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Record W4411067205 · doi:10.1177/23743735251344505

An Assessment of Harm in Adults—Adverse Childhood Experiences Screening in Primary Care: A Survey-Based Study

2025· article· en· W4411067205 on OpenAlexaffabout
Katelyn M. Inch, Craig Olmstead, Brenna A. Kaschor

Bibliographic record

VenueJournal of Patient Experience · 2025
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsWestern University
Fundersnot available
KeywordsAdverse Childhood ExperiencesMedicinePrimary careFeelingAdverse effectHarmFamily medicinePediatricsPsychiatryPsychologyMental healthInternal medicine

Abstract

fetched live from OpenAlex

The Adverse Childhood Experiences Questionnaire (ACE-Q) screens for adverse childhood experiences (ACEs), which are linked to increased disease risk. Although pediatric studies report no adverse effects of ACE-Q use, primary care data is limited. This study examined adult patients’ experiences with ACE-Q screening in primary care. Adults (18+) at a primary care center in London, Ontario, completed the ACE-Q and a follow-up questionnaire evaluating ACE screening experience. Correlations assessed relationships between ACE-Q scores and follow-up responses. Among 260 participants, 81% reported at least one ACE. Most (82%) felt comfortable discussing stressful childhood experiences with their healthcare provider. Higher ACE scores were associated with increased discomfort (r s = −0.166, P = 0.007), feeling upset by the ACE-Q (r s = 0.173, P = 0.005), and greater interest in learning about ACEs (r s = 0.177, P = 0.004). Overall, ACE-Q screening in primary care was generally well-received, with most patients recognizing its relevance despite some discomfort. These findings highlight the potential for integrating ACE screening into routine primary care to address long-term health risks. Further research is needed to confirm findings and optimize screening practices.

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 score0.016
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.364
Teacher spread0.344 · 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
Published2025
Admission routes2
Has abstractyes

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