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Record W2036892894 · doi:10.1080/10640260701190709

Targeting Students, Teachers and Parents in a Wellness-Based Prevention Program in Schools

2007· article· en· W2036892894 on OpenAlexaff
Shelly Russell‐Mayhew, Nancy Arthur, Carol Ewashen

Bibliographic record

VenueEating Disorders · 2007
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyIntervention (counseling)Control (management)Clinical psychologyMedical educationDevelopmental psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

This study examines the effectiveness of a wellness-based prevention program on elementary and junior high students' body image, personal attitudes, and eating behaviors. Group differences in measures of student attitudes and eating behaviors are examined to determine the effect of targeting different participant combinations (students, parents, and teachers) in 10 groups. For elementary schools, student participants consisted of control (no intervention) (n = 36), student only (n = 81), student/parent (n = 124), student/parent/teacher (n = 103), and parent/teacher (n = 149). For junior high schools, student participants consisted of control (n = 143), student only (n=215), student/parent (n=65), student/parent/teacher (n = 14), and parent/teacher (n = 177). Overall, complete data was available for 1,095 students, 114 parents and 92 teachers. Results indicate that self-concept and eating attitudes and behaviors were positively affected by participation in the program. For example, in elementary schools posttest scores on the behavior subscale of the self-concept measure are significantly higher for the student/parent/teacher group than for the control group. Results indicate that a one-time wellness-based eating disorder prevention program with students, which have in the past shown to be minimally effective, may be more effective in changing attitudes and behaviors when teachers and parents are involved.

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)0.000
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 score0.165
Threshold uncertainty score0.912

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.367
Teacher spread0.352 · 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

Citations28
Published2007
Admission routes1
Has abstractyes

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