Sleep quality, physical and psychological outcomes in nurses with low backpain from a tertiary hospital, South India
Notice bibliographique
Résumé
Introduction: Low back pain (LBP) affects 80% of the population globally. In India, prevalence of LBP among nurses is reported to be 66%. Methodology: A descriptive cross-sectional study design was adopted to assess the sleep quality of nurses with low back pain in a tertiary care setting, South India and to determine the relationship of sleep quality with the physical and psychological parameters such as pain intensity, functional disability, anxiety, and depression. All the nurses willing to participate in the study, and available during the data collection period were screened for LBP. Among the nurses with LBP, 193 subjects were selected using systematic random sampling technique. Study was approved by the Institutional Review Board and informed written consent was obtained from the subjects. Subjects were asked to complete the following questionnaires: Pittsburgh Sleep Quality Index (PSQI), Short-form McGill Pain Questionnaire (SFMP), Oswestry Low Back Pain Disability Questionnaire (ODI), Zung Self-rating Anxiety (ZSA) and Depression (ZSD) scales. Results: Among 1284 nurses screened, 686 (53.4%) had LBP. Of the 193 nurses included in the study 68.4% of the nurses had good quality of sleep. Majority of the subjects had minimal disability (68.4%), moderate pain (81.3%), and normal anxiety (56.3%) and depression (91.7%) levels. There was a significant positive correlation between sleep quality and pain intensity (r=.355, p<.01), disability (r=.376, p<.01), anxiety (r=.297, p<.01), and depression (r=.233, p<.001). Conclusion: Improving sleep quality will decrease the physical and psychological manifestations of patients with low back pain and hence improve the quality of life of nurses with LBP. Biography: Nirmala M Emmanuel has completed her MSc Nursing at the age of 30 years from Christian Medical College (CMC), Vellore affiliated to Tamilnadu Dr. MGR Medical University. She is working as a Nurse Manager in the Surgical Nursing department of CMC, which is a multispeciality hospital with nearly 2500 beds. She also serves as a Professor at the College of Nursing, CMC, Vellore. Nursing is an integrated system of education and practice in the institution. Speaker Publications: 1. Cunningham C, Flynn T, Blake C. Low back pain and occupation among Irish health workers. Occup Med. 2006;56(7):23–28. 2. Mafuyai MY, Babangida BG, Mador ES, Bakwa DD, Jabil YY. The increasing cases of lower back pain in developed Nations: a reciprocal effect of development. AJIS. 2014;3(5):23–28. 3. Golob A, Wipf J. Low Back Pain. Med Clin North Am. 2014;98(3):405–428. 4. Lidgren L. The bone and joint decade 2000–2010. Bulletin of the World Health Organization. 2003;81(9):629. 5. CDC, author. Preventing back injuries in health care settings. Atlanta, USA: Centers for Disease Control and Prevention; 2008. 5th World Congress on Public Health and Nutrition; London, UK- February 24-25, 2020. Abstract Citation: Nirmala M Emmanuel, Sleep quality, physical and psychological outcomes in nurses with low back pain from a tertiary hospital, South India, Public Health 2020, 5th World Congress on Public Health and Nutrition; London, UKFebruary 24-25, 2020 (https://publichealth.healthconferences.org/abstract/2020/sleepquality- physical-and-psychological-outcomes-in-nurses-withlow- back-pain-from-a-tertiary-hospital-south-india)
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 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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».