COVID‐19 restrictions such as lockdowns or quarantines may increase the risk for social isolation and perceived loneliness. The mechanisms can be modeled by Cacioppo's Evolutionary Theory of Loneliness (ETL), which predicts that a lack of perceived social connectedness may lead, in the long‐term, to mental and physical health consequences. However, the association between COVID‐19 pandemic distress, mental health, and loneliness is not sufficiently understood. The present longitudinal study examined the relationship between distress and depression, and the mediating effects of anxiety and loneliness in a German rehabilitation sample ( N = 403) at two timepoints (≤6 weeks pre‐rehabilitation; ≥12 weeks post‐rehabilitation; mean time between T1 and T2 was 52 days). Change scores between T1 and T2 were examined for the variables COVID‐19 Peritraumatic Distress Index (CPDI), anxiety, loneliness, and depression. The results of the serial mediation analysis indicated that anxiety and loneliness were able to explain the relationship between distress and depression with 42% of variance in depression accounted for. Findings extend research on the relationship between COVID‐19 and mental health by considering anxiety and loneliness as sustaining factors of depressive symptoms, thus, successfully applying the ETL. Results stress the necessity to consider anxiety and loneliness in the treatment or prevention of depression.

Background: Patients with post-COVID/long-COVID symptoms need support, and health care professionals need to be able to provide evidence-based patient care. Digital interventions can meet these requirements, especially if personal contact is limited. Objective: We reviewed evidence-based digital interventions that are currently available to help manage physical and mental health in patients with post-COVID/long-COVID symptoms. Methods: A scoping review was carried out summarizing novel digital health interventions for treating post-COVID/long-COVID patients. Using the PICO (population, intervention, comparison, outcome) scheme, original studies were summarized, in which patients with post-COVID/long-COVID symptoms used digital interventions to help aid recovery. Results: From all scanned articles, 8 original studies matched the inclusion criteria. Of the 8 studies, 3 were “pretest” studies, 3 described the implementation of a telerehabilitation program, 1 was a post-COVID/long-COVID program, and 1 described the results of qualitative interviews with patients who used an online peer-support group. Following the PICO scheme, we summarized previous studies. Studies varied in terms of participants (P), ranging from adults in different countries, such as former hospitalized patients with COVID-19, to individuals in disadvantaged communities in the United Kingdom, as well as health care workers. In addition, the studies included patients who had previously been infected with COVID-19 and who had ongoing symptoms. Some studies focused on individuals with specific symptoms, including those with either post–COVID-19 or long-term symptoms, while other studies included patients based on participation in online peer-support groups. The interventions (I) also varied. Most interventions used a combination of psychological and physical exercises, but they varied in duration, frequency, and social dimensions. The reviewed studies investigated the physical and mental health conditions of patients with post-COVID/long-COVID symptoms. Most studies had no control (C) group, and most studies reported outcomes (O) or improvements in physiological health perception, some physical conditions, fatigue, and some psychological aspects such as depression. However, some studies found no improvements in bowel or bladder problems, concentration, short-term memory, unpleasant dreams, physical ailments, perceived bodily pain, emotional ailments, and perceived mental health. Conclusions: More systematic research with larger sample sizes is required to overcome sampling bias and include health care professionals’ perspectives, as well as help patients mobilize support from health care professionals and social network partners. The evidence so far suggests that patients should be provided with digital interventions to manage symptoms and reintegrate into everyday life, including work.

Background: Adherence to internet-delivered interventions targeting mental health such as online psychotherapeutic aftercare is important for the intervention’s impact. High dropout rates limit the impact and generalizability of findings. Baseline differences may be putting patients at risk for dropping out, making comparisons between online with face-to-face (F2F) therapy and care as usual (CAU) necessary to examine. Objective: This study investigated adherence to online, F2F, and CAU interventions as well as study dropout among these groups and the subjective evaluation of the therapeutic relationship. Sociodemographic, social-cognitive, and health-related variables were considered. Methods: In a randomized controlled trial, 6023 patients were recruited, and 300 completed the baseline measures (T1), 144 completed T2 (retention 44%-52%), and 95 completed T3 (retention 24%-36%). Sociodemographic variables (eg, age, gender, marital status, educational level), social-cognitive determinants (eg, self-efficacy, social support), health-related variables (eg, depressiveness), and expectation towards the treatment for patients assigned to online or F2F were measured at T1. Results: There were no significant differences between the groups regarding dropout rates (χ21=0.02-1.06, P≥.30). Regarding adherence to the treatment condition, the online group outperformed the F2F and CAU conditions (P≤.01), indicating that patients randomized into the F2F and CAU control groups were much more likely to show nonadherent behavior in comparison with the online therapy groups. Within study groups, gender differences were significant only in the CAU group at T2, with women being more likely to drop out. At T3, age and marital status were also only significant in the CAU group. Patients in the online therapy group were significantly more satisfied with their treatment than patients in the F2F group (P=.02; Eta²=.09). Relationship satisfaction and success satisfaction were equally high (P>.30; Eta²=.02). Combining all study groups, patients who reported lower depressiveness scores at T1 (T2: odds ratio [OR] 0.55, 95% CI 0.35-0.87; T3: OR 0.56, 95% CI 0.37-0.92) were more likely to be retained, and patients who had higher self-efficacy (T2: OR 0.57, 95% CI 0.37-0.89; T3: OR 0.52, 95% CI 0.32-0.85) were more likely to drop out at T2 and T3. Additionally, at T3, the lower social support that patients reported was related to a higher likelihood of remaining in the study (OR 0.68, 95% CI 0.48-0.96). Comparing the 3 intervention groups, positive expectation was significantly related with questionnaire completion at T2 and T3 after controlling for other variables (T2: OR 1.64, 95% CI 1.08-2.50; T3: OR 1.59, 95% CI 1.01-2.51). Conclusions: While online interventions have many advantages over F2F variants such as saving time and effort to commute to F2F therapy, they also create difficulties for therapists and hinder their ability to adequately react to patients’ challenges. Accordingly, patient characteristics that might put them at risk for dropping out or not adhering to the treatment plan should be considered in future research and practice. Online aftercare, as described in this research, should be provided more often to medical rehabilitation patients. Trial Registration: ClinicalTrials.gov NCT04989842; https://clinicaltrials.gov/ct2/show/NCT04989842

Background: The postacute COVID-19 syndrome (PACS) can be addressed with multidisciplinary approaches, including professional support and digital interventions. Objective: This research aimed to test whether patients who received a health care facilitation program including medical internet support from human personal pilots and digital interventions (intervention group [IG] and active control group [ACG]) would experience fewer symptoms and have higher work ability and social participation than an untreated comparison group (CompG). The second objective was to compare the impact of a diagnostic assessment and digital interventions tailored to patients’ personal capacity (IG) with that of only personal support and digital interventions targeting the main symptoms (ACG). Methods: In total, 1020 patients with PACS were recruited. Using a randomized controlled trial design between the IG and the ACG, as well as propensity score matching to include the CompG, analyses were run with logistic regression and hierarchical-linear models. Results: Symptoms decreased significantly in all groups over time (βT1-T2=0.13, t549=5.67, P<.001; βT2-T4=0.06, t549=2.83, P=.01), with a main effect of the group (β=–.15, t549=–2.65, P=.01) and a more pronounced effect in the IG and ACG compared to the CompG (between groups: βT1-T2=0.14, t549=4.31, P<.001; βT2-T4=0.14, t549=4.57, P<.001). Work ability and social participation were lower in the CompG, but there was no significant interaction effect. There were no group differences between the IG and the ACG. Conclusions: Empowerment through personal pilots and digital interventions reduces symptoms but does not increase work ability and social participation. More longitudinal research is needed to evaluate the effects of a diagnostic assessment. Social support and digital interventions should be incorporated to facilitate health care interventions for PACS. Trial Registration: ClinicalTrials.gov NCT05238415; https://classic.clinicaltrials.gov/ct2/show/NCT05238415. International Registered Report Identifier (IRRID): RR2-10.1186/s12879-022-07584-z

Background: Because the clinical patterns and symptoms that persist after a COVID-19 infection are diverse, a diagnosis of post-acute COVID-19 syndrome (PACS) is difficult to implement. The current research project therefore aims to evaluate the feasibility and the practicability of a comprehensive, interdisciplinary, and cross-sectoral treatment program consisting of a low-threshold online screening and holistic assessment for PACS. Furthermore, it aims to evaluate digital interventions and the use of so-called personal guides that may help to facilitate the recovery of PACS.Methods: This German study consists of a low-threshold online screening for PACS where positively screened participants will be supported throughout by personal pilots. The personal pilots are aimed at empowering patients and helping them to navigate through the study and different treatment options. Patients will then be randomly assigned either to an intervention group (IG) or an active control group (ACG). The IG will receive a comprehensive assessment of physiological and psychological functioning to inform future treatment. The ACG does not receive the assessment but both groups will receive a treatment consisting of an individual digital treatment program (digital intervention platform and an intervention via a chatbot). This digital intervention is based on the needs identified during the assessment for participants in the IG. Compared to that, the ACG will receive a more common digital treatment program aiming to reduce PACS symptoms. Importantly, a third comparison group (CompG) will be recruited that does not receive any treatment. A propensity score matching will take place, ensuring comparability between the participants. Primary endpoints of the study are symptom reduction and return to work. Secondary outcomes comprise, for example, social participation and activities in daily life. Furthermore, the feasibility and applicability of the online screening tool, the holistic assessment, digital trainings, and personal pilots will be evaluated.Discussion: This is one of the first large-scale studies to improve the diagnosis and the care of patients with PACS by means of empowerment. It is to be evaluated whether the methods utilized can be used for the German and international population.Trial registrationClinicalTrials.gov Identifier: NCT05238415; date of registration: February 14, 2022

Background: During the COVID-19 pandemic, hygiene behaviors such as keeping distance, avoiding masses, wearing face masks, and complying with hand hygiene recommendations became imperative. The current study aims to determine factors interrelating with hygiene behaviors. Methods: A total of 4049 individuals (1305 male, 2709 female, aged 18–80 years) were recruited from rehabilitation clinics or freely on the internet. They were surveyed via online questionnaires between May 2020 and August 2021. Sociodemographics, hygiene behaviors, and fear of COVID-19 infection were assessed. Results: Overall prevalence for hygiene behaviors was: keeping a distance—88.1%; avoiding mass gatherings—88.0%; wearing face masks—96.9%; and hand hygiene—81.6%, with 70% of the study participants complying with all four researched behaviors. Hygiene behaviors were significantly related to fear in a linear and quadratic fashion. Conclusion: Patients are more compliant according to their self-reported responses than the general population. To improve hygiene behavior, hand hygiene in particular provides options for improvements. A medium level of fear seems to be more functional than too-elevated fear. Behavioral interventions and targeted communication aiming at improving different behaviors in orchestration can help individuals to protect their health and to remain healthy. Accordingly, communication is required to ensure high hygiene standards and patient safety, and to prevent adverse effects.