Resilience has been defined as one’s ability to maintain a mental health state and overall well-being when undergoing grave stress or facing significant adversity. Numerous resilience-investigating research tools have been developed over the years, with the Connor–Davidson Resilience Scale (CD-RISC), a self-rated tool presenting valuable psychometric properties, remaining one of the most prominent. We aimed to translate and validate the brief CD-RISC-10 in a convenience sample of 584 nurses in Greece’s secondary and tertiary health care system. We conducted a confirmatory factor analysis and known-groups validity test and estimated the reliability of the CD-RISC-10. Our confirmatory factor analysis revealed that the scale had a unifactorial structure since all the model fit indices were very good. Moreover, the reliability of the CD-RISC-10 was very good since the acquired Cronbach’s alpha and McDonald’s omega were 0.924 and 0.925, respectively. Therefore, the Greek version of the CD-RISC-10 confirmed the factor structure of the original scale and had very good validity and reliability.

Background: There is an emerging need for evidence-based approaches harnessing large amounts of health care data and novel technologies (such as artificial intelligence) to optimize public health policy making. Objective: The aim of this review was to explore the data analytics tools designed specifically for policy making in noncommunicable diseases (NCDs) and their implementation. Methods: A scoping review was conducted after searching the PubMed and IEEE databases for articles published in the last 10 years. Results: Nine articles that presented 7 data analytics tools designed to inform policy making for NCDs were reviewed. The tools incorporated descriptive and predictive analytics. Some tools were designed to include recommendations for decision support, but no pilot studies applying prescriptive analytics have been published. The tools were piloted with various conditions, with cancer being the least studied condition. Implementation of the tools included use cases, pilots, or evaluation workshops that involved policy makers. However, our findings demonstrate very limited real-world use of analytics by policy makers, which is in line with previous studies. Conclusions: Despite the availability of tools designed for different purposes and conditions, data analytics is not widely used to support policy making for NCDs. However, the review demonstrates the value and potential use of data analytics to support policy making. Based on the findings, we make suggestions for researchers developing digital tools to support public health policy making. The findings will also serve as input for the European Union–funded research project ONCODIR developing a policy analytics dashboard for the prevention of colorectal cancer as part of an integrated platform.

Purpose: The higher-level aim of this study is to investigate the impact of health information needs satisfaction on the fear of COVID-19 for the general population. The investigation is theoretically grounded on Wilsons’ model of information seeking in the context of inquesting the reasons for seeking health information as well as the information sources the general population deploy during the COVID-19 pandemic.Design/methodology/approach: This cross-sectional survey examines the correlations between health information seeking behavior and the COVID-19 generated fear in the general population through the application of a specially designed structured questionnaire which was distributed online. The questionnaire comprised four main distinct research dimensions (i.e. information needs, information sources, obstacles when seeking information and COVID-19 generated fear) that present significant validity levels.Findings: Individuals were motivated to seek COVID-related health information to cope with the pandemic generated uncertainty. Information needs satisfaction as well as digital health literacy levels is associated with the COVID-19 generated fear in the general population. Finally, a conceptual framework based on Wilsons’ macro-model for information seeking behavior was developed to illustrate information needs satisfaction during the pandemic period. These results indicate the need for incentives to enhance health information needs satisfaction appropriately.Originality/value: The COVID-19 generated fear in the general population is studied through the information seeking behavior lenses. A well-studied theoretical model for information seeking behavior is adopted for health-related information seeking during pandemic. Finally, digital health information literacy levels are also associated with the fear of COVID-19 reported in the authors’ survey.

Resilience has been defined as one's competence to maintain a mental health state and overall well-being when undergoing grave stress or facing significant adversities. Numerous resili-ence-investigating research tools were developed over the years, with the Connor-Davidson Re-silience Scale (CD-RISC), a self-rated tool presenting valuable psychometric properties, remaining one of the most prominent. We aimed to translate and validate the brief CD-RISC-10 in a convenient sample of 584 nurses in Greece's secondary and tertiary health care system. We conducted a con-firmatory factor analysis and known-groups validity and estimated the reliability of the CD-RISC-10. Our confirmatory factor analysis revealed that the scale had a unifactorial structure since all the model fit indices were very good. Moreover, the reliability of the CD-RISC-10 was very good since Cronbach's alpha was 0.924 and McDonald's omega was 0.925. Therefore, the Greek version of the CD-RISC-10 confirmed the factor structure of the original one and had very good validity and reliability.

This study investigated the relationship between health information-seeking behavior (HISB), digital health literacy, and fear of COVID-19 among Greek nursing staff during the pandemic. Utilizing a cross-sectional design grounded in Wilson's Model of Information-Seeking Behavior, a structured questionnaire was administered to 120 licensed professionals at a regional general hospital. The primary objective was to examine how informational needs and literacy levels correlated with psychological responses, specifically the fear of the virus. Results indicated that nursing staff were highly motivated to seek information regarding COVID-19 treatments and patient protocols. Younger and less experienced staff favored official sources, such as journals and formal training. While overall levels of fear of COVID-19 were generally low, significant variations emerged based on demographics; male staff and those aged over 51 reported higher anxiety. Furthermore, fear of COVID-19 was found to be negatively correlated with satisfaction with available information. These findings emphasized the necessity of empowering digital health literacy and tailoring informational resources to mitigate fear and enhance professional preparedness during public health crises.

Purpose: This paper introduces a novel conceptual framework depicting individuals’ health information-seeking behavior during public health emergencies within the complex circumstances induced in the highly digitalized era we currently live in. It discusses the empirical findings and theoretical insights that impacted its synthesis as well as its theoretical and practical implications. Design/methodology/approach: A narrative literature review was conducted to identify human behavioral theories and information behavior macromodels applicable to portray, elaborate and predict individuals’ health information behavior at times of crisis, considering additional impactful factors that had as well emerged from the literature review, i.e. personality. The integrated model of health literacy was expanded by Wilson’s 1981 model of information-seeking behavior and Savolainen’s model of everyday life information seeking, to encapsulate a varying set of determining factors that shape one’s information behavior during public health emergencies. Findings: A multitude of parameters at the personal and societal levels determines how an individual will respond to his/hers information needs triggered by a public health crisis outbreak. The information behavior demonstrated will be additionally impacted by relevant collective information-seeking endeavors as well as the emerging threats of misinformation, disinformation and infodemics. Therefore, health behaviors and outcomes observed during and after the manifestation of a public health crisis appear strongly linked to individuals’ health information needs satisfaction as well as his/hers health information literacy levels. Originality/value: While prior models have examined health information behavior during emergencies, this framework offers a novel integration of behavioral, personal, societal and contextual dimensions specific to public health crises, thereby aiming to advance a more multidimensional understanding of this complex human function. Once validated, the findings will have broad significance for policymakers, as they would be in a position to prepare for and respond to imminent threats holistically while strengthening citizens’ digital competencies and enhancing their health information literacy.