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Record W3034871043 · doi:10.3389/fpsyg.2020.01255

State and Trait Anxiety Among University Students: A Moderated Mediation Model of Negative Affectivity, Alexithymia, and Housing Conditions

2020· article· en· W3034871043 on OpenAlexaboutno aff
Isabella Giulia Franzoi, Maria Domenica Sauta, Antonella Granieri

Bibliographic record

VenueFrontiers in Psychology · 2020
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
FundersFondazione CRT
KeywordsNegative affectivityPsychologyAlexithymiaAnxietyClinical psychologyDistressPersonalityModerationBeck Depression InventoryPopulationToronto Alexithymia ScalePsychiatrySocial psychologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Starting university education is a crucial period for the mental health of students, who report higher levels of distress compared to the general population. This study sought to better understand the distress experienced by students by considering contextual facets (e.g., housing conditions) as well as stable clinical variables (e.g., negative affectivity, emotion regulation, and anxiety). METHODS: A total of 177 University students (71.2% females) aged 18-29 were administered the State-Trait Anxiety Inventory-Y, the Beck Depression Inventory-II, the Suicidal History Self-Rating Screening Scale, the Personality Inventory for DSM-5-Brief Form, and the Toronto Alexithymia Scale-20. RESULTS: University students showed concerning levels of distress, particularly concerning anxiety, and depression. We found that the relationship between negative affectivity and both state and trait anxiety was mediated by alexithymia but housing conditions did not act as a moderator for the indirect effect of negative affectivity on state or trait anxiety through alexithymia. CONCLUSION: Undoubtedly, university lifestyle can be demanding, but experiencing distress is not inevitable nor inexplicable. The present study sought to gain insight into the anxiety experienced by Italian University students while taking into account the importance of personality and clinical characteristics that have previously been widely underestimated. We found that these characteristics can be of extreme importance for developing preventative and therapeutic interventions tailored to the clinical characteristics of students, as well taking into account their living environment.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.449

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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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

Citations44
Published2020
Admission routes1
Has abstractyes

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