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Record W1975057840 · doi:10.3109/07420528.2013.843541

Are all evening-types doomed? Latent class analyses of perceived morningness–eveningness, sleep and psychosocial functioning among emerging adults

2013· article· en· W1975057840 on OpenAlexaffabout
Royette Tavernier, Teena Willoughby

Bibliographic record

VenueChronobiology International · 2013
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsBrock University
Fundersnot available
KeywordsEveningMorningPsychosocialChronotypePsychologyCircadian rhythmSleep (system call)Latent class modelBedtimeClinical psychologyDevelopmental psychologyMedicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

An overwhelming amount of research has indicated that evening-types report more negative psychosocial functioning as well as more negative sleep characteristics (e.g. more sleep problems) relative to morning-types. Researchers also find a strong, consistent link between poor sleep characteristics and negative psychosocial functioning. These studies, however, have been based on a variable-centred approach, and thus were not able to assess possible individual differences within morning-types and evening-types with respect to their sleep characteristics prior to assessing differences in psychosocial functioning. Thus, it is not clear whether it is morningness-eveningness per se or sleep characteristics that explain the differences in psychosocial functioning found between morning-types and evening-types. The purpose of the present two-year longitudinal study was to employ a person-centred approach to determine whether there are subgroups within morning-types and evening-types based on 10-sleep characteristics (e.g. sleep problems and sleep duration). Then subgroups were compared on three indices of psychosocial functioning (i.e. academics, intrapersonal adjustment and alcohol consumption), both concurrently, as well as one year later. Participants were 780 (72.2% female; M = 19.0 years, SD = 0.90) emerging adults at a mid-sized university in Southern Ontario, who were either morning-types or evening-types. A latent class analysis (LCA) conducted for morning-types yielded two subgroups, classified as having good sleep characteristics (i.e. morning-good) and poor sleep characteristics (i.e. morning-poor). Results of a second LCA conducted for evening-types yielded three subgroups, classified as having good (i.e. evening-good), moderate (i.e. evening-moderate) and poor (i.e. evening-poor) sleep characteristics. Results comparing subgroups across the 10-sleep characteristics indicated that morning-good and evening-good individuals reported very similar scores, and both were characterized by the least sleep problems and longest sleep duration relative to the other subgroups. In terms of the three psychosocial functioning indices we found that academic achievement generally did not differ across the five subgroups (i.e. morning-good, morning-poor, evening-good, evening-moderate and evening-poor). With respect to intrapersonal adjustment, morning-good and evening-good subgroups reported significantly better intrapersonal adjustment relative to the other subgroups across time. Interestingly, evening-type subgroups generally reported higher alcohol consumption than morning-type subgroups. Overall, these results suggest that intrapersonal adjustment in particular appears to be associated more with differences in sleep characteristics (i.e. sleep problems and duration), than with morningness-eveningness per se, while the opposite is generally true for alcohol consumption. Lifestyle and personality factors likely also play a critical role. Importantly, our study is the first to identify a subgroup of evening-types who report good sleep characteristics and similar levels of intrapersonal adjustment and academic achievement to that of the majority of morning-types.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.173
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.310
Teacher spread0.290 · 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 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

Citations65
Published2013
Admission routes2
Has abstractyes

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