Dysmenorrhea (pain during menstruation) is one of the most common medical conditions among women of reproductive age. Dysmenorrhea has been studied around the world but not yet in Greece. The aim of the present study was to investigate the prevalence, characteristics, and impact of dysmenorrhea on the wellbeing (exercising, and social and academic functioning) among nursing students in Greece. A cross-sectional study of 637 nursing students was conducted by administering a questionnaire at a university in Athens. The prevalence of dysmenorrhea was 89.2% and the rate of severe intensity was 52.5%. Factors that were associated with severe dysmenorrhea were family history (p = 0.02), early menarche (p = 0.05) and menstruation duration (p = 0.05). Women with moderate and severe pain reported using pain relievers (non-steroidal anti-inflammatory drugs (NSAIDs), paracetamol etc., p < 0.0005). Finally, activities affected by severe pain were class attendance (p = 0.01), personal studying (p < 0.0005), exercising (p < 0.0005), and socializing (p < 0.0005). Exam attendance (p = 0.27) and clinical placement attendance (p = 0.48) were not affected by severe dysmenorrhea. Dysmenorrhea has a high prevalence among nursing students and seems to affect important aspects of wellbeing and academic performance when the pain intensity is severe. The present findings lay the foundation for further investigation of dysmenorrhea both in the Greek population and cross-culturally.

Cardiovascular disease (CVD) is responsible for 18 million annual deaths worldwide. CVD affects patients’ Quality of Life (QoL) mainly in physical, emotional and social dimension. To assess the QoL of patients with CVD in Northern Greece, using three different instruments. The study was conducted in one large hospital located in a major Greek city. A convenience sample of 80 patients participated. A questionnaire including Short Form-36 Health Survey (SF-36), EuroQoL 5-dimensions 5-levels (EQ-5D-5L), MacNew, demographic, and clinical characteristics was used to collect data. The mean age of the patients was 63.31±14.07. Analysis revealed statistically significant main effects of age on the physical limitations, emotional limitations, social functioning, and pain. Also, the analysis showed significant main effects of education on the MacNew Physical, MacNew Social, and the EQ-5D-5L index (p < 0.05). Participants who had graduated primary school had significantly lower quality of life scores than higher education graduates in the MacNew physical (p < 0.02). Furthermore, in the SF-36 pain subscale, the heart failure group had a significantly lower quality of life than the other heart diseases (p = 0.03). Quality of life is affected by factors such as age, type of heart disease, therapy, and comorbidities. Health care providers should be knowledgeable of the factors that affect the quality of life sectors (physical, emotional, and social life) of patients with CVD in order to meet their needs and have the most suitable treatment.

Background: The integration of Artificial Intelligence (AI) technology in cancer care has gained unprecedented global attention over the past few decades. This has impacted the way that cancer care is practiced and delivered across settings. The purpose of this study was to explore the perspectives and experiences of healthcare professionals (HCPs) on cancer treatment and the need for AI. This study is a part of the INCISIVE European Union H2020 project's development of user requirements, which aims to fully explore the potential of AI-based cancer imaging technologies. Methods: A mixed-methods research design was employed. HCPs participating in cancer care in the UK, Greece, Italy, Spain, Cyprus, and Serbia were first surveyed anonymously online. Twenty-seven HCPs then participated in semi-structured interviews. Appropriate statistical method was adopted to report the survey results by using SPSS. The interviews were audio recorded, verbatim transcribed, and then thematically analysed supported by NVIVO. Results: The survey drew responses from 95 HCPs. The occurrence of diagnostic delay was reported by 56% (n = 28/50) for breast cancer, 64% (n = 27/42) for lung cancer, 76% (n = 34/45) for colorectal cancer and 42% (n = 16/38) for prostate cancer. A proportion of participants reported the occurrence of false positives in the accuracy of the current imaging techniques used: 64% (n = 32/50) reported this for breast cancer, 60% (n = 25/42) for lung cancer, 51% (n = 23/45) for colorectal cancer and 45% (n = 17/38) for prostate cancer. All participants agreed that the use of technology would enhance the care pathway for cancer patients. Despite the positive perspectives toward AI, certain limitations were also recorded. The majority (73%) of respondents (n = 69/95) reported they had never utilised technology in the care pathway which necessitates the need for education and training in the qualitative finding; compared to 27% (n = 26/95) who had and were still using it. Most, 89% of respondents (n = 85/95) said they would be opened to providing AI-based services in the future to improve medical imaging for cancer care. Interviews with HCPs revealed lack of widespread preparedness for AI in oncology, several barriers to introducing AI, and a need for education and training. Provision of AI training, increasing public awareness of AI, using evidence-based technology, and developing AI based interventions that will not replace HCPs were some of the recommendations. Conclusion: HCPs reported favourable opinions of AI-based cancer imaging technologies and noted a number of care pathway concerns where AI can be useful. For the future design and execution of the INCISIVE project and other comparable AI-based projects, the characteristics and recommendations offered in the current research can serve as a reference.

Finding new ways to cost-effectively facilitate population screening and improve cancer diagnoses at an early stage supported by data-driven AI models provides unprecedented opportunities to reduce cancer related mortality. This work presents the INCISIVE project initiative towards enhancing AI solutions for health imaging by unifying, harmonizing, and securely sharing scattered cancer-related data to ensure large datasets which are critically needed to develop and evaluate trustworthy AI models. The adopted solutions of the INCISIVE project have been outlined in terms of data collection, harmonization, data sharing, and federated data storage in compliance with legal, ethical, and FAIR principles. Experiences and examples feature breast cancer data integration and mammography collection, indicating the current progress, challenges, and future directions.

The purpose of this study was to examine the relationship between fear of cancer recurrence, spiritual well-being, and mental health among cancer patients. The study involved 217 patients undergoing chemotherapy. Data were collected with the following instruments: a demographic and clinical information recording form, the fear of cancer recurrence inventory, the Athens insomnia scale, the FACIT-Sp-12 scale for the assessment of spirituality, and the HADS scale for the assessment of mental health. For statistical analysis, SPSS statistical software was used, with the significance threshold set at 0.05;andtl number, t-test, one-way ANOVA, and multiple regression tests were used. The sample consisted of 217 cancer patients with a mean age of 63.7 years (SD = 11.6 years), 39.2% male and 60.8% female. The minimum value on the scale of fear of cancer recurrence was 0 and the maximum was 33 points, with a mean value of 14.1 points (SD = 8.2 points). The hospital scale of anxiety and depression was correlated, both in the dimension of anxiety and in the dimension of depression, significantly and positively with the scale of fear of cancer recurrence. Thus, greater fear of recurrence was associated with greater anxiety and depression. On the contrary, the correlations of anxiety and depression with the dimensions and the overall chronic disease treatment rating scale were significant and negative. So, greater spiritual well-being, in each domain and overall, were associated with less anxiety and depression. Finally, less fear of cancer recurrence was associated with finding greater meaning in life, greater peace, and overall greater spiritual well-being. In summary, fear of cancer recurrence is a predictor of psychological distress in cancer patients. However, spirituality can prevent the development of mental illness and FCR.

Purpose: To assess breast cancer patients’ quality of life six months after the completion of adjuvant chemotherapy, and to investigate factors affecting this. Methods: The study was conducted in one large hospital located in a major Greek city. A convenience sample of 61 breast cancer outpatients was recruited. A questionnaire, including the SF-36 scale and questions regarding demographic and clinical information, was used to collect data. Results: The mean age of the patients was 51.52 ± 12.10. The effect of age on the physical role was significant (p = 0.003). Τhe effect of menopausal status on physical role was also found to be significant (p = 0.003); this might be explained by age. Regarding the treatment type, patients who received hormone therapy in addition to surgery and chemotherapy reported a significantly higher quality of life in terms of bodily pain (p = 0.04) and vitality (p = 0.04) than patients who underwent only surgery and chemotherapy. Conclusions: Quality of life is affected by factors such as age, menopausal status, and previous therapy. Health care professionals should be more aware of the factors that influence the quality of life domains (physical role, bodily pain, vitality) within this group of cancer patients in order to meet their needs following acute treatment.