The effect of computer-based Stress Inoculation Training (SIT) approach on the pelvic pain, depression, and anxiety in students with primary dysmenorrhea: a clinical trial study
Notice bibliographique
Résumé
BACKGROUND: Primary dysmenorrhea (PD) is one of the most common pains experienced by women. Stress Inoculation Training (SIT) is a cognitive-behavioral technique that immunizes them against future periods of stress. The purpose of this research is to investigate the effectiveness of a computer-based stress inoculation approach on pelvic pain, depression, and anxiety symptoms in students with PD. METHODS: The present study is a clinical trial conducted on 100 students with PD. The SIT intervention consisted of eight consecutive sessions. The content of the sessions was created as multimedia on a computer platform of a site. In each session, several interactive questions were asked about the topics of that session, and participants answered them, with responses recorded in the system. Then, each individual session, lasting about 50 min, was sent as a link (offline) to a participant. Data collection tools included the demographics Checklist, McGill Pain Questionnaire (MPQ), Moos Menstrual Distress Questionnaire (MMDQ), Hospital Anxiety and Depression Scale (HADS), Pain Self-Efficacy Questionnaire (PSEQ), and Perceived Stress Scale (PSS-14), which were completed on the second menstrual day of the cycle before the study and for three consecutive cycles after the intervention by each student. The data were analyzed using chi-square, generalized linear mixed models (GLMM), and multiple linear regression tests. The significance level was set at P < 0.05. RESULTS: The results of the GLMM test showed that the SIT intervention decreased depression (p = 0.002), anxiety (p = 0.001), menstrual distress (p = 0.001), pain intensity (p = 0.003), and perceived stress (p = 0.002), while it increased pain self-efficacy (p = 0.001). Based on multiple linear regression analysis, the main predictors of depression were the student's age and residence in a dormitory (β=-0.255, p = 0.047 and β=-0.376, p = 0.005, respectively). The factors influencing pain self-efficacy were birth rank and the type of university admission (β=-0.351, p = 0.027 and β=-0.249, p = 0.030, respectively). In the presence of confounding variables, increasing age and living in a dormitory were risk factors that increased depression, while studying with tuition fees and a higher birth rank were associated with decreased self-efficacy. CONCLUSION: The computer-based SIT was effective in reducing pelvic pain, and psychological factors, and in increasing pain self-efficacy in students with primary dysmenorrhea. Therefore, it can be used as a useful solution to manage complications associated with primary dysmenorrhea. TRIAL REGISTRATION: IRCT20230130057274N5 Date of registration: 2024-04-29 Retrospectively registered.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».