MétaCan
Menu
Back to cohort
Record W2402451040 · doi:10.1002/2327-6924.12378

Nurse practitioner screening for childhood adversity among adult primary care patients

2016· article· en· W2402451040 on OpenAlexaff
Karen A. Kalmakis, Genevieve E. Chandler, Susan Jo Roberts, Katherine Leung

Bibliographic record

VenueJournal of the American Association of Nurse Practitioners · 2016
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsHealth Sciences North
FundersAmerican Nurses Foundation
KeywordsNurse practitionersPrimary careMedicinePrimary health careFamily medicineNursingHealth careEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Researchers have demonstrated an association between experiencing childhood abuse and multiple chronic health conditions in adulthood, yet this evidence has not been routinely translated to practice. The purpose of this research study was to examine nurse practitioner (NP) practices, skills, attitudes, and perceived barriers associated with screening adult patients for childhood abuse to determine the extent to which evidence of the association between childhood abuse and negative health outcomes has been translated to NP practice. METHODS: A mixed-method approach with web-based questionnaires and online focus groups was used to examine NP screening for histories of childhood abuse. CONCLUSIONS: A total of 188 complete NP surveys were analyzed along with data from focus groups with 12 NPs. One third of the NPs regularly screened for childhood abuse and believed screening was their responsibility. Six barriers, including insufficient time and lack of confidence when inquiring about abuse, were significantly associated with NP screening practices. The focus group participants discussed how and when one should ask about childhood abuse, and the need for education about screening. IMPLICATIONS FOR PRACTICE: Time constraints and NPs' lack of confidence in their ability to screen for histories of childhood abuse must be addressed to encourage routine screening in primary care practice.

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)0.001
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 score0.070
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.268
Teacher spread0.261 · 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

Citations37
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Association of Nurse PractitionersSame topicChild Abuse and TraumaFrench-language works237,207