Introduction: Post-COVID-19 is an increasing chronic disease for which potential treatment options require further development and examination. A well-established approach to symptom management in post-COVID-19 patients could be e-Health interventions. To enhance the implementation and utilization of e-Health interventions, the needs and demands of patients should be taken into consideration. The aim of this study was to investigate needs and demands of post-COVID-19 patients concerning e-Health symptom management interventions. Methods: A total of 556 patients participated in this cross-sectional online survey study. Recruitment was performed from January 19 to May 24, 2022. Data related to the needs and demands for e-Health interventions were analyzed, along with medical and sociodemographic information. Results: The majority of the patients preferred interventions accessible on smartphones (95.3%). The favored content formats were applications (82.7%), interactive training (69.3%), or audio and video materials (61.1%). Furthermore, the preferred session length was about 10-20 min. The most desired topics included "quality of life," "information about how intensively I may exert myself or do sports," "adjustment to new life situation," and "handling physical changes." Conclusions: This study provides a detailed framework for the content and design of e-Health interventions to support patients managing their post-COVID-19 symptoms. The findings could significantly influence the further development of tailored e-Health interventions to address this pressing global health concern.
Objective: Increased utilization of e-health services can help to meet shortages of psychotherapeutic treatment. e-Health interventions can be effective if tailored according to the individual needs and demands of the target group. To gather comprehensive data for the development of a user-centered e-health intervention, a cross-sectional study was conducted among a heterogeneous cohort of 309 patients seeking treatment or consultation at psychosomatic university hospital in a densely populated region of Germany. Methods: Sociodemographic data, psychometric dimensions of mental burden, as well as needs and demands regarding an e-health intervention were assessed. A descriptive statistical analysis and a cluster analysis were performed to examine distribution of preferences and differences based on level of burden regarding needs and demands for e-health interventions. Results: Two hundred thirty-nine (N = 239) participants were included in the final data analysis. Among this primarily urban target group smartphone availability was favored by 77.8% of the participants. The cluster analysis revealed significant differences dependent on mental burden. 75.2% of participants with a high mental burden preferred longer interventions of 1-4 months compared with 49% in the low burden group, which also considered short interventions of up to 1 month (46%). Differences were also identified for content preferences and daily-life integration and were consistent irrespective of the initial reason for consultation. Conclusion: The findings of this study can provide a foundational framework for developing user-centered psychosomatic interventions. The potential relationship between individual burden and individual needs and demands highlights the crucial role of preliminary research to tailor interventions to effectively address diverse needs and preferences.
Background: Due to digitization in the medical sector, many healthcare interactions are switched to online services. This study assessed the acceptance of video consultations (VCs) in cancer care, and determined drivers and barriers of acceptance. Methods: A cross-sectional online-based survey study was conducted in Germany from February 2022 to February 2023. Recruitment took place at oncology outpatient clinics, general practitioners, oncology practices and via cancer-related social media channels. Inclusion criteria were a cancer diagnosis, cancer treatment and internet access. Sociodemographic, medical data, eHealth-related data were acquired via an online assessment. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to determine the acceptance of VC and its predictors. Results: Of N = 350 cancer patients, 56.0% (n = 196) reported high acceptance of VC, 28.0% (n = 98) stated moderate acceptance and 16.0% (n = 56) indicated low acceptance. Factors influencing acceptance were younger age (ß = -.28, p < .001), female gender (ß = .35, p = .005), stage of disease (ß = .11, p = .032), high digital confidence (ß = .14, p = .010), low internet anxiety (ß = -.21, p = .001), high digital overload (ß = -.12, p = .022), high eHealth literacy (ß = .14, p = .028), personal trust (ß = -.25, p < .001), internet use (ß = .17, p = .002), and the UTAUT predictors: performance expectancy (ß = .24, p < .001), effort expectancy (ß = .26, p < .001), and social influence (ß = .34, p < .001). Conclusions: Patients' acceptance of VC in cancer care is high. Drivers and barriers to acceptance identified should be considered for personalized applications. Considering the growing demand for cancer care establishing digital healthcare solutions is justified.
Introduction: Elite athletes are exposed to a variety of sport-specific stressors that may put them at particular risk for mental health symptoms and disorders. The aim of the present study was to assess data on mental health of elite athletes and investigate associations and interconnections among different variables using network analysis. Methods: A cross-sectional study was conducted from December 2021 to December 2022. The sample consisted of 275 German elite athletes (167 females) aged ≥18 years. Next to sociodemographic, medical and sport-related data, psychometric data such as psychological distress, symptoms of generalized anxiety, depression, and somatic symptom disorder have been gathered through questionnaires and analyzed by means of network analysis. Results: Over 95.0% of the athletes showed elevated distress and 28.6% reported symptoms of depression. Results of the network analysis show, among other findings, that symptoms of somatic symptom disorder were associated with severe injuries and substance use. Moreover, elite athletes who reported a better financial situation reported fewer symptoms of depression, generalized anxiety, and somatic symptom disorder. They also reported a lower incidence of mild to moderate injuries and severe injuries, fewer years spent in elite sports, less substance use, and fewer training sessions per week. Conversely, these athletes reported a higher level of distress. Furthermore, sex, financial situation and number of training units per week emerged as significant predictors for mental health symptoms. Discussion: Elite athletes showed increased numbers regarding mental health symptoms. Providing appropriate mental health interventions for elite athletes and further analysis of factors that influence the mental health of elite athletes and their interplay seem to be of central importance for the general well-being of elite athletes.
Aims: Cardiovascular diseases are one of the main contributors to disability and mortality worldwide. Meanwhile, risk factors can be modified by lifestyle changes. mHealth is an innovative and effective way to deliver cardiac health promotion. This study aims to examine the needs and demands regarding the design and contents of an mHealth intervention for cardiac health promotion among individuals with cardiac diseases. Different clusters were determined and analysed in terms of the intention to use an mHealth intervention. Methods and results: A cross-sectional study was conducted via a web-based survey. Three hundred and four individuals with coronary artery diseases (CADs) and/or congestive heart failure (CHF) were included in the data analysis. Descriptive statistics were applied to evaluate needs and demands regarding an mHealth intervention. A k-medoids cluster analysis was performed. Individuals with CAD and CHF favoured an mHealth intervention that supports its users permanently and is easily integrated into everyday life. Handheld devices and content formats that involve active user participation and regular updates were preferred. Three clusters were observed and labelled high, moderate, and low burden, according to their psychometric properties. The high burden cluster indicated higher behavioural intention towards use of an mHealth intervention than the other clusters. Conclusion: The results of the study are a valuable foundation for the development of an mHealth intervention for cardiac health promotion following a user-centred design approach. Individuals with cardiac diseases report positive attitudes in the form of high usage intention regarding mHealth. Highly burdened individuals report a high intention to use such interventions.
Background: The internet is most people's primary source of (health) information. However, no validated instrument exists to assess eHealth literacy in the group of patient with cardiac diseases. Objective: The objective of this study was the evaluation of the psychometric properties of the German revised version of the eHealth literacy scale (GR-eHEALS) in individuals with coronary artery disease (CAD) and congestive heart failure (CHF). Methods: A cross-sectional study was conducted. N = 455 were included in the statistical analyses. The assessment compromised the GR-eHEALS, medical history, sociodemographic data, and technology-related data. Confirmatory factor analyses, correlational analyses, and tests of measurement invariance were performed. Results: The two-factorial model reached a good model fit. The sub-scales information seeking and information appraisal, as well as the eHealth literacy total score, reached high reliability coefficients. Construct and criterion validity was fully confirmed For the two-factorial model, measurement invariance up to the scalar level could be confirmed regarding the sociodemographic characteristics sex, age, and educational level. Conclusions: This study confirmed the two-factor structure, construct, and criterion validity as well as measurement invariance at the scalar level for sex, age, and educational level of the GR-eHEALS scale in a sample of individuals with CAD and CHF.
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.
BACKGROUND: Cardiac diseases are a major global health issue with an increasing prevalence of affected people. Rehabilitation following cardiac events is underutilized, despite its proven effectiveness. Digital interventions might present a useful addition to traditional cardiac rehabilitation. AIMS: This study aims to assess the acceptance of mobile health (mHealth) cardiac rehabilitation and to investigate the underlying factors of acceptance in patients with ischemic heart disease and congestive heart failure. METHODS: A cross-sectional study was conducted from November 2021 to September 2022 with N = 290 patients. Sociodemographic, medical, and eHealth-related data were assessed. The Unified Theory of Acceptance and Use of Technology (UTAUT) was applied. Group differences in acceptance were examined and a multiple hierarchical regression analysis was conducted. RESULTS: The overall acceptance of mHealth cardiac rehabilitation was high (M = 4.05, SD = 0.93). Individuals with mental illness reported significantly higher acceptance (t(288) = 3.15, padj = 0.007, d = 0.43). Depressive symptoms (ß = 0.34, p < 0.001); digital confidence (ß = 0.19, p = 0.003); and the UTAUT predictors of performance expectancy (ß = 0.34, p < 0.001), effort expectancy (ß = 0.34, p < 0.001), and social influence (ß = 0.26, p < 0.001) significantly predicted acceptance. The extended UTAUT model explained 69.5% of the variance in acceptance. CONCLUSIONS: As acceptance is associated with the actual use of mHealth, the high level of acceptance found in this study is a promising basis for the future implementation of innovative mHealth offers in cardiac rehabilitation.
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.
INTRODUCTION: Several studies indicate an association between mental disorders and overweight or obesity. E-Mental health interventions offer an effective way to overcome barriers to health care access for individuals with overweight and obesity. The objective of this study was to examine the needs and demands for e-mental health interventions among individuals with overweight and obesity. METHODS: A cross-sectional study was conducted from 2020 to 2021 in Germany. A total of 643 participants were recruited through specialized social media platforms and the Alfried-Krupp hospital in Essen, Germany. Sociodemographic and medical data were analysed, as well as data on depressive symptoms and on the needs and demands for e-mental health interventions. RESULTS: Contact with and recommendation by experts appear to be key aspects in the acceptance and use of e-mental health interventions. In summary, most participants preferred a 20-30-min weekly session via smartphone over a 4-month period. The highest preference in terms of features included practicing coping skills and being provided with information; in regard to desired topics, nutrition consultation, quality of life, and adapting to new life situations were considered most important. DISCUSSION: e-Mental health interventions can be highly beneficial for individuals, especially when developed through a user-centred design approach. The results of the study indicate which content and design are preferred and, thereby, provide valuable information for consideration when developing a tailored e-mental health intervention.
Mental Health , Overweight , Humans , Overweight/therapy , Overweight/psychology , Quality of Life , Cross-Sectional Studies , Obesity/therapy
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.
INTRODUCTION: This study investigated the mental health burden of patients with chronic inflammatory demyelinating polyneuropathy (CIDP) or multifocal motor neuropathy (MMN) during the COVID-19 pandemic in comparison to matched healthy controls. METHODS: The cross-sectional study included 59 patients with a diagnosis of either CIDP or MMN and 59 propensity score matched healthy controls. All participants completed a survey including demographics, distress (distress thermometer), depressive symptoms (PHQ-2), generalized anxiety (GAD-7), COVID-19-related fear, and risk perception. Additionally, patients with CIDP or MMN were asked about the frequency and type of infections since treatment initiation. RESULTS: Patients with either CIDP or MMN reported experiencing reduced frequency or no differences in infection frequency since immune medication was initiated. Regarding COVID-19, patients with CIDP or MMN rated their risk of infection similar to healthy controls, while they expected a higher probability of the occurrence of symptoms, severe course, and dying of COVID-19. They reported increased depressive symptoms, generalized anxiety, and COVID-19-related fear in comparison to healthy controls. CONCLUSION: Despite their personal experience of reduced frequency of infection since immune medication was initiated, patients with CIDP or MMN reported increased risk perception and prevalence of depressive symptoms, generalized anxiety, and COVID-19-related fear in comparison to healthy controls. This highlights the need for evidence-driven strategies to protect the mental health of this vulnerable group.
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.
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.
COVID-19 , Diabetes Mellitus , Anxiety/epidemiology , Cross-Sectional Studies , Depression/epidemiology , Disease Outbreaks , Humans , Mental Health , Pandemics , Retrospective Studies , SARS-CoV-2
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.
