Notice bibliographique
Résumé
Aim: Investigate the role of mobile phones in use by the international LUHS students Objectives: 1) Determine the most common practices and habits of mobile phones usage among international students, 2) Investigate consequences and possible effects of habits through comparison of results to literature of previous studies performed determining mobile phone use and well-being, 3) Determine possible consequences and effects of current habits of mobiles phone use among international students. Materials and methods: Cross-sectional study was performed at the Lithuanian University of Health Sciences during the first quarter of 2022. Total population of international students present in LUHS consists of 1300 full-time students; sample size reached 52 student participants. Research was done applying Smartphone addiction scale, shortened version, and a previously tested form for determination of mobile phone use. The form was presented to participants as an online link that directed them to the documents which they completed anonymously. Consent was taken from each student prior to participation; data of student responses were further analyzed with descriptive statistical analysis, exploratory analysis and inferential analysis. Results: Out of the 10 SAS-SV questions answered by students, the mean points of each question totaled (p0.95)3.668∓ 0.159, with a standard deviation of 0.415 reflecting an answer leaning towards students slightly agreeing with the statements. Students seem to admit to exhibiting behaviours of hazardous phone use, even by their standards and judgement. The most common time of mobile phone use appears to be in the evening, where 83% of participants reported to mobile phone use at this time. The average LUHS student spends about 5 hours a day on their phone. When counting students' most preferred uses for mobile phones, we find that students report internet use as their most common reason for use, followed by messaging and listening to music. Conclusion: Students of LUHS appear to, on average, use their phones for at least 4 hours a day, peaking highest during the evening, for predominantly internet use, followed by listening to music and text messaging, with academic purposes being the last on the list. The consequences of increasing mobile phone use appear to be linked to dysfunction of daily activities by interfering with sleep as well as academic responsibilities, either causing or magnifying the stress experienced by students leading to lowered reported general well-being. Participants of LUHS reported being more likely to indulge in hazardous phone use than not, indicating that effects of sleep disturbance, daytime disturbance and reduced reported well-being may be prevalent among students of this institution.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».