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Record W4405098755 · doi:10.22215/etd/2024-16193

Understanding the Association Between Offline Psychological Need Satisfaction and Social Media Related Bedtime Procrastination

2024· dissertation· en· W4405098755 on OpenAlexafffund
Ryan Matthew Soltendieck

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsCarleton University
FundersCarleton University
KeywordsProcrastinationBedtimePsychologySocial mediaAssociation (psychology)Social psychologyOnline and offlinePerception

Abstract

fetched live from OpenAlex

Do the basic psychological needs for autonomy, competence and relatedness play a role in university students procrastinating their bedtime to use social media?This study examined whether lower offline psychological need satisfaction was related to more social media related bedtime procrastination amongst university students, and whether this negative association was stronger for students who perceived that their nighttime social media use satisfied their basic psychological needs.University students (N = 644, Mage = 19.8,Female = 69.7%)completed several online self-report measures at one time point.After adjusting for several covariates, offline psychological need satisfaction was not associated with social media related bedtime procrastination (β = -.00,p = .99),and this association did not depend on nighttime social media psychological need satisfaction (β = -.02,p = .66).Offline psychological needs satisfaction was also not indirectly related to subjective sleep quality via social media related bedtime procrastination (b = .00,95% CI[-.01, .01]).These findings suggest that perceptions of basic psychological need satisfaction both offline and through nighttime social media use are not related to social media related bedtime procrastination amongst university students.

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)0.006
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.075
GPT teacher head0.349
Teacher spread0.273 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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Same topicPerfectionism, Procrastination, Anxiety StudiesFrench-language works237,207