Students’ Perception of Peer- Students Mentoring Program “Big Sibling Mentoring Program” to Complement Faculty Mentoring of First-Year Medical Students in Saudi Arabia
Notice bibliographique
Résumé
Background: The Big Sibling Program is an innovative peer student mentoring method that was designed and implemented by the students' council in 2021 to complement the faculty mentoring program of first-year medical students in the College of Medicine, King Saud University, Saudi Arabia. The aim of the study was to evaluate the medical students' perception of the peer students "Big Sibling" mentoring program and to assess the effectiveness of the program in terms of changes in the behavior and academic performance of the students. Methods: This is a retrospective study that was conducted in 2021. A registration form that includes demographic data, personal information, and academic performance (GPA and extracurricular achievements) was sent to all second- and third-year medical students to select the Big Siblings. A total of 49 mentors "Big Siblings" were accepted (30 males, 19 females) and matched randomly with the little siblings from first-year medical students. A written consent was obtained from the participants. The survey was structured on a 5-point Likert scale, and composed of four sections of closed-ended questions, that includes: the demographic data, the students' (little sibling) evaluation of the mentorship sessions, the little sibling perception of the Big Sibling Program and its effectiveness of the Big Sibling Program in terms of behavioral or quality effects. Results: Out of 297 first-year medical students, 284 (95.62%) responded. The majority significantly agreed that the Big Sibling was readily available and they personally benefitted from the relationship (94.36%, p<0.001; 90.14%, p<0.001). They significantly disagreed that the relationship requires too much time (72.54%, p<0.001) or that they do not need a mentor (78.87%, p<0.001). Most significantly agreed that mentoring is a good idea (94.37%, p<0.001), the program helped reduce their stress (84.51%, p<0.001), helped them adjust to college (89.44%, p<0.001), and advance academically (78.52%, p<0.001). The program also encouraged their involvement in extracurricular activities (58.10%, p<0.0001), research (43.31%, p<0.001), and social engagement with peers (71.48%, p<0.001). Moreover, the majority thought the program significantly improved their self-confidence (73.94%, p<0.001), self-awareness (84.51%), accountability (54.51%), leadership (54.93%), resilience (71.13%), punctuality (69.01%, p<0.001), time management (75.70%), stress coping (77.82%), problem-solving (76.76%), and teamwork (75.35%). Conclusion: Peer students' big Siblings program has succeeded in reducing first-year medical students stress levels, improving their self-confidence, self-awareness, accountability and responsibility, leadership, resilience, punctuality and engaging them in research and extracurricular activities.
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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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».