Evidence map›Paper›PMID 40269123›Full record

ArticleScientific reports2025

The science behind the lifesum app: an intervention design analysis.

Signe Svanfeldt, Chris Seth, Marcus Gners, Andreas Blomqvist

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Signe SvanfeldtLifesum AB, Repslagargatan 17B, Stockholm, 118 46, Sweden.
Chris SethLifesum AB, Repslagargatan 17B, Stockholm, 118 46, Sweden.
Marcus GnersLifesum AB, Repslagargatan 17B, Stockholm, 118 46, Sweden.
Andreas BlomqvistDepartment of Health, Medicine and Caring Sciences, Linköping University, Linköping, 58183, Sweden. andreas.blomqvist@liu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wellness is an increasingly important part of public health and can prevent both disease and death. Diet and nutrition are important factors that contribute to wellness and predict health outcomes. Adhering to healthy diets is notoriously difficult for many, and some support is often required. Increasingly, that support may be found in the shape of an app in a smartphone. One such app is Lifesum, with some 65 million users worldwide. Lifesum adopts a more holistic approach to nutrition and well-being, and adopted an evidence-based approach to its development. The aim of this study was to describe the scientific, theoretical basis for the Lifesum app and contribute to advancing science in the field of wellness app development. This was an intervention design analysis, designed to describe the theoretical model and intervention theory used to create the Lifesum app in its current embodiment. A pragmatic theoretical model describing behaviour change in the context of healthy eating was devised based on findings in literature. Factors that drive unhealthy eating behaviours, but that were malleable and whose mechanisms of change were feasible to implement, were identified and used to form an intervention theory. The theoretical model and the intervention theory could then guide the implementation of the Lifesum app, illustrated by a logic model. The theoretical model emphasizes personal goal-attainment and motivation as keys to establishing and maintaining healthy eating behaviours, with proximal outcomes being nutrition knowledge, mindfulness about eating and macro-nutrient balance. Nutrition knowledge is achieved through the provision of nutrition information from a vast database on food items, easily available. Continuous feedback on food choices made will enhance this knowledge and a greater awareness of the impact of nutrition on health remains desirable. A more mindful disposition regarding foods is achieved through support in terms of tracking food intake continuously, as well as recommending meals or recipes. After collecting user preferences on health status, biometrics and goals, these meal plans and recipes can be made to offer the optimal macro-nutrient distribution for each individual user. A theoretical model for diet-related behavior change was developed and key dietary issues were identified, outlining mechanisms for positive impact. These insights informed a mechanistic description of the Lifesum app, providing a foundation for future research on intervention outcomes.

Indexed as

Diet, HealthyHealth PromotionMobile ApplicationsFeeding BehaviorHealth BehaviorHumansModels, TheoreticalSmartphoneAppBehaviour changeHealthy eatingIntervention developmentMacro-nutrient balanceWellness

Identifiers

PMID40269123
PMCPMC12019602

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.