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Record W4403682991 · doi:10.1093/pch/pxae067.083

84 Methods to screen caregivers for previous and current substance use in the paediatric office: A scoping review

2024· review· en· W4403682991 on OpenAlexaboutno aff
Sebastian Steven, Matt Carwana, Akash Grewal

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSubstance useCurrent (fluid)MedicinePsychologyEngineeringPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Paediatric healthcare providers have been shown to miss opportunities to screen caregivers for substance use. Individuals who use or have used substances face general healthcare barriers and may disengage with the system to avoid stigma or discrimination. Poorly worded or administered substance use screening practices by paediatricians could lead to retraumatization or judgment of caregivers that may affect the ability to continue providing healthcare to the child. There is limited information in the literature regarding best approaches for screening caregivers for substance use in paediatrics. Objectives The unique objective of this review was to identify current methods for, approaches to, and acceptability of caregiver substance use screening in paediatric offices. Design/Methods Searches were performed in CINAHL, PsycInfo, MEDLINE, and Social Sciences Abstracts databases with results limited from 2000 to 2023. Keywords included “perinatal”, “postnatal” “paediatric OR paediatric”, “substance use” OR “substance abuse” OR substances OR “alcohol use” OR “alcohol abuse” OR “addiction”, AND “screening”. Studies must have been conducted in Canada, the USA, Australia, or Scandinavia. Literature that was published in a language other than English, described screening caregivers for substance use using biological samples, or that focused solely on screening pregnant caregivers for substance use was excluded. Individual approaches to and provider and patient perspectives on screening were identified. Three authors completed title, abstract, and full text screening in Covidence screening software. Qualitative thematic coding identified geographical setting, the specific paediatric clinical setting, substances for which each study screened, characteristics of the participants, method of screening, and feedback related to acceptability, outcomes, or methods of screening. Results Practitioners used standardized and informal substance use screening tools. This review found that paediatric practitioners reported gaps in guidance on how best to screen caregivers for substance use and a desire for more improvement. Lack of guidance made it uncomfortable to screen caregivers. Increased comfort with screening was noted when a social needs survey was used as guidance. Caregivers were generally highly comfortable being screened for substance use and felt it was an acceptable action for paediatricians to undertake. However, the input of families in caregiver substance use screening methods was otherwise lacking. Substance use questions were often paired with questions asking caregivers to rate acceptability while other studies simply used the openness of being approached or absence of objections as acceptance of being screened. None of the studies identified in this review included the ability for families to participate more fully in screening acceptability or design. Conclusion Family engagement in research regarding the ideal acceptability and design of screening methods is lacking while paediatric healthcare providers continue to be uncomfortable screening caregivers for substance use and wish for improved methods that facilitate trust with families. Further research into the design of trauma-informed caregiver substance use screening in paediatric settings may be needed.

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)0.025
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.033
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.097
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0330.030
Science and technology studies0.0020.002
Scholarly communication0.0060.007
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.103
GPT teacher head0.459
Teacher spread0.356 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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