METHODS: A convenience sample of 135 Malaysian women with breast cancer completed questionnaires measuring uncertainty in illness, mood states (i.e. anxiety and depression), quality of life, and copying styles.
RESULTS: The results showed an inverse correlation between uncertainty and quality of life after controlling for the effects of age, cancer stage and time since diagnosis. Moreover, the negative association between illness uncertainty and quality of life was mediated by coping strategies and mood states.
CONCLUSION: The findings revealed that breast cancer patients experiencing a high level of uncertainty more likely use avoidant and less likely use active emotional coping strategies which in turn amplifies anxiety and depression and undermines their quality of life. While some interventions to reduce the adverse consequences of uncertainty are recommended, the findings indicated the need for targeted psychological interventions seeking to gradually shift cancer patients' coping strategies from avoidant to active emotional coping.
METHODS: A descriptive and correlational survey was conducted in a private hospital in Kuala Lumpur, Malaysia. A convenience sample of 118 Malaysian breast cancer patients voluntarily participated in the study and responded to a set of questionnaires including: socio-demographic questionnaire, the short form of Locus of Control Scale, the Functional Assessment of Cancer Therapy-Breast (FACT-B), the Hospital Anxiety and Depression Scale (HADS), and the Short-Form Mishel Uncertainty in Illness Scale (SF-MUIS).
RESULTS: The results revealed that breast cancer patients with higher internal locus of control and lower external locus of control experience a higher quality of life, lower anxiety, and lower depression. Also, uncertainty mediated the relationship between locus of control with quality of life and depression (quasi-significant).
CONCLUSIONS: The findings indicated the need for early, targeted psychological interventions seeking to gradually shift cancer patients' locus of control from external to internal in order to improve their quality of life and reduce their depression and anxiety. Moreover, health care providers by providing relevant information to cancer patients, especially for externally oriented patients, can reduce their uncertainty which in turn would improve their quality of life.
METHODS: In this cross-sectional study, 504 Iranian older adult participants from Qazvin province were recruited between December 2015 and April 2016. They completed a questionnaire that included the Revised Adult Attachment Scale, the Life Satisfaction Index-Z, and the Herth Hope Index.
RESULTS: Participants in the study had a mean age of 66.20 years (SD: 5.76) and most of them were women (57.5%). A mediation model testing the direct relationships between attachment, hope, religiosity, and life satisfaction showed a positive relationship between close attachment and religiosity (β = .226, p
Methods: A cross-sectional study was conducted on nurses (n= 400) at public and private Mazandaran hospitals. An online questionnaire was used that consisted of two parts: demographic variables and NICS. The scale was translated into Persian first and then validated using both construct and content validity.
Results: The findings from an exploratory factor analysis yielded six factors that explained 53.12% of the total variance of the NICS. The confirmatory factor analysis demonstrated that the model had a good fit and the inter-item correlation values of the factors indicated good internal consistency.
Conclusion: The Persian version of NICS in Iranian nurses had six factors. The results of our study add insight for nurse administrators and educators to further develop strategies to increase nurses' intention by improving positive attitudes and reducing their negative beliefs.
Methods: This retrospective prevalence study was based on medical records of the heart center of Mazandaran Province on all patients diagnosed with AMI in Mazandaran, northern Iran between 2013 and 2015. Patients' sex and the day, month, year and time of hospital admission were extracted from patients' records. Moreover, the meteorological reports were gathered.
Results: A statistically significant difference was found between the distributions of AMI cases across 12 months of the year (P < 0.01). Fuzzy clustering analysis using 16 different climatic variables showed that March, April, and May were in the same cluster together. The other 9 months were in different clusters.
Conclusion: Significant increase in AMI was seen in March, April and May (cold to hot weather).