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Is There a Need for Screening for Type 2 Diabetes in Seventh Graders?

2004· article· en· W2158807338 on OpenAlexaff
Judy A. Whitaker, Kimberley L. Davis, Chad Lauer

Bibliographic record

VenueJournal of the American Academy of Nurse Practitioners · 2004
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsSeneca Polytechnic
Fundersnot available
KeywordsMedicineType 2 diabetesBody mass indexFamily medicineHealth promotionPopulationFamily historyEthnic groupDiabetes mellitusHealth educationGerontologyPublic healthNursingEnvironmental healthSurgery

Abstract

fetched live from OpenAlex

PURPOSE: To determine if a screening program for type 2 diabetes in a seventh-grade population is warranted as well as to increase health care providers' awareness of the need for this screening. DATA SOURCES: We sent a diabetes questionnaire to each participant's parent or guardian. The questionnaire assessed for any family history of diabetes, any currently diagnosed participant with diabetes, and physical activity. Each participant was also assessed for age, ethnicity, gender, and acanthosis nigricans and received a one-time blood pressure reading. The researchers obtained height and weight by utilizing each school's weight/height scale and calculated each participant's body mass index (BMI). CONCLUSIONS: Overall results determined that there is a need for screening for type 2 diabetes in a seventh-grade population. IMPLICATIONS FOR PRACTICE: The role of the nurse practitioner (NP) is to increase health professionals' and the public's awareness of risk factors related to adolescents and type 2 diabetes by patient education both in areas of health promotion and disease prevention. NP-directed educational programs could include diabetic education in health classes in cooperation with the school nurse and/or health teacher and community-based diabetic forums addressing this topic.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.044
GPT teacher head0.351
Teacher spread0.307 · 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 designOther design
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

Citations9
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Academy of Nurse PractitionersSame topicDiabetes, Cardiovascular Risks, and LipoproteinsFrench-language works237,207