Enhanced health intelligence for personal behavioral strategies in everyday life - 1st application scenario

Enhanced health intelligence for personal behavioral strategies in everyday life - 1st application scenario - Eghi

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00027551

Enrollment

Registered

2022-05-10

Start date

2022-11-07

Completion date

Unknown

Last updated

2025-10-06

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

Conditions

UEBERGEWICHT E66.0

Interventions

Group 1: Overweight/obese participants of the Bodymed nutrition program - Study duration: 4 weeks + optional follow-up 4 months after study start for an additional 2 weeks. - Additional use of own sm

Eligibility

Sex/Gender

All

Age

18 Years to 59 Years

Inclusion criteria

Inclusion criteria: - BMI = 25.0 kg/m², i.e. overweight or obesity - Regular participation in the Bodymed nutrition program - Presence of own Android smartphone at least version Android 7.

Exclusion criteria

Exclusion criteria: - Eating disorders - Cancer diseases - Diabetic nephropathy or renal insufficiency only after consultation with the specialist physician in charge - Protein utilization disorders (e.g. phenylketonuria) - Cachexia - Decompensated liver cirrhosis - Pregnancy (from the 3rd trimester) - Breastfeeding - Taking the following medications: Amiodarone, tamoxifen, corticosteroid, methotrexate, tetracyclines, valproic acid, Chemotherapy (CASH; 5-FU, taxanes, platinum-containing chemotherapeutic agents)

Design outcomes

Primary

Measure	Time frame
In the 1st application scenario of the study, requierments for successful implementation are first defined. For this: - Acquisition of various behavioral parameters as well as biomarkers via Smartwatch and Smartphone to create a digital twin. --> Derivation of behavioral patterns --> Generation of recommendations for behavioral change - Conducting a semi-structured interview: --> Query affinity and willingness to use technological support options in the context of weight management or behavior modeling in general, and in this context query potential forms of technological support. - In addition, motivation, affinity, comprehensibility, user-friendliness, presentation and meaningfulness of exemplary recommendations for action or personally-adapted behavioral strategies were queried.	—

Measure

Time frame

In the 1st application scenario of the study, requierments for successful implementation are first defined. For this: - Acquisition of various behavioral parameters as well as biomarkers via Smartwatch and Smartphone to create a digital twin. --> Derivation of behavioral patterns --> Generation of recommendations for behavioral change - Conducting a semi-structured interview: --> Query affinity and willingness to use technological support options in the context of weight management or behavior modeling in general, and in this context query potential forms of technological support. - In addition, motivation, affinity, comprehensibility, user-friendliness, presentation and meaningfulness of exemplary recommendations for action or personally-adapted behavioral strategies were queried.

—

Secondary

Measure	Time frame
Long-term and sustainable improvement of health and nutritional behavior through the support in everyday life by the use of digital applications. Successful weight reduction with decrease in fat mass and increase in metabolically active mass (musculature).	—

Countries

Germany

Contacts

Public ContactAgathe Buchheit

Bodymed-Center Ommersheim

a.buchheit@bodymed.com06803 / 981881

Outcome results

None listed

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