Needs and Demands for e-Health Interventions in Patients Attending a Psychosomatic Outpatient Clinic: A Baseline Assessment for a User-Centered Design Approach.

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.

Efficacy of eHealth interventions to reduce depression symptoms in individuals with obesity: a systematic review of randomized controlled trials.

Introduction: Obesity and depression are inter-related health concerns, demanding a high level of treatment and costs in the health care system. The development of eHealth interventions that simultaneously address obesity and mental health can be supportive in this regard. However, evidence of the efficacy of eHealth interventions in the treatment of depression symptoms in individuals with obesity is lacking. The aim of this systematic literature review is to evaluate the efficacy of existing eHealth interventions for individuals with obesity that target depression symptoms. Methods: We systematically searched electronic databases (Cochrane Library, PubMed, Scopus) to identify studies published in English between January 2016 and January 2023, that focused on eHealth interventions, targeting depression symptoms in individuals with obesity people. Exclusion criteria were study objectives that (1) focused specifically on one or more metabolic comorbidities of individuals with obesity, e.g., hypertension, hyperlipidemia, diabetes; (2) focused specifically on eating disorders comorbidities e.g., binge eating disorder, and (3) focused specifically on patients before or after bariatric surgery. Results: The database search identified 214 records. Six articles were included in this review. Sample sizes ranged from 70 to 1267 participants of ages 18-60 years. All included studies were randomized controlled trials. Two of the six included studies were web-based interventions guided either by medical doctors or psychologists. All interventions included video, printed materials, and interactive parts of which two studies integrated elements of Cognitive Behavioural Therapy and Social Cognitive Therapy. The findings showed that eHealth treatment services, supported and guided throughout the intervention had high acceptance and efficacy in the reduction of depression symptoms among individuals with obesity. Conclusion: EHealth interventions that address and target both mental and physical health with interactive strategies calls for better efficacy in the reduction of depression symptoms. Future eHealth interventions that target depression symptoms in individuals with obesity should integrate digital strategies that address both mental and physical health through interactive modules.

An e-mental health intervention to reduce depression symptoms in individuals with obesity: study protocol for the randomized, controlled, two-armed, confirmatory LightMood trial.

BACKGROUND: Patients with obesity often experience psychological distress, specifically depression symptoms. Due to various barriers, such as limitations of healthcare offers, digital interventions, for example medical apps, can provide a suitable approach to support affected people. In the envisaged prospective randomized controlled trial, we aim to examine the efficacy of the LightMood intervention. The LightMood intervention is a manualized and user-centered, digital intervention for patients with obesity, with a duration of 4 months, which contains elements of cognitive behavioral therapy and mindfulness-based and skills-based exercises. We expect the LightMood intervention to be superior to treatment as usual (TAU) in terms of reducing depression symptoms. METHODS: The trial incorporates four distinct measurement time points: the baseline assessment, the post-treatment assessment, and 1- and 3-month follow-up assessments. Furthermore, we implemented in-treatment assessments for both groups. Participants will be randomized into two groups (LightMood intervention vs TAU). The aim is to include 128 participants (64 per group) in the study. Inclusion criteria are patients who are obese, at least 18 years old, with a private Internet access, and with adequate digital literacy and show depression symptoms (PHQ ≥ 10). Exclusion criteria are weekly outpatient individual psychotherapy, obesity surgery within the last year or planned within the next 7 months, no private Internet access, and the prescription of a new psychotropic drug within the last 2 weeks. The primary outcome is the post-assessment reduction in depression symptoms. Secondary outcomes will include the improvement in self-efficacy, quality of life, mindfulness, reduction in eating disorder symptoms, and body mass index (BMI). Furthermore, we expect a positive development of depression symptoms throughout the different time points (T1, T2, and T3) in patients with obesity. DISCUSSION: LightMood is an evidence-based, efficient, low-threshold online intervention that aims to reduce depression symptoms in people with obesity. Online interventions could offer a promising alternative to conventional face-to-face therapy. The primary objective of the current study is to add essential insight into the feasibility, efficacy, effectiveness, and acceptance of e-mental health interventions for people with obesity and depression symptoms. TRIAL REGISTRATION: German Clinical Trial Register (DRKS), DRKS00029219. Registered on May 19, 2023.

Needs and Demands for e-Mental Health Interventions in Individuals with Overweight and Obesity: User-Centred Design Approach.

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.

Electronic Patient-Reported Outcome Measures (ePROMs) Improve the Assessment of Underrated Physical and Psychological Symptom Burden among Oncological Inpatients.

For advanced cancer inpatients, the established standard for gathering information about symptom burden involves a daily assessment by nursing staff using validated assessments. In contrast, a systematic assessment of patient-reported outcome measures (PROMs) is required, but it is not yet systematically implemented. We hypothesized that current practice results in underrating the severity of patients' symptom burden. To explore this hypothesis, we have established systematic electronic PROMs (ePROMs) using validated instruments at a major German Comprehensive Cancer Center. In this retrospective, non-interventional study, lasting from September 2021 to February 2022, we analyzed collected data from 230 inpatients. Symptom burden obtained by nursing staff was compared to the data acquired by ePROMs. Differences were detected by performing descriptive analyses, Chi-Square tests, Fisher's exact, Phi-correlation, Wilcoxon tests, and Cohen's r. Our analyses pointed out that pain and anxiety especially were significantly underrated by nursing staff. Nursing staff ranked these symptoms as non-existent, whereas patients stated at least mild symptom burden (pain: meanNRS/epaAC = 0 (no); meanePROM = 1 (mild); p < 0.05; r = 0.46; anxiety: meanepaAC = 0 (no); meanePROM = 1 (mild); p < 0.05; r = 0.48). In conclusion, supplementing routine symptom assessment used daily by nursing staff with the systematic, e-health-enabled acquisition of PROMs may improve the quality of supportive and palliative care.