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Record W4307054693 · doi:10.1093/pch/pxac100.095

96 Impact and Feasibility of a Pediatric Social Determinants of Health Questionnaire: A Pilot Mixed-Methods Study

2022· article· en· W4307054693 on OpenAlexaff
Matthew Carwana, Taylor Ricci, Alesia Dicicco, Ethan Ponton, Damian Duffy, Rebecca Courtemanche, William Lau, Tanjot K. Singh, Christine Loock

Bibliographic record

VenuePaediatrics & Child Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of British ColumbiaBC Children's Hospital
Fundersnot available
KeywordsThematic analysisSocioeconomic statusContext (archaeology)Social determinants of healthDescriptive statisticsHealth carePsychologyMedicineFamily medicineQualitative researchNursingPublic healthEnvironmental healthPopulationSociologyPolitical science

Abstract

fetched live from OpenAlex

Abstract Background Social determinants of health (SDoH)—which are factors such as socioeconomic status (SES), access to transportation, food and housing security, disability and social supports—have been shown to influence up to 50% of health in patients. The project team developed a SDoH Questionnaire which evolved into what is now referred to as BEARS (Barriers to Care, Economic Factors, Adversity, Resiliency, Social Capital). Part of the BEARS Questionnaire includes an optional section for inquiring about Adverse Childhood Experiences (ACEs). Objectives The primary purpose of this study was to evaluate the impact and feasibility of the BEARS Questionnaire. Additional objectives were to assess the utility and functionality of the BEARS Questionnaire as a social history-taking tool, including the cumulative ACEs questions, and obtain suggestions for improvement of the tool. Design/Methods This was a mixed methods pilot study that consisted of quantitative surveys and qualitative structured interviews with clinicians who had experience using the BEARS Questionnaire. Descriptive statistics were performed on all survey results. Thematic analysis was performed on clinician interviews with recurrent themes being identified through iterative analysis and tagged quotations. Results 15 clinicians completed the quantitative survey and five took part in a qualitative interview. Study participants included surgeons, pediatricians, speech language pathologists, social workers and nurse clinicians. The BEARS Questionnaire changed clinician practice by increasing the frequency and breadth of social screening in their patients and optimizing care to fit their patients’ social context. Participants described the BEARS as an effective screening tool for SDoH and ACEs that was feasible to implement into their clinic workflow. Three themes emerged from our interviews: (1) Thorough social history taking highlights family resiliency and improves clinician-patient rapport, (2) Screening for ACEs is acceptable and feasible in a safe clinical environment, and (3) Social screening is feasible in a busy clinical environment and there is room for improvement. Conclusion This study highlights the importance of social screening in pediatric patients and their families, and how using a social screening tool allows providers to tailor care for a patients’ social context. The BEARS Questionnaire is feasible to implement within the context of a busy clinic. Finally, despite being a sensitive topic, an ACEs questionnaire can be incorporated when done in a trauma-informed way, and in the context of a longitudinal therapeutic relationship.

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)0.053
metaresearch head score (Gemma)0.036
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 score0.053
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.175
GPT teacher head0.528
Teacher spread0.354 · 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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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