This study explores the levels of COVID-19 knowledge, risk perception, and preventive behavior practice in Seoul, to determine whether knowledge and risk perception are significantly associated with the full adoption of preventive behaviors, for the delivery of a customized public campaign to Seoul’s citizens. A total of 3000 Seoul residents participated in this study through an online questionnaire survey. They had a mean score of 84.6 for COVID-19 knowledge (range: 0–100 points) and 4.2 (range: 1–7 points) for risk perception. Of the participants, 33.4% practiced full adoption of all three preventive behaviors: hand hygiene, wearing a face mask, and social distancing; wearing a face mask was practiced the most (81.0%). Women significantly adopted these three preventive behaviors more often compared with men. Both COVID-19 knowledge and risk perception were found to be significantly associated with the full adoption of preventive behaviors; however, this association differed by the type of preventive behavior. This indicates that city-level information on the levels of COVID-19 knowledge, risk perception, and preventive behaviors should be clearly and periodically communicated among public officers and healthcare professionals to continually raise the public’s awareness of the full adoption of non-pharmaceutical preventive behaviors.

Objective:There is scarce evidence revealing an association between job stress and cardiometabolic lifestyle modification behaviors among workers.Methods:A cross-sectional, correlation study was conducted among workers in high-risk and low-risk workplaces by work characteristics.Results:Workers in high-risk workplaces had significantly higher job stress levels than low-risk workplaces. Higher job stress was significantly associated with lower cardiometabolic lifestyle modification behaviors (β = −0.14, P = .001). This significant association was evident only for high-risk workplaces in total job stress (β = −0.16, P = .001), including job demand (β = −0.16, P = .005) and job insecurity (β = −0.11, P = .026).Conclusions:Strategies for alleviating job stress should be prioritized to high-risk workplaces, and these efforts may concomitantly contribute to cardiometabolic risk reduction.

Introduction: A hybrid intervention of online and offline behavioral strategies can be more effective in promoting multiple lifestyle behaviors than online strategies alone. However, little is known about the effects of hybrid behavioral strategies on the modification of multiple heart-healthy lifestyle behaviors in cardiovascular health. The present study aims to evaluate the effects of a community-based, heart-healthy lifestyle-promoting program (i.e., HeartHELP program) using hybrid behavioral strategies on heart-healthy lifestyle outcomes for individuals at cardiovascular risk. Hypothesis: We assessed three hypotheses: 1) a mobile-app group would be more likely to increase heart-healthy behavioral outcomes than a control group 2) a hybrid group would be more likely to increase heart-healthy behavioral outcomes than the control group 3) the hybrid group would be more likely to increase heart-healthy behavioral outcomes than the mobile-app group. Methods: The present study is a three-arm, parallel group, randomized controlled trial (clinical trial No. ISRCTN83643383) with assessments carried out at baseline and after a 12-week HeartHELP program. We will recruit 75 participants, each having at least one component of metabolic syndrome, in a community-based setting. The participants will be allocated to one of the following three study arms by age- and gender-stratified block randomization: (1) a hybrid group (n = 25), (2) a mobile-app group (n = 25), or (3) a control group (n = 25). The hybrid group will receive a “HeartHELP program” with hybrid strategies: (1) mobile-app use as an online strategy and (2) motivational interviewing counselling as an offline strategy. The mobile-app group will receive the online strategy exclusively. The control group will receive a brochure that will include information on cardiovascular health. The mobile-app use involves receiving text messages, self-monitoring six heart-healthy lifestyle behaviors, and receiving feedback text messages based on behavioral outcomes obtained from self-monitoring. The motivational interviewing counselling includes customized individual and group counseling based on motivational interviewing principle. At baseline and after 12 weeks, a battery of heart-healthy behavioral outcomes will be measured. The primary outcome will comprise heart-healthy behavioral practices; the secondary outcomes will be heart-healthy knowledge, heart-healthy motivation, heart-healthy self-efficacy, and cardiometabolic biomarkers (i.e., fasting glucose, total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides). In conclusion, we expect the community-based HeartHELP program to provide significant data findings on how heart-healthy behavioral practices can be improved, along with other cardiometabolic biomarkers.

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Background:The purpose of this study was to determine whether characteristics of metabolic syndrome (MetS) and MetS management behaviors would be significantly associated with health-related quality of life (HRQOL) among patients with liver transplantation. Methods: Ninety-four patients who underwent liver transplantation were recruited at an outpatient clinic from a university hospital in Seoul between December 2009 and June 2019. MetS was defined according to NCEP-ATP III. MetS management behaviors were measured by using the Evaluation Tool of a Lifestyle Habit for MetS Modification. HRQOL was measured by using the MOS SF-36 II and analyzed by categorizing physical QOL and mental QOL. Results:The means of physical and mental QOLs were 82.3 and 82.8 scores, respectively. MetS prevalence was 68% and a mean of MetS management behaviors was 97.0. MetS prevalence was not significantly associated with either physical or mental QOLs. However, an increase in abdominal obesity was significantly and negatively associated with physical (β=-0.53, P=0.001) and mental QOLs (β=-0.41, P=0.005), respectively. Of the MetS management behaviors, diet control (β=0.59, P=0.021) and drinking & smoking control (β=2.18, P<0.001) were significantly associated with physical QOL. Physical activity (β=1.45, P=0.001), diet control (β=0.51, P=0.013), and drinking & smoking control (β=2.00, P<0.001) were significantly associated with mental QOL. Conclusions: MetS may not associate with HRQOL directly but MetS management behaviors may associate with HRQOL among patients with liver transplantation. Therefore, nursing strategies for promoting MetS management behaviors should be enhanced to improve their HRQOL levels in outpatent clinics and community settings.

Aims This study aimed to develop a reliable and valid scale, i.e. the Heart-Healthy Information Questionnaire (HHIQ). Methods and results The HHIQ was developed in three phases: (i) creating the item pool, (ii) conducting a preliminary evaluating the items, and (iii) refining the scale and evaluating psychometric properties. An initial item pool of 77 items with a 3-point True/False format with a ‘Don’t know’ option was extracted from the literature review and 54 items reached content validity. The psychometric properties of HHIQ were tested with 1315 individuals without cardiovascular disease. By using the exclusion criteria of the difficulty index (&gt;0.95), discrimination index (&lt;10.0), and item-total correlation (tetrachoric coefficient &lt;0.2), 50 items were finally selected. The construct validity was determined by using the known-groups validation: Individuals (n = 107) who were educated with heart-healthy education sessions showed significantly higher scores of the HHIQ than those (n = 107) who were not educated (P = 0.015). The Kuder–Richardson formula 20 coefficient indicated good internal consistency (0.85), and the test–retest reliability coefficient with a 15-day interval also indicated good stability (0.78). A total score of the HHIQ was significantly correlated with a total score of the Evaluation Tool for Metabolic Syndrome Modification Lifestyles (ρ = 0.23, P &lt; 0.001). Conclusion The HHIQ showed good psychometric properties of validity and reliability and may be useful to evaluate the knowledge levels of heart-healthy information in the areas of cardiovascular disease prevention.

Introduction: Acquiring sufficient information about cardiovascular prevention is a prerequisite for individuals’ decision making to practice heart-healthy lifestyle behaviors. However, no well-validated instrument currently exists to measure the knowledge about information on heart disease symptoms, risk factors, and benefits of heart-healthy behaviors for cardiovascular prevention targeting healthy people. We used systematic scale development procedures to create a scale of the Heart-Healthy Information Questionnaire (HHIQ) based on the Information-Motivation-Behavioral skills model and recent scientific guidelines of cardiovascular prevention. Methods: Standard scale development methods were used to create items and test their psychometric properties. Participants were 1,315 people without cardiovascular diseases, who were residing in Seoul Metropolitan city. Results: We created preliminary 70 items using a 3-point True/False format with a Don’t know option. The items were two times reviewed by a panel of eight experts in terms of the relevance and clarity of the items, and 54 items were selected by using the cut-off score of content validity index (0.8 or greater). Next, we administrated the questionnaire of 54 items for 1,315 participants, and finally selected 50 items by using the cut-off scores of difficulty index ( < 0.95), discrimination index ( > 10), and item-total correlation (tetrachoric coefficient > 0.2). The Kuder-Richardson formula 20 coefficient for the HHIQ indicated good internal consistency (0.85), and the test-retest reliability coefficient with a 15-day interval also indicated that it had good stability (0.78). Finally, individuals (n = 107) who were informed from heart-healthy education sessions showed significantly higher scores of the HHIQ than those (n = 1,208) who were not informed (p = 0.009). A total score of the HHIQ was significantly correlated with a total score of the Heart Disease Facts Questionnaire (r = 0.61, p < 0.001) and significantly correlated with a total score of the Evaluation Tool for Metabolic Syndrome Modification Lifestyles (r = 0.23, p < 0.001). Conclusion: The HHIQ may be useful to evaluate the knowledge levels of heart-healthy information in the areas of cardiovascular prevention