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.

The management of a healthcare organization is monitored using a suitably designed questionnaire to 271 nurses operating in Greek hospital. The data are fed to an automatic data mining system to obtain a suitable series of models to analyse, visualise and study the obtained information. Hidden patterns, correlations and interdependencies are investigated and the results are analytically presented.

The factors that contribute and outline the perceived satisfaction of the primary health care system in Greece are presented and analysed. A model correlate all these factors and a prediction tool is used to demonstrate how they influence in the overall result. The study is based in a sample taken by stratified random sampling and covers a period of recent four years.