Skip to content

Testing the acceptance and effectiveness of an mHealth-supported patient-centered treatment approach for patients with heart failure

Testing the acceptance and effectiveness of an mHealth-supported patient-centered treatment approach for patients with heart failure - GÖ-MD14

Status
Recruiting
Phases
Phase 2
Study type
Interventional
Source
DRKS
Registry ID
DRKS00033140
Enrollment
90
Registered
2023-12-05
Start date
2025-01-27
Completion date
Unknown
Last updated
2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

I50

Interventions

Group 1: Patients in treatment group 1 (n=30) receive support from different mHealth components and care management over a period of three months in addition to the usual treatment from their speciali

Sponsors

Universitätsmedizin Göttingen
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: - Consent to data collection - Willingness to use a smartphone provided by us as part of the study - Diagnosed heart failure with NYHA class II-III

Exclusion criteria

Exclusion criteria: - very severe heart failure (NYHA class IV) - severe mental disorders (e.g. acute psychosis, bipolar disorder or existing addictions, except nicotine) - Communication barriers (e.g. insufficient knowledge of German to use the app, blindness, deafness)

Design outcomes

Primary

MeasureTime frame
The main objective of the study is to demonstrate sufficient acceptance of a randomized trial of a blended collaborative care intervention supplemented by the use of apps and sensor data in general as well as the acceptance of this intervention itself. Two primary endpoints will be investigated. 1. To examine the willingness of the patients approached to be randomized in our study. To this end, the reasons for non-participation will be documented. This allows us to check whether non-participation is more due to the intervention itself or the study design. In addition, some demographic and clinical characteristics of the patients are collected; this makes it possible to examine whether the RCT population is representative of the routine population. For statistical planning (case number planning), it is assumed that 20% of the screened patients are willing to participate in the study. 2. We want to show that the proportion p of patients who complete the intervention (applies only to groups 1 and 2) is not too low, whereby we define too low acceptance as a maximum 50% completion rate (non-dropout). For this purpose, the following null hypothesis, which states that acceptance is too low, is tested one-sidedly using a tested one-sidedly at a significance level of 2.5% using a binomial model, in each case for Group 1 and Group 2. ?0: ? = 0.5. ?1: ? > 0.5.

Secondary

MeasureTime frame
- Effects of the intervention on quality of life, the improvement of health behavior and the reduction of psychological stress (recorded via questionnaires and the mHealth components) - Patient satisfaction with healthcare overall and with the intervention (recorded via a questionnaire) - Feasibility of an app recommendation algorithm

Countries

Germany

Contacts

Public ContactChristoph Herrmann-Lingen

Universitätsmedizin Göttingen - Klinik für Psychosomatische Medizin und Psychotherapie

cherrma@gwdg.de+49 551 3964901

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026