Determinants of tourism for “Sun and Sea” Cyprus

Tourism is an essential contributor of economic growth, social and cultural development. Cyprus is now an established tourist destination, which, however, is passing through a slowdown phase. The determinants of tourism have been extensively examined for other countries, but the literature regarding Cyprus is very scarce. This paper examines the factors that affect tourism in Cyprus for the period 1995-2010, using time series regression analysis. Tourism is represented by tourist arrivals and tourism expenditure, while the predictors are relative prices, the Gross Domestic Product (GDP) of Cyprus and the income of the main countries that send tourists to Cyprus. The results show that tourism expenditure is significantly affected by the GDP of Cyprus and the relative prices between Cyprus and its main competitor, Greece, while tourist arrivals are additionally affected by the level of income of the origin countries. Increased competition, high operational costs, standardization of touristic product (sun and sea), as well as the international political instability and global financial crisis, which have raised unemployment and reduced tourists’ disposable income, appear to influence tourism in Cyprus. These findings are discussed, in combination with the corresponding low or high rankings of Cyprus in various pillars of travel and tourism competitiveness.peer-reviewe

The Inclusion of Labor Market Conditions in a Proposed Modeling Framework for Fresh Graduates’ Retention

Fresh graduates are often described as young generations with high productivity potentials but with fewer chances to enter the labor market. After graduation, they frequently find themselves in a complexity of work integration. Employers have expectations from them and they also have their own ambitions that are usually considered as high. Being the promise for a better tomorrow to any labor market, it matters for nations as well as organizations to retain these young generations. Nowadays, retaining fresh graduates has turned to be a great challenge especially that labor market conditions have become very tough and hard hit by economic crises, low wages and unequal labor rights. Although many scholars and practitioners emphasize the importance of retaining fresh graduates in challenging labor markets, research related to the links among fresh graduates, labor market conditions and retention has failed to keep up. Given the importance of this issue, this study seeks to review the existing literature on labor market conditions affecting fresh graduates’ retention and job satisfaction, identify and address the related research gaps and develop an integrated model highlighting how fresh graduates’ retention can be affected by various practices, conditions and psychological states

Linking patient satisfaction with nursing care: the case of care rationing -a correlational study

Abstract Background: Implicit rationing of nursing care is the withholding of or failure to carry out all necessary nursing measures due to lack of resources. There is evidence supporting a link between rationing of nursing care, nurses' perceptions of their professional environment, negative patient outcomes, and placing patient safety at risk. The aims of the study were: a) To explore whether patient satisfaction is linked to nurse-reported rationing of nursing care and to nurses' perceptions of their practice environment while adjusting for patient and nurse characteristics. b) To identify the threshold score of rationing by comparing the level of patient satisfaction factors across rationing levels

Heat-related mortality in Cyprus for current and future climate scenarios

Extreme temperatures have long been associated with adverse health impacts, ranging from minor illness, to increased hospitalizations and mortality. Heat-related mortality during summer months is likely to become an increasing public health problem in future due to the effects of climate change. We performed a health impact assessment for heat-related mortality for the warm months of April–September for the years 2004 to 2009 inclusive, for the city of Nicosia and for Cyprus as a whole, based on separately derived exposure-response functions. We further estimated the potential future heat-related mortality by including climate projections for southern Europe, which suggest changes in temperature of between 1 °C and 5 °C over the next century. There were 32 heat-related deaths per year in Cyprus over the study period. When adding the projected increase in temperature due to climate change, there was a substantial increase in mortality: for a 1 °C increase in temperature, heat related mortality in Cyprus was estimated to double to 64 per year, and for a 5 °C increase, heat-related mortality was expected to be 8 times the baseline rate for the warm season (281 compared with 32). This analysis highlights the importance of preparing for potential health impacts due to heat in Cyprus, particularly under a changing climate.</p

An Alternative Methodology for Combining Different Forecasting Models

Many economic and financial time series exhibit heteroskedasticity, where the variability changes are often based on recent past shocks, which cause large or small fluctuations to cluster together. Classical ways of modelling the changing variance include the use of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models and Neural Networks models. The paper starts with a comparative study of these two models, both in terms of capturing the non-linear or heteroskedastic structure and forecasting performance. Monthly and daily exchange rates for three different countries are implemented. The paper continues with different methods for combining forecasts of the volatility from the competing models, in order to improve forecasting accuracy. Traditional methods for combining the predicted values from different models, using various weighting schemes are considered, such as the simple average or methods that find the best weights in terms of minimizing the squared forecast error. The main purpose of the paper is, however, to propose an alternative methodology for combining forecasts effectively. The new, hereby-proposed non-linear, non-parametric, kernel-based method, is shown to have the basic advantage of not being affected by outliers, structural breaks or shocks to the system and it does not require a specific functional form for the combination.GARCH models, neural networks, heteroskedasticity, combination methods, non-parametric methods, kernel regression, forecasting criteria,

Exploring the other side of cancer care : the informal caregiver

Objectives: To identify the caregiver outcomes among relatives caring for patients with cancer and to examine the patient and family caregiver variables that predicted for caregiver burden and depression. Methods: One hundred and thirty caregivers completed the Greek versions of the Burden Interview (BI), the Center of Epidemiology – Depression Scale (CES-D) and the Ways of Coping Questionnaire. Principal component analysis was performed to examine the underlying dimensions of caregiver outcome measures. One-way ANOVA and independent sample t-tests were used to test for differences in burden and depression in relation to demographic variables of interest. One-way ANOVA was used for examining differences in coping strategies. Findings: One-way ANOVA showed that there are significant differences among the various educational levels (p < 0.001) and the income (p < 0.005) of the caregiver in terms of overall burden. 66.4% of caregivers had a depression above the usual cutoff point for depression. An independent samples t-test for possible gender differences, showed that there is a significant difference between males and females (p ¼ 0.29). In regression analysis it was found that only caregiver’s income and patient’s age are statistically significant in predicting burden and depression. When considering high-burdened caregivers results showed that there are significant differences in the use of coping strategies (p < 0.001). Conclusions: Caregivers reported high levels of burden and depression. These outcomes of caregiving are related to several variables, but the caregiver’s income and patient’s age are predictive. Intervention strategies are needed to the vulnerable caregivers to help reduce burden and depression associated with caregiving

Psychometric Testing of the Greek Version of the Clinical Learning Environment-Teacher (CLES+T)

Clinical practice is an important part of nursing education, and robust instruments are required to evaluate the effectiveness of the hospital setting as a learning environment. The study aim is the psychometric test of the Clinical Learning Environment+Teacher (CLES+T) scale-Greek version.: 463 students practicing in acute care hospitals participated in the study. The reliability of the instrument was estimated with Cronbach’s alpha coefficients. The construct validity was evaluated using exploratory factor analysis (EFA) with Varimax rotation. Convergent validity was examined by measuring the bivariate correlations between the scale/subscales. Content, validity and semantic equivalence were examined through reviews by a panel of experts. The total scale showed high internal consistency (α=0.95). EFA was identical to the original scale, had eigen values larger than one and explained a total of 67.4% of the variance. The factor with the highest eigen value and the largest percentage of variance explained was “supervisory relationship”, with an original eigenvalue of 13.1 (6.8 after Varimax rotation) and an explanation of around 38% of the variance (or 20% after rotation). Convergent validity was examined by measuring the bivariate correlations between the scale and a question that measured the general satisfaction. The Greek version of the CLES+T is a valid and reliable instrument that can be used to examine students’ perceptions of the clinical learning environment

Assessment of the Effect of Erenumab on Efficacy and Quality-of-Life Parameters in a Cohort of Migraine Patients With Treatment Failure in Cyprus

&lt;jats:p&gt;Erenumab is the first human monoclonal antibody to be approved as a selective therapy for migraine prophylaxis in adults. This study assessed, in a real-world setting, the efficacy of erenumab and its impact on the quality of life (QoL) of Cypriot migraine patients who had failed several treatments in the past. Erenumab was prescribed as a stand-alone or as an add-on therapy to 16 patients with chronic migraine. The first component of the study examined migraine parameters before and after erenumab therapy and included an interim 3-month subjective assessment. In the second component, the patients were asked to complete the validated Migraine-Specific Quality-of-Life Questionnaire—Version 2.1 (MSQ V2.1) during the last month of their individual treatment as a measure of the QoL. The results showed a statistically significant improvement in almost all migraine parameters following erenumab treatment. In the 3-month-interval assessment, 81.3% of the patients reported an improvement in their mental well-being, anxiety, and depression levels, with more than 80% of the patients reporting an improvement in almost all assessed migraine parameters. MSQ V2.1 indicated a good health status in all three domains (mean values &amp;amp;gt; 60 on a scale 0–100), with the “role function preventative” domain having the highest health scores (85). Over a period of 6 months, erenumab was safe, well-tolerated, and effective in preventing migraine symptoms and improving HR-QoL. We conclude that this novel medication, which is not yet part of the national formulary in Cyprus, may be a cost-effective solution in reducing the disease burden of chronic migraine.&lt;/jats:p&gt

Nonparametric ANCOVA with two and three covariates

Fully nonparametric analysis of covariance with two and three covariates is considered. The approach is based on an extension of the model of Akritas et al. (Biometrika 87(3) (2000) 507). The model allows for possibly nonlinear covariate effect which can have different shape in different factor level combinations. All types of ordinal data are included in the formulation. In particular, the response distributions are not restricted to comply to any parametric or semiparametric model. In this nonparametric model, hypotheses of no main effect no interaction and no simple effect, which adjust for the covariate values, are defined through a decomposition of the conditional distribution functions of the response given to the factor level combination and covariate values. The test statistics are based on averages over the covariate values of certain Nadaraya-Watson regression quantities. Under their respective null hypotheses, such test statistics are shown to have a central [chi]2 distribution. Small sample corrections are also provided. Simulation results and the analysis of two real datasets are also presented.Nonparametric hypotheses Nonparametric regression Ties Ordinal response Ordinal covariates ANCOVA Logistic regression Rank tests

The Burdensome and Depressive Experience of Caring: What Cancer, Schizophrenia, and Alzheimer’s Disease Caregivers Have in Common

Background: Family members of patients with chronic illnesses experience distress as a result of caregiving roles, which can be manifested as burden and depression, but cross-disease studies on how caring is experienced are limited. Objective: The present study was designed to examine the burden and psychiatric morbidity in the form of depression experienced by Cypriot families caring for a relative with one of the following: cancer, Alzheimer’s disease, or schizophrenia. Methods: This study was cross-sectional, descriptive, and correlational. A total of 410 caregivers were recruited from the community. The research instruments included the Greek version of the Burden Interview and the Center of Epidemiological Studies–Depression Scale. Descriptive statistics, 1-way analysis of variance, and post hoc Tukey pairwise comparisons were used to examine significant differences between the 3 groups. Results: The results indicate a high level of burden and depression among all caregivers. Significant differences (P < .001, F = 26.11) between the 3 caregiving groups were detected in terms of burden, with the highest reported for Alzheimer’s disease caregivers. One-way analysis of variance showed significant differences (P = .008, F = 4.85) between the 3 caregiving groups in terms of depression, with the highest depression levels being for cancer caregivers. Conclusions: The findings increase our understanding about burden and emotional well-being in family caring for relatives with cancer and other chronic illnesses. Implications for Practice: The findings may be useful for health professionals to plan intervention strategies focusing on each domain of burden. The lessons learned from the caregiving role of family caregivers of patients with Alzheimer’s disease or schizophrenia can be used to improve the caregiving process of patients with cancer