Evidence map›Paper›PMID 42256459›Full record

ArticleObesity science & practice2026

Does Digital Make a Difference? Willingness-to-Pay for Digital Versus Offline Weight Loss in Germany.

Kevin Helms, Stefan K Lhachimi, Wolf Rogowski, Oliver Lange

Abstract read
In one paragraph

Article in Obesity science & practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kevin HelmsDepartment of Health Care Management Institute for Public Health and Nursing Sciences Health Sciences University of Bremen Bremen Germany.ORCID https://orcid.org/0000-0003-1221-0614
Stefan K LhachimiDepartment of Nursing Management University of Applied Sciences Neubrandenburg Neubrandenburg Germany.ORCID https://orcid.org/0000-0001-8597-0935
Wolf RogowskiDepartment of Health Care Management Institute for Public Health and Nursing Sciences Health Sciences University of Bremen Bremen Germany.ORCID https://orcid.org/0000-0003-1625-4171
Oliver LangeDepartment of Health Care Management Institute for Public Health and Nursing Sciences Health Sciences University of Bremen Bremen Germany.ORCID https://orcid.org/0000-0001-9780-7334

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Germany introduced both digital health applications (DiGA) and an "offline" structured disease management program (DMP) for obesity within statutory health insurance. Given limited resources and ongoing reimbursement decisions, evidence on how individuals with obesity assessed the value of intervention delivery in terms of their willingness to pay (WTP) remained limited. Objective: This study assessed the WTP of individuals with obesity (BMI ≥ 30 kg/m Methods: An online contingent valuation survey was conducted among 424 participants with a BMI ≥ 30 kg/m Results: The mean WTP for the DiGA was €16.15 per month (95% CI: €14.22-€18.09) and was significantly positively associated with older age (€0.24 higher per year, Conclusion: Respondents showed a positive WTP for weight loss interventions, yet at an amount far below DiGA manufacturer prices of approximately €70 per month. The small difference between digital and offline formats suggested that the perceived effectiveness of the intervention had a greater influence on WTP than the format.

Indexed as

contingent valuationdigital public healtheconomic evaluationweight losswillingness‐to‐pay

Identifiers

PMID42256459
PMCPMC13240293

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.