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Record W2604318615

Home visits in family medicine residency

2015· article· en· W2604318615 on OpenAlexaffvenueabout
Difat Jakubovicz, Anita Srivastava

Bibliographic record

VenueCanadian Family Physician · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsSt Joseph's Health Centre
Fundersnot available
KeywordsGraduation (instrument)MedicineFamily medicineHouse callAmbulatoryConfidence intervalMEDLINEGerontology
DOInot available

Abstract

fetched live from OpenAlex

Problem addressed There has been a decline in family physicians providing home visits to housebound patients. Objective of program To increase family medicine residents’ exposure to home visits; their comfort and skills in providing home visits; and their willingness to provide home visits after graduation. Program description Between 2000 and 2010, each family practice resident at St Joseph’s Health Centre Family Medicine Teaching Unit in Toronto, Ont, was assigned at least 1 housebound patient to care for longitudinally over 2 years; the rationale for this was to increase the sense of “ownership” and responsibility among residents for their assigned homebound patients. Starting in 2003, until the program’s conclusion in 2010, residents were asked to fill out surveys before and after the program to assess their comfort with and confidence in providing home visits, as well as their satisfaction with the program. Survey responses were analyzed for changes over the course of residency training. A total of 85 residents completed the home visit teaching program between 2003 and 2010 inclusive. Conclusion While residents’ willingness to provide home visits did not increase over the course of residency, their confidence in making housecalls did increase. There was also a trend toward increased confidence among residents in working with community agencies. Thus, having home visit patients be a part of resident practices might play an important role in increasing the likelihood that future family physicians will continue to care for their patients when those patients are no longer ambulatory.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.076
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.156
GPT teacher head0.410
Teacher spread0.254 · 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 routes3
Has abstractyes

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