A comparison of stress, coping, empathy, and personality factors among post-graduate students of behavioural science and engineering courses
Notice bibliographique
Résumé
To the editor, A great deal of stress is common among students pursuing professional training in behavioral science and engineering. They often face stress associated with education, interpersonal relationships, workloads, financial difficulties, emotions, physical health, family, academics, jobs, and careers. Stress perception is influenced by personality traits. A person’s perception of stress and their ability to cope with its negative effects are complex processes involving both interpersonal and intrapersonal factors. Stress affects students across all disciplines, but students who employ positive coping mechanisms are more likely to succeed academically.[1-4] Coping and stress are strongly associated with empathy. Empathic self-efficacy is positively correlated with adaptive coping strategies, while it is negatively correlated with maladaptive ones. An empathic person is likely to have better interpersonal skills, as well as a natural tendency to comfort others. Professionals in the mental health field, especially those who provide care, need empathy to understand their clients’ problems and provide effective care.[1-3] In non-clinical professions such as engineering, empathy also comes into play, as it promotes intrapersonal and interpersonal skills, helps in multidisciplinary environments, and helps facilitate healthy relationships between staff, administrators, and other stakeholders. Engineers are more autonomous, independent, dominant, oriented to their jobs, less inclined to social issues, tough-minded, and low in extraversion according to studies of personality characteristics.[4-7] Our study examined the impact of personality characteristics and empathy on stress perception and coping of 80 postgraduate students in mental health and engineering disciplines [MPhil students (Clinical Psychology and Psychiatric Social Work) and MTech students (Engineering Disciplines)]. Measures like the 16 Personality Factor Test, Toronto Empathy Questionnaire, Perceived Stress Scale, and Coping Orientations to Problems Experienced (COPE) were used for data collection.[8-11] In this study, we noted significant differences between the postgraduate students of these two disciplines in three areas of the 16 PF Test, viz., E (Dominance), L (Vigilance), and Q2 (Self-Reliance). Engineering professionals tend to be dominating, autonomy-seeking, and tough-minded.[3,6,7,12] Engineering postgraduates scored significantly higher in all these three areas of 16 PF. We observed “perfectionism” is a strong predictor of stress perception among postgraduate students of behavioral sciences, while, emotional stability is a strong predictor of stress perception among engineering postgraduates [Table 1]. Emotional stability and empathy are predictors of perceived stress in postgraduate students of either discipline. Empathy and emotional stability were both found to be significant predictors of perceived stress. Stress would be perceived differently by students with higher emotional stability and empathy. Empathy is a key component of every profession, including engineering. In the healthcare field, empathy plays a key role, since professionals with high levels of empathy do a better job with their clients.[1-5]Table 1: Personality Factors (scores in 16 PF Personality Factor Test) between the postgraduate students of mental health and the postgraduate students of engineering (n=80)Ethical clearance Ethical approval of this study has been received from the Ethical Committee of the Central Institute of Psychiatry, Ranchi, Jharkhand, India. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».