Acceptance, drivers, and barriers to use eHealth interventions in patients with post-COVID-19 syndrome for management of post-COVID-19 symptoms: a cross-sectional study.

Background: Post-COVID-19 syndrome is a new and debilitating disease without adequate treatment options. eHealth could be a reasonable approach for symptom management. Objectives: This study aims to evaluate the acceptance for eHealth interventions for symptom management in individuals with post-COVID-19 syndrome, as well as drivers and barriers influencing acceptance. Design: Cross-sectional study. Methods: This study was conducted from January 19 until 24 May 2022. Recruitment took place with a web-based survey. Acceptance and predictors of eHealth interventions were measured by the extended UTAUT model. Included in the model were the core predictor performance expectancy, social influence, and effort expectancy. Previously diagnosed mental illness was estimated and mental health by using the well-established Generalized Anxiety Disorder Scale-7 and the Patient Health Questionnaire Depression Scale. The effect of sociodemographic and medical data was assessed. Multiple hierarchical regression analyses as well as group comparisons were performed. Results: 342 individuals with post-COVID-19 syndrome were examined. The acceptance of eHealth interventions for symptom management was moderate to high (M = 3.60, SD = 0.89). Acceptance was significantly higher in individuals with lower/other education, patients with moderate to severe symptoms during initial COVID-19 infection, still significantly impaired patients, and individuals with a mental illness. Identified predictors of acceptance were age (ß = .24, p < .001), current condition including moderate (ß = .49, p = .002) and still significantly impaired (ß = .67, p < .001), digital confidence (ß = .19, p < .001), effort expectancy (ß = .26, p < .001), performance expectancy (ß = .33, p < .001), and social influence (ß = .26, p < .001). Conclusion: Patients with post-COVID-19 syndrome reported a satisfying level of acceptance and drivers and barriers could be identified. These factors need to be considered for the implementation and future use of eHealth interventions.

Predictors of patients' acceptance of video consultation in general practice during the coronavirus disease 2019 pandemic applying the unified theory of acceptance and use of technology model.

Background: The coronavirus disease 2019 pandemic has led to an increase in remote consultations in health care. This study aimed to assess the acceptance of video consultation as an alternative to face-to-face in-office visits in general practice (GP) and to investigate its drivers and barriers. Methods: A cross-sectional study was conducted in Germany during the coronavirus disease 2019 pandemic from December 2020 to April 2021. Participants were recruited among patients in 16 GP surgeries. Assessed were sociodemographic and medical data as well as information and communications technology related data. Acceptance of video consultation and its predictors were determined using a modified questionnaire based on a short version of the renowned unified theory of acceptance and use of technology model. Results: In total, 371 participants were included in the data analysis. Acceptance of video consultation was moderate. A hierarchical regression revealed acceptance was significantly predicted by the PHQ-2, taking no regular medication, computer proficiency, knowledge about digital health care solutions, no prior use of video consultation, and the unified theory of acceptance and use of technology predictors performance expectancy, effort expectancy, and social influence. The extended unified theory of acceptance and use of technology model explained significantly more variance than the restricted unified theory of acceptance and use of technology model in acceptance of video consultation. Conclusions: In this study computer proficiency, existing knowledge about digital health care solutions and depressive symptoms functioned as drivers to acceptance, no prior use of video consultation could be identified as a potential barrier. Patients with regular medication have been particularly receptive to video consultation. The study confirmed the validity of the unified theory of acceptance and use of technology model in determining acceptance of video consultation. Considering that there is growing demand and acceptance for different approaches to engage with health care providers, additional steps should be taken to establish video consultation as a genuine alternative.

Determining the Influencing Factors on Acceptance of eHealth Pain Management Interventions Among Patients With Chronic Pain Using the Unified Theory of Acceptance and Use of Technology: Cross-sectional Study.

BACKGROUND: Chronic pain is a complex disease with high prevalence rates, and many individuals who are affected do not receive adequate treatment. As a complement to conventional therapies, eHealth interventions could provide many benefits to a multimodal treatment approach for patients with chronic pain, whereby future use is associated with the acceptance of these interventions. OBJECTIVE: This study aims to assess the acceptance of eHealth pain management interventions among patients with chronic pain and identify the influencing factors on acceptance. A further objective of the study is to evaluate the viability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and compare it with its extended version in terms of explained variance of acceptance. METHODS: We performed a cross-sectional web-based study. In total, 307 participants with chronic pain, as defined according to the International Association for the Study of Pain criteria, were recruited through flyers, posters, and web-based inquiries between December 2020 and July 2021. In addition to sociodemographic and medical data, the assessment included validated psychometric instruments and an extended version of the well-established UTAUT model. For statistical analyses, group comparisons and multiple hierarchical regression analyses were performed. RESULTS: The acceptance of eHealth pain management interventions among patients with chronic pain was overall moderate to high (mean 3.67, SD 0.89). There was significant difference in acceptance among age groups (W=9674.0; r=0.156; P=.04). Effort expectancy (ß=.37; P<.001), performance expectancy (ß=.33; P<.001), and social influence (ß=.34; P<.001) proved to be the most important predictors of acceptance. The extended UTAUT (including the original UTAUT factors as well as sociodemographic, medical, and eHealth-related factors) model explained 66.4% of the variance in acceptance, thus supporting the viability of the model. Compared with the original UTAUT model (performance expectancy, effort expectancy, and social influence), the extended model explained significantly more variance (F25,278=1.74; P=.02). CONCLUSIONS: Given the association between acceptance and future use, the knowledge of the influencing factors on acceptance should be used in the development and promotion of eHealth pain management interventions. Overall, the acceptance of eHealth pain management interventions was moderate to high. In total, 8 predictors proved to be significant predictors of acceptance. The UTAUT model is a valuable instrument for determining acceptance as well as the factors that influence acceptance of eHealth pain management interventions among patients with chronic pain. The extended UTAUT model provided the greatest predictive value for acceptance.

Increased Safety Behavior and COVID-19-Related Fear in Adults with Cystic Fibrosis during the Pandemic.

People with cystic fibrosis (pwCF) face great challenges during the ongoing COVID-19 pandemic. Recent research found equal levels of distress in pwCF and healthy controls (HC). The current study aimed to investigate the mental health burden and safety behavior in pwCF. Sixty-nine adult pwCF and sixty-nine propensity-score-matched HC participated in this study. Participants completed an anonymous online questionnaire assessing distress, generalized anxiety, depressive symptoms, COVID-19-related variables, self-reported adherent safety behavior (ASB), and dysfunctional safety behavior (DSB). PwCF showed equal amounts of distress (W = 2481.0, p = 0.669), depressive symptoms (W = 2632.5, p = 0.268), and generalized anxiety symptoms (W = 2515.5, p = 0.565) compared to the HC. COVID-19-related fear (W = 1872.0, p = 0.028), ASB (W = 1630.0, p = 0.001), and DSB (W = 1498.5, p < 0.001) were significantly elevated in pwCF. The pwCF estimated that the probability of suffering from symptoms (W = 954.5, p < 0.001), experiencing a severe course (W = 806.5, p < 0.001), or dying (W = 1079.0, p < 0.001) from COVID-19 is significantly higher than that of the HC. ASB was associated with a CF diagnosis, COVID-19-related fear, and a subjective level of information (R2 = 0.414, F(13, 124) = 6.936, p ≤ 0.001). DSB was associated with a diagnosis of CF and COVID-19-related fear (R2 = 0.196, F(13, 124) = 3.169, p ≤ 0.001). The data suggest that pwCF show functional and adequate behaviors towards the risk caused by the pandemic. Therefore, functional coping behaviors may provide advantages in addressing pandemic challenges.

Mental health burden of patients with diabetes before and after the initial outbreak of COVID-19: predictors of mental health impairment.

BACKGROUND: The COVID-19 pandemic is affecting people's mental health worldwide. Patients with diabetes are at risk for a severe course of illness when infected with SARS-CoV-2. The present study aims to retrospectively examine mental health changes in patients with diabetes in Germany before and after the initial COVID-19 outbreak, and to furthermore explore potential predictors of such changes. METHODS: Over the course of eight weeks from April to June 2020, 253 individuals diagnosed with diabetes participated in an online cross-sectional study. Participants completed an anonymous survey including demographics, depression (PHQ-2) and generalized anxiety symptoms (GAD-2), distress (DT), and health status (EQ-5D-3L). In addition, all instruments used were modified to retrospectively ask participants to recall their mental health and health status before the outbreak had started. Additionally examined factors were COVID-19-related fear, trust in governmental actions to face the pandemic, and the subjective level of information about COVID-19. RESULTS: This study shows a significant increase in prevalence of depression symptoms, generalized anxiety symptoms and distress, as well as significantly decreased health statuses in diabetes patients after the initial COVID-19 outbreak. Increased depression symptoms, generalized anxiety symptoms and distress were predicted by COVID-19-related fear, whereas trust in governmental actions to face COVID-19 predicted higher depression symptoms. CONCLUSIONS: The results indicate a negative impact of the initial COVID-19 outbreak on mental health and health status in patients with diabetes. In order to improve the efficacy of psychological support strategies for diabetes patients during the pandemic, possible predictors of mental health impairment such as the aforementioned should be examined more thoroughly and addressed more openly.

Evaluation of the E-Mental Health Mindfulness-Based and Skills-Based "CoPE It" Intervention to Reduce Psychological Distress in Times of COVID-19: Results of a Bicentre Longitudinal Study.

Background: The SARS-CoV-2 pandemic poses immense challenges for health care systems and population-wide mental health. The e-mental health intervention "CoPE It" has been developed to offer standardized and manualized support to overcome psychological distress caused by the pandemic. The aim of this study was to assess the effectiveness of "CoPE It" in terms of reducing distress (primary outcome), depression and anxiety symptoms, and improving self-efficacy, and mindfulness (secondary outcomes). Furthermore, the intervention's usability, feasibility, and participants' satisfaction with "CoPE It" was evaluated (tertiary outcome). The study protocol has been published previously. Methods: A bicentre longitudinal study was conducted from April 27th 2020 to May 3rd 2021. N = 110 participants were included in the analyses. The intervention consisted of four modules featuring different media promoting evidence-based methods of cognitive behavioral therapy and mindfulness-based stress reduction. Difference in psychological distress between baseline (T0) and post-intervention (T1) were analyzed by repeated measure analysis of covariance. Mixed linear models were applied to assess moderating effects. Depressive symptoms, generalized anxiety symptoms, self-efficacy, and mindfulness were compared between baseline (T0) and post-intervention (T1) via t-tests. Usability of the "CoPE It" intervention and participants' satisfaction was evaluated by calculation means and frequencies. Results: Primary outcome: A significant effect of time on psychological distress at post-intervention (T1) after controlling for age, gender, education, mental illness and attitudes toward online interventions was found. Depressive and anxiety symptoms, and mindfulness were a significant moderators of the relationship between time and psychological distress for consistent wording. Secondary outcomes: There was a significant decrease in depressive symptoms and generalized anxiety, and a significant increase in self-efficacy and mindfulness between baseline (T0) and post-intervention (T1). Tertiary outcomes: 95.83% of the participants thought the "CoPE It" intervention was easy to use and 87.50% were satisfied with the "CoPE It" intervention in an overall, general sense. Conclusion: The e-mental health "CoPE It" intervention seems to be an effective approach in reducing psychological distress, anxiety and depressive symptoms, and in enhancing self-efficacy and mindfulness during the COVID-19 pandemic. Participants' satisfaction and the program's feasibility, and usability were proven to be high. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: DRKS00021301.