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Record W2899222263 · doi:10.1111/apa.14634

The therapeutic space and doctor–parent relationship in paediatrics: trainees’ experiences and perspectives

2018· article· en· W2899222263 on OpenAlexaff
Bonnie Arzuaga, Carter R. Petty, Annie Janvier

Bibliographic record

VenueActa Paediatrica · 2018
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCenter for Clinical and Translational Research
KeywordsMedicineFamily medicinePediatrics

Abstract

fetched live from OpenAlex

AIM: To explore paediatric trainees' experiences and perspectives regarding interactions and relationships between physicians and patients' parents. METHODS: Email survey was sent to AAP Section of Pediatric Trainees members. Trainees were asked about 40 interactions with parents as well as perceived benefits/risks and potential influences. Analysis of associations between variables and perspectives/experiences used chi-square and Fisher exact. RESULTS: Three hundred and seventy surveys were completed. Respondents participated in a median of nine interactions (IQR 7-13; range 0-37): 99.7% participated in at least one; 52% in 5-10; 41% in >10. 50% reported refusing to participate in at least one interaction following parental request; 8% refused 5-10; 1% refused >10. Electronic communication/social media domain had highest refusals and most interactions respondents believed should never be allowed. 94% agreed that interactions may be beneficial to providers: 75% identified at least one benefit; 86% one risk. Respondents who are parents or female reported increased interactions. CONCLUSION: A variety of interactions with patient's parents are common amongst paediatric trainees, who identify risks and benefits. Disagreements relative to acceptability of certain interactions points to the need for additional research. A reflective educational approach, rather than a prescriptive one, may help trainees better manage these relationships.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.153
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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 teacher head, 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
Published2018
Admission routes1
Has abstractyes

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