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Record W2988462079 · doi:10.2196/14535

Screening University Students for Health Checks With an Electronic Health Questionnaire in Finland: Protocol for a Retrospective, Register-Based Cohort Study

2019· article· en· W2988462079 on OpenAlexvenueno aff
Susanna Paldanius, Noora Seilo, Kristina Kunttu, Reija Autio, Minna Kaila

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Retrospective cohort studyMedicineCohortElectronic health recordCohort studyMedical educationFamily medicineHealth careAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Health questionnaires and health checks are an established part of preventive health care services in Finland. However, only very limited research of these has been conducted. The Finnish Student Health Service (FSHS) provides primary health care services to all bachelor's and master's degree university students (approximately 134,500 students) in Finland. FSHS's statutory health examination process of university entrants includes an electronic health questionnaire (eHQ) and, based on the students' eHQ responses, a subsequent health check if necessary. To our knowledge, no previous studies have been published on the use of questionnaires for screening students for general health checks. OBJECTIVE: The general aim of the study is to evaluate the health examination process of university entrants. The objectives are to determine how students' self-reported health in the eHQ and participation in the health examination process are associated with graduation, mental health problems, and the use of student health care services. METHODS: This is an ongoing, nationwide, retrospective, register-based cohort study with a 6-year follow-up. The study population is the cohort of university entrants (N=15,723) from the 2011-2012 academic year. These students were sent the eHQ, which consisted of 26 questions about health, health habits, social relations, and studying. Based on the eHQ responses, students were referred to one of the following interventions: (1) a health check, (2) an appointment other than a health check (eg, physiotherapy), or (3) electronic feedback to support a healthy lifestyle, when the other interventions were not necessary. Multiple comparisons will be made within these groups using logistic regression. The primary outcome variables are graduation, having a mental health problem, and attending a health check. The use of FSHS health care services will be studied with the cluster analysis method. The data have been obtained from three nationwide registers: the eHQ register, the medical records of FSHS, and the Higher education achievement register. The data have been linked using personal identity codes. RESULTS: As of August 2019, the data collection and processing are complete and the statistical analyses are in progress. Preliminary results are expected in autumn 2019. Further publications are expected in 2020, and two PhD theses are expected to be completed by the end of 2022. CONCLUSIONS: Studying practical procedures in primary health care is highly important for resource allocation and the development of evidence-based processes. This study will be the first to assess the usage of a health questionnaire in screening students for health checks. The findings of this study will contribute to the field of preventive health care. The main practical implication is the development of the FSHS's health examination process. We hypothesize that participation in the health examination process enhances academic achievement and the detection of university students' mental health problems early on in their studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14535.

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)0.020
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.138
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.144
GPT teacher head0.563
Teacher spread0.418 · 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
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

Citations6
Published2019
Admission routes1
Has abstractyes

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