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Record W2803948511 · doi:10.1093/pch/pxy054.140

PAEDIATRIC SCHOOL OUTREACH: DEMOGRAPHICS AND CLINICAL NEEDS OF A UNIQUE INNER-CITY STUDENT POPULATION

2018· article· en· W2803948511 on OpenAlexaffabout
Pamela Ng, Justine Cohen-Silver, Heather Yang, Aparna Swaminathan, Anne Wormsbecker

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsUniversity of TorontoSt Joseph's Health Centre
Fundersnot available
KeywordsMedicineOutreachFamily medicinePopulationLanguage barrierHealth carePediatricsEnvironmental health

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Paediatric School Outreach (PSO) clinic is a school-based health centre housed in a Kindergarten-Grade 8 public school. It serves an inner-city community impacted by the social determinants of health, such as language and income, which are barriers to accessing health care. This clinic focuses on developmental/behavioural, mental health and educational concerns. OBJECTIVES To characterize demographics, social determinants of health and some clinical characteristics of patients accessing services at PSO. By gaining a better understanding of the challenges of patients, services may be tailored to better suit patient/family needs. DESIGN/METHODS We conducted a retrospective chart review of children enrolled at PSO from November 2015 to March 2017. Data were obtained from demographic questionnaires and the electronic medical record. Analyses were performed in Microsoft Excel and SPSS (version 23) and are primarily descriptive. This work was funded by a faculty of medicine student research program and approved by research ethics boards at our hospital and school board. RESULTS 138 children, between the ages of 2 and 15 years (average birth year 2008) enrolled at PSO during the study period. 73% were male. 70% of patients were in Grade 1 or above at enrolment. Children tended to be Canadian born to immigrant mothers; 74% of children were born in Canada but only 34% of mothers were also Canadian-born. After Canada, Hungary was the second common maternal place of birth (12%). English was the most common language spoken by patients (71%), followed by Hungarian, Tibetan, Portuguese and Spanish. 58% of patients’ families had a household annual income (HAI) of <$30,000 and 18% a HAI of $30,000–49,999. 84% of 138 patients reported having a family physician. Referrals were made by school support team (54%), teacher (36%) or principal (28%). The common presenting concerns were behaviour (81%), school performance (60%), followed by social communication (51%) and emotional presentation (49%). Among 132 patients with clinical records, 13% were on any medication at enrolment; and 3% (4/132) on psychostimulants. 14% of patients were started on medication during the study period, most frequently psychostimulants (11%, 15/132). CONCLUSION PSO patients are culturally diverse and at least three quarters have HAIs below our city’s median of $65,829 (2015). The majority reported having a family physician but accessed our clinic for educational/behavioural concerns, suggesting PSO may be a stream-lined approach. With knowledge of maternal languages, we can begin to translate questionnaires and clinic materials. Further data analyses will better describe diagnoses and referrals made at the clinic.

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)0.002
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.419
Teacher spread0.372 · 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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