razieh chabok

Sleep disorder is common in women with mastectomy. Previous studies have shown that relaxation technique improves sleep quality. However, the effects of these interventions on the sleep quality of breast cancer patients who underwent mastectomy surgery is still unclear. This study aimed to determine the effect of the Benson relaxation technique (BRT) on sleep quality in women with breast cancer after mastectomy.

This randomized clinical trial study was performed on 72 eligible patients who were referred to the screening and chemotherapy center of Shahid Modares Hospital of Kashmar City from April to July 2021. The patients were selected through convenient sampling and randomly allocated to intervention (n = 36) and control (n = 36) groups. In the intervention group, in addition to the routine treatments, BRT was performed once in the morning and once in the evening for 2 months, each time for 20 minutes. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate the score of sleep quality at the beginning of the study and 2 months later. Data were analyzed using the paired t test and independent t test at 95% CI.

The mean score of sleep quality before the intervention in the intervention and control groups was 9.25 ± 2.50 and 8.47 ± 2.13, respectively. After the intervention, the mean score of sleep quality in the intervention and control groups was 6.63 ± 1.92 and 8.41 ± 2.15, respectively, and the difference was significant between the 2 groups (P = 0.001)

The Benson relaxation technique improves sleep quality in women with breast cancer after mastectomy. Therefore, it can be considered an adjunct therapy to improve the sleep quality in these people.

Digital epidemiology is introduced as a major aspect of epidemiology; itssources are digital data and it uses spaces such as Google, YouTube and Twitter as databases.In the recent Covid-19 pandemic, the use of digital epidemiology, as an early warning system,has been considered. This study aimed to investigate the context of Google Trend as an earlywarning system in the study of coronavirus outbreaks in Iran. The coronavirus epidemic in Iran started on February 24, 2020, and with somedifferences to consider the rumors in the community, we consider the date before theannouncement of all by February 16, 2020 until November 16, 2021. We searched usingkeywords related to symptoms such as “fever”, “cough” and “sore throat” and the keyword“corona symptoms”; information was extracted and entered in Microsoft Excel and thekeyword chart was drawn according to the date of each wave. Spearman correlation test wasperformed to find the correlation between keywords in SPSS version 18. The trend chart of the keywords “fever”, “cough” and “sore throat” and the keyword“corona symptoms” in different waves of coronavirus in Iran showed an increase in keywordsearches before the onset of the corona epidemic wave. Spearman correlation coefficientbetween sore throat and fever was 0.645, sore throat and cough 0.775, sore throat and coronasymptoms 0.684, between fever and cough keywords 0.435, fever and corona symptoms 0.779and between keyword cough and corona symptoms 0.503. In all these coefficients, the level oferror of the first type was 0.05 significant (P<0.001) Google Trend, a digital epidemiology tool, can be used as an effective earlywarning system to control the corona pandemic, and this field of epidemiological knowledgewith all its limitations needs further research.