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Record W2971197223 · doi:10.1136/bmjopen-2019-029854

U-Flourish university students well-being and academic success longitudinal study: a study protocol

2019· article· en· W2971197223 on OpenAlexafffundabout
Sarah Goodday, Daniel Rivera, Nathan King, Melissa Milanovic, Charles Keown‐Stoneman, Julie Horrocks, Elizabeth Tetzlaff, Christopher R. Bowie, William Pickett, Kate L. Harkness, Kate Saunders, Simone Cunningham, Steven H. McNevin, Anne Duffy

Bibliographic record

VenueBMJ Open · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of OttawaPublic Health OntarioUniversity of TorontoQueen's University
FundersCanadian Institutes of Health ResearchQueen's UniversityUniversity of Oxford
KeywordsMental healthMedicineIntervention (counseling)PopulationGerontologyLongitudinal studyMedical educationFamily medicineNursingEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Over 30% of Canadians between the ages of 16 and 24 years attend university. This period of life coincides with the onset of common mental illnesses. Yet, data to inform university-based mental health prevention and early intervention initiatives are limited. The U-Flourish longitudinal study based out of Queen's University, Canada and involving Oxford University in the UK, is a student informed study funded by the Canadian Institute for Health Research Strategy for Patient Oriented Research (CIHR-SPOR). The primary goal of U-Flourish research is to examine the contribution of risk and resiliency factors to outcomes of well-being and academic success in first year students transitioning to university. METHODS AND ANALYSIS: The study is a longitudinal survey of all first-year undergraduate students entering Queen's University in the fall term of 2018 (and will launch at Oxford University in fall of 2019). In accordance with the CIHR-SPOR definitions, students represent the target population (ie, patient equivalent). Student peer health educators were recruited to inform the design, content and implementation of the study. Baseline surveys of Queen's first year students were completed in the fall of 2018, and follow-up surveys at the end of first year in the spring of 2019. Extensive student-led engagement campaigns were used to maximise participation rates. The baseline survey included measures of personal factors, family factors, environmental factors, psychological and emotional health, and lifestyle factors. Main outcomes include self-reported indicators of mental health at follow-up and mental health service access, as well as objective measures of academic success through linkage to university administrative and academic databases. A combination of mixed effects regression techniques will be employed to determine associations between baseline predictive factors and mental health and academic outcomes. ETHICS AND DISSEMINATION: Ethical approval was obtained by the Health Sciences and Affiliated Teaching Hospitals Research Ethics Board (HSREB) (#6023126) at Queen's University. Findings will be disseminated through international and national peer-reviewed scientific articles and other channels including student-driven support and advocacy groups, newsletters and social media.

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)0.035
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.045
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.017
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.004
Science and technology studies0.0090.003
Scholarly communication0.0050.004
Open science0.0050.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0450.015

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 head0.158
GPT teacher head0.566
Teacher spread0.408 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations43
Published2019
Admission routes3
Has abstractyes

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