needs of the next generation of health care professionals. METHODS: In 2011, an anonymous, Web-based satisfaction survey was distributed to the program membership through a pre-established email distribution list. The survey was used to evaluate demographics, level of participation and satisfaction with the various programming, career trajectory, and whether the program's goals were being met. RESULTS: Upon the completion of the survey cycle, a 69.8% (125/179) response rate was achieved with the majority of respondents (94/119, 79.0%) reporting their 3-year goal to be in medical school (52/119, 43.7%) or nonmedical graduate school (42/119, 35.3%). Additionally, most respondents agreed or strongly agreed that PRADA had made them feel more a part of a research community (88/117, 75.2%), enhanced their job satisfaction (66/118, 55.9%), and provided career guidance (63/117, 53.8%). Overall, 85.6% of respondents (101/118) agreed or strongly agreed with recommending PRADA to other research assistants. CONCLUSIONS: High response rate and favorable outlook among respondents indicate that the program had been well received by the program's target population. The high percentage of respondents seeking short-term entry into graduate programs in health care-related fields supports the claim that many RAs may see their positions as stepping-stones and therefore could benefit from a professional development program such as the one described herein. Strong institutional support and sustainable growth and participation are other indications of early success. Further evaluation is necessary to assess the full impact of the program, particularly in areas such as job satisfaction, recruitment, retention, productivity, and career trajectory, but also in reproducibility in other institutions.

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)0.010
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.378
GPT teacher head0.633
Teacher spread0.255 · 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 designObservational
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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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