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
Abstract 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 in the college of medicine, King Saud University. 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 male, 19 female) and matched 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 students responded with a response rate of 95.62%. The majority of the students (n = 268, 94.36%, p < 0.001) significantly agreed that the Big Sibling was readily available and have personally benefitted from the relationship with the mentor (big sibling) (n = 256, 90.14%, p < 0.001). The students significantly disagree that the relationship with the Big Sibling requires too much time (n = 206, 72.54%, p < 0.001) and that they do not need a mentor (n = 224, 78.87%, P < 0.001). The majority of the students significantly agreed that mentoring is a good idea (n = 268, 94.37%, p < 0.001), the Big Siblings Program helped reduce their stress (n = 240, 84.51%, p < 0.001), helped to adjust to their new college environment (n = 254, 89.44%, p < 0.001), helped them to advance academically (n = 223, 78.52%, p < 0.001). encouraged them to become involved in college extracurricular activities (n = 165, 58.10%, p < 0.0001), encouraged them to become involved in research activities (n = 123, 43.31%, p < 0.001), encouraged them to become socially engaged with students in my batch at the college of Medicine (n = 203, 71.48%, p < 0.001), encouraged them to become socially engaged with students in elder batches at the college of Medicine (n = 203, 71.48%, p < 0.001). The majority of the students think that the Big Sibling program significantly (p < 0.001) improved their self-confidence (n = 210, 73.94%, p < 0.001), self- awareness (n = 240, 84.51%), accountability and responsibility (n = 240, 54.51%), leadership (n = 156, 54.93%), resilience (n = 202, 71.13%), punctuality (n = 196, 69.01%, p < 0.001), ability to manage time properly (n = 215, 75.70%), ability to cope with stress (n = 221, 77.82%), ability to solve problems (n = 218, 76.76%) and the ability to work in a team (n = 214, 75.35%).Conclusions First year medical students have positive perception of the peer students ‘Big Sibling program’ and its effectiveness in terms of behavior and academic achievements.
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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 | 0,003 | 0,011 |
| 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 | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».