Evidence map›Paper›PMID 41996600›Full record

ReviewInteractive journal of medical research2026

Mapping Digital Nudges and Recommender Systems for Obesity Prevention: Scoping Review.

Sarah Forberger, Lucia A Reisch, Pieter Van Gorp, Christoph Stahl, Lara Christianson, Jihan Halimi, Karina Karolina De Santis, Chungwan Lo, Cassandra A Omane, Alejandra Loyola-Leyva and 3 more

Abstract readReview
In one paragraph

Review in Interactive journal of medical research, 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

13 authors.

Sarah ForbergerLeibniz Science Campus Digital Public Health (LSC DiPH), Bremen, Germany.ORCID http://orcid.org/0000-0002-7169-675X
Lucia A ReischEl-Erian Institute for Behavioural Economics and Policy, Cambridge Judge Business School, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0002-5731-4209
Pieter Van GorpEindhoven University of Technology, Eindhoven, The Netherlands.ORCID http://orcid.org/0000-0001-5197-3986
Christoph StahlLuxembourg Institute of Science and Technology, Belvaux, Luxembourg.ORCID http://orcid.org/0000-0001-9489-2385
Lara ChristiansonLeibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen, 28359, Germany, 49 42121856907, 49 42121856941.ORCID http://orcid.org/0000-0002-7780-255X
Jihan HalimiAgro-Food Research and Tecnological Center of Aragon (CITA), Zaragoza, Spain.ORCID http://orcid.org/0009-0006-8476-2513
Karina Karolina De SantisLeibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen, 28359, Germany, 49 42121856907, 49 42121856941.ORCID http://orcid.org/0000-0001-7647-6767
Chungwan LoLeibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen, 28359, Germany, 49 42121856907, 49 42121856941.ORCID http://orcid.org/0000-0003-2048-9352
Cassandra A OmaneLeibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen, 28359, Germany, 49 42121856907, 49 42121856941.ORCID http://orcid.org/0009-0002-7693-323X
Alejandra Loyola-LeyvaLuxembourg Institute of Health, Strassen, Luxembourg.ORCID http://orcid.org/0000-0002-0355-803X
Laurent MalisouxLuxembourg Institute of Health, Strassen, Luxembourg.ORCID http://orcid.org/0000-0002-6601-5630
Tiziana de-MagistrisAgro-Food Research and Tecnological Center of Aragon (CITA), Zaragoza, Spain.ORCID http://orcid.org/0000-0001-5480-183X
Torsten BohnLuxembourg Institute of Health, Strassen, Luxembourg.ORCID http://orcid.org/0000-0002-7825-0697

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recommender systems are pivotal in organizing information to enhance noticeability, reduce overload, and streamline decision-making. They can be even more effective if combined with digital nudges. Digital nudging is a subtle approach that combines design, information, and interaction elements to create a choice architecture that can guide user behavior in digital environments. While promising in many fields, there is a notable gap in health promotion, particularly because digital nudges and recommender systems can encourage and support sustained healthier choices in nutrition, physical activity (PA), and sedentary behavior reduction to prevent overweight and obesity. Objective: This scoping review addresses these gaps by exploring how digital nudges and recommender systems are used in obesity prevention. Methods: We prospectively published the scoping review protocol and adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Eligibility was defined using the PCC (Population, Concept, Context) framework. We searched 7 bibliographic databases (MEDLINE and PsycINFO via Ovid, Web of Science, CINAHL via EBSCO, Scopus, ACM Digital Library, and IEEE Xplore) up to October 2023. Following a 2-stage screening by independent reviewers, we selected 68 articles that included 94 user evaluations. Results: Most articles (36/68, 53%) report on recommender systems focused on nutrition, with fewer (16/68, 23%) aiming to promote PA. Most studies on digital nudges (11/68, 16%) targeted nutrition-related nudges for shopping and meal selection (8/68, 2%). Articles address PA and sedentary behavior less frequently (3/68, 4%). Three out of 68 (4%) articles report on recommender systems in combination with games, and 2 out of 68 (3%) articles report on recommender systems and digital nudges. Approaches to item retrieval vary widely, with 31 out of 68 (46%) articles failing to describe their methods. In the scoping review, we found a discrepancy between the target group for which the system was developed and the group with which the evaluation was conducted. Sixty-eight evaluations report positive results, while 26 studies report mixed, negative, or no-difference results. Conclusions: Integrating digital nudges and recommender systems might hold potential in overweight and obesity prevention by subtly encouraging healthier lifestyle choices. However, the heterogeneity in study designs, outcome measures, and reporting quality limits the comparability of findings and makes it difficult to draw robust conclusions about effectiveness. Future work should include detailed definitions, mechanism descriptions, broader geographic representation, and rigorous intervention testing and user evaluations to fully leverage these systems for improved health outcomes and to support sustainability and well-being objectives.

Indexed as

digital healthdigital interventiondigital nudgeslifestyleobesity preventionphysical activityrecommender systemssedentary behavior

Identifiers

PMID41996600
PMCPMC13089671

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.