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Record W2086185876 · doi:10.5539/ijps.v6n2p107

Food Intake Behavior and Chronotype of Japanese Nurses Working Irregular Shifts

2014· article· en· W2086185876 on OpenAlexvenueno aff
Shunsuke Nagashima, Eiko Masutani, Tomoko Wakamura

Bibliographic record

VenueInternational Journal of Psychological Studies · 2014
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsnot available
FundersLiverpool John Moores University
KeywordsChronotypeSnackingMorningMealPsychologyPreferenceFood intakeTruancyDemographicsSupperNight workDemographyShift workDevelopmental psychologyCircadian rhythmMedicineObesityPsychiatryGeography

Abstract

fetched live from OpenAlex

Shift work is the popular working pattern in many fields in industrialized nations. However, the shift workerdoes not pay much attention to his (her) own health. It is known that shift work has strong associations withvarious diseases. The aim of this study was to investigate the relationship between food intake and chronotype inJapanese nurses working an irregular rotation of shifts. This questionnaire-based study used a cross-sectionaldesign. Participants were nurses working in several hospitals, data from 159 respondents being analyzed. Thequestionnaire covered demographics, the Diurnal Type Scale (DTS) and a Food Intake Questionnaire (FIQ). TheDTS scores were classified into three chronotype groups: modified Morning-type (M-type), modifiedEvening-type (E-type) and modified Intermediate-type (I-type). For food intake behavior, meal habits of theM-types were compared with the E-types before / after day- and night-work. In the morning, just after thenight-shift, the M-types chose cold food more frequently (p = .016) and felt less satiated after the meal (p = .016)than the E-types. Furthermore, the E-types chose significantly larger meals (p = .023) than the M-types, theM-types snacking more frequently. Chronotype was associated with the food intake behavior both in day- andnight-shift. These results suggest that the Morning-type person suffered more inconvenience with regard to foodintake behavior during night-work.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.079
GPT teacher head0.398
Teacher spread0.319 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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