Association of COVID-19 with lifestyle behaviours and socio-economic variables in Turkey: An analysis of Google Trends.

This study aims to examine the relationship between COVID-19 cases/deaths and Google data on lifestyle behaviours and socio-economic variables in Turkey. The data of the research are composed of Google Trends search volume for various words related to socio-economic conditions, nutritional attitudes, indoor behaviour, outdoor activities and confirmed COVID-19 case and death data from the Ministry of Health from 31 December 2019 to 31 January 2021. Spearman correlation analysis was conducted to evaluate the relationship between the Google search volumes of selected keywords and COVID-19 case and deaths. In addition, repeated ANOVA and Bonferroni post-hoc tests were performed to compare the differences in search volumes of selected keywords before and during the COVID-19 outbreak. Correlation analysis showed that the strongest variables in each category were vitamin C, zinc, Zoom, online shopping, hotel, market, gym, unemployment and unemployment benefit. Compared to previous years, during the pandemic, there was a significant increase or decrease in the search volumes of almost all words. These results showed that the COVID-19 significantly changed people's online interests regarding lifestyle behaviours and socio-economic conditions. It is thought that the findings can guide health policies to be followed in reducing the effects of both behavioural changes and negative socio-economic consequences.

Impacts of Economic Freedom, Health, and Social Expenditures on Well-Being Measured by the Better Life Index in OECD Countries.

The Organization for Economic Co-operation and Development (OECD) has developed the Better Life Index (BLI), which is a multidimensional approach to well-being. This study aims to investigate the impact of health and social expenditures as well as the economic freedom index on well-being measured by BLI among 34 OECD countries for 2013-2017 period. We estimated panel models to observe the social and health expenditure effects according to their sources and the overall impact of economic changes among countries. We find that public and private social expenditures have a positive and statistically significant impact on BLI at 1% significance level. Additionally, whereas public health expenditure has a positive and statistically significant impact on BLI at 1% significance level, the effects of private health expenditure are statistically significant at 10% significance level. The economic freedom index has a positive and statistically significant impact on BLI in both models. Both social and health expenditures should take a prominent position in policy debates for a better life.

Predictors of hospital readmissions in internal medicine patients: Application of Andersen's Model.

OBJECTIVE: This study aimed to identify predictors of internal medicine patients' readmission to hospital, using Andersen's behavioral model. METHODS: This prospective cohort study included 2622 patients aged ≥18 years, who were admitted to internal medicine wards at a university hospital between 1 February 2015 and 31 January 2016. Independent variables were divided into four groups (predisposing, enabling, need, and utilization), based on Andersen's model, and included in stepwise logistic regression analysis. RESULTS: Younger age, male sex, a main diagnosis of neoplasm, longer length of stay, higher comorbidity scores, and weaker coping ability predicted all readmission. Predictors of unplanned readmission included having someone to help at home following discharge, comorbidity scores, and length of stay. Predictors of unplanned, related, and preventable readmissions included having someone to help at home following discharge, having a regular physician, and the main diagnosis at discharge. The most powerful predictors influencing readmission were need-related variables. CONCLUSION: Although some predictors of readmission were unalterable, they could be used to identify high-risk patients. Innovative approaches targeting discharge planning and postdischarge care for patients with high comorbidity scores and long length of stay could reduce internal medicine patients' unplanned readmission.

Ethical climate as a moderator between organizational trust and whistle-blowing among nurses and secretaries.

OBJECTIVES: To reveal the effect of perception of ethical climate by nurses and secretaries and their level of organizational trust on their whistleblowing intention. METHODS: Nurses and secretaries working in a University Hospital in Ankara, Turkey, were enrolled in the study conducted in 2016. Responses were received from 369 nurses and secretaries working at Clinics and Polyclinics. Path analysis, investigation of structural equation models used while multi-regression analysis was also applied. RESULTS: According to the regression model, ethical climate dimensions, profession, gender, and work place had significant impact on the whistleblowing intention. According to Path analysis, ethical climate had direct impact of 69% on whistleblowing intention. It was seen that organizational trust had an indirect impact of 27% on the whistleblowing score when ethical climate had a moderator role. CONCLUSION: In order to promote whistleblowing in organizations, it is important to keep the ethical climate perception of employees and the level of their organizational trust at high levels.

Patients' readiness for discharge: Predictors and effects on unplanned readmissions, emergency department visits and death.

AIM: To determine the variables that affect patients' perceptions about their readiness for discharge and to elucidate the effects of these perceptions on patient outcomes such as unplanned readmission to the hospital, emergency department visits and death within 30 days after discharge. BACKGROUND: In recent years, it has become even more important to assess patients' readiness for discharge as patients tend to be discharged more quickly. METHODS: For the determination of patients' self-assessment, the Readiness for Hospital Discharge Scale/Short Form was utilized. This 1-year prospective cohort study included 1,601 patients. Data were analysed using a chi-square test, Mann-Whitney U test, univariate logistic regression analysis and multiple logistic regression analysis. RESULTS: The results of multiple logistic regression analysis revealed that age, sex, marital status, educational status, presence of someone to help at home after discharge and length of stay were predictors of patients' readiness for hospital discharge. Furthermore, being unready for discharge increased the risk of 30 day unplanned readmission and 30 day death. CONCLUSIONS: Considering these predictors, patients' perceptions of readiness for discharge must be assessed before deciding to discharge them. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers can consider the predictors of patients' readiness for discharge, thus the risk of unplanned readmission and death may be reduced.

A comprehensive framework identifying readmission risk factors using the CHAID algorithm: a prospective cohort study.

OBJECTIVE: To identify frequency of readmission after discharge from internal-medicine wards, readmission risk factors, and reasons and costs of readmission. DESIGN: Prospective cohort study. SETTING: A tertiary-care hospital in Turkey. PARTICIPANTS: 2622 adult patients discharged from internal-medicine wards of the hospital between 1 February 2015 and 31 January 2016. MAIN OUTCOME MEASURES: Thirty day all-cause readmission rates, reasons and costs of readmission. To identify readmission risk factors Chi-square Automatic Interaction Detector (CHAID) analysis was conducted. RESULTS: The same hospital readmission rate was 17.9%, while the same hospital or different-hospital readmission rate was 21.3%. Receiver operating characteristic (ROC) curve analysis showed that the predictive performance of the CHAID algorithm was high. According to the CHAID algorithm, the most significant readmission risk factor was the main diagnosis of neoplasm at the index admission. In other diagnosis groups, higher Charlson comorbidity score, higher level of education, having a regular physician, and three dimensions of Readiness for Hospital Discharge Scale were significant risk factors for readmission. The most frequent reason for readmission was neoplasm, and the total cost of readmissions was ~$900 000. CONCLUSIONS: The CHAID algorithm for readmissions had a high predictive strength and provided details that aid physicians in decision-making. Measures must be taken from initial diagnosis to post-discharge follow-up, to minimize readmissions, especially in patients with neoplasm.

Validity and reliability of the Turkish version of the readiness for hospital discharge scale/short form.

AIM: The aim of this study is to test the validity and reliability of the Turkish version of the readiness for hospital discharge scale/short form. BACKGROUND: Assessment of readiness for discharge from the patient's perspective is becoming increasingly important for patient safety, satisfaction and various patient outcomes such as readmission, health service utilization and mortality. The readiness for hospital discharge scale/short form allows health care providers to determine patients' discharge readiness. METHODS: Participants were 1,579 inpatients from internal medicine departments. The readiness for hospital discharge scale/short form was translated into Turkish via back-translation. We analyzed its reliability and validity via item analyses, an expert panel (content validity) and exploratory and confirmatory factor analyses (construct validity). RESULTS: The Cronbach's alpha of the whole scale was .74 and those for the subscales ranged from .79 to .93. The Spearman-Brown reliability coefficient was .92. The confirmatory factor analysis revealed good fit indices (χ2 /df = 2.6; RMSEA = .03; CFI = 1; GFI and AGFI = .99). The mean total score was 7.27 ± 1.85, while the subscale means ranged from 6.62 ± 3.41 to 7.69 ± 2.24. CONCLUSION: The Turkish version of the readiness for hospital discharge scale/short form is a valid and reliable tool for assessing discharge readiness. The subscales with low means suggest opportunities for improvement. IMPLICATIONS FOR NURSING MANAGEMENT: If readiness for hospital discharge scale/short form is valid and reliable, patients who are unready for discharge can be determined with this scale. Thus, nurse managers can determine what kind of measures should be taken for patients who are not ready for discharge, can control nursing practices related to these patients and can provide cooperation between the nurses and other health professionals.