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Record W4316672335 · doi:10.2147/jhl.s393177

A Needs Assessment Survey of Division Chiefs at an Academic Children’s Hospital

2023· article· en· W4316672335 on OpenAlex
Donna L. Johnston, Lindy Samson, Mona Jabbour

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Healthcare Leadership · 2023
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPreparednessMedical educationDemographicsNeeds assessmentPsychologyDivision (mathematics)MedicinePolitical scienceSociology

Abstract

fetched live from OpenAlex

Purpose: The Division Chief at an academic health sciences centre has many leadership roles and responsibilities. There are no data on leadership training needs for Division Chiefs, and so we sought to design and implement a needs assessment for pediatric Division Chiefs at CHEO, a pediatric academic health sciences centre in Eastern Ontario, Canada. Methods: A needs assessment survey was developed with the aim to document demographics, preparedness for the role of Division Chief and desired leadership training for the role. This survey was piloted, revised and then distributed to all the Division Chiefs at our institution. The results of each question were collated, and simple descriptive statistics were calculated. Results: The survey was completed by 22 of 31 Division Chiefs. The majority of respondents were from the Department of Pediatrics (63.6%), followed by Surgery (20%), Psychiatry (3.3%) and Laboratory Medicine (3.3%). Their mean length of time as Division Chief was 5.5 years. Seventy-seven percent had concurrent leadership roles in addition to the role of Division Chief. None felt they were very well prepared for the role, five felt they were somewhat well prepared, nine were neutral, five were somewhat unprepared and three were very unprepared for the role. Half of the respondents received mentoring, either formal or informal, for their role and all but one felt that formal mentoring would have been useful. In terms of desired training, the Division Chiefs felt they had the most knowledge and skills in patient safety. All wanted training in developing divisional budgets, and many desired training in supporting the academic mission of the Division. Conclusion: Overall, this needs assessment identified an unmet need for leadership training and development among Division Chiefs. The findings are being used to optimize onboarding of Division Chiefs and an ongoing leadership development program targeted at this group.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.392
GPT teacher head0.501
Teacher spread0.110 · 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