Evidence map›Paper›PMID 40018441›Full record

ArticleFrontiers in digital health2025

Evaluating the feasibility of using the Multiphase Optimization Strategy framework to assess implementation strategies for digital mental health applications activations: a proof of concept study.

Ayla Aydin, Wouter van Ballegooijen, Ilja Cornelisz, Anne Etzelmueller

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Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ayla AydinDepartment of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, Netherlands.
Wouter van BallegooijenDepartment of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, Netherlands.
Ilja CorneliszDepartment of Educational and Family Studies, LEARN!, Amsterdam Center for Learning Analytics, Vrije Universiteit, Amsterdam, Netherlands.
Anne EtzelmuellerHelloBetter, GET.ON Institut für Online Gesundheitstrainings GmbH, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Despite the effectiveness and potential of digital mental health interventions (DMHIs) in routine care, their uptake remains low. In Germany, digital mental health applications (DiGA), certified as low-risk medical devices, can be prescribed by healthcare professionals (HCPs) to support the treatment of mental health conditions. The objective of this proof-of-concept study was to evaluate the feasibility of using the Multiphase Optimization Strategy (MOST) framework when assessing implementation strategies. Methods: We tested the feasibility of the MOST by employing a 2 Results: The results primarily demonstrated the feasibility of applying the MOST to a non-randomized setting. Furthermore, analyses indicated significant differences between the groups of HCPs receiving specific implementation strategies [ Discussion and limitations: These findings support the feasibility of using the MOST to evaluate implementation strategies in digital mental health care. It also gives an exploratory example on how to conduct factorial designs with information on implementation strategies. However, limitations such as non-random assignment, underpowered analysis, and varying approaches to HCPs affect the robustness and generalizability of the results. Despite these limitations, the results demonstrate that the MOST is a viable method for assessing implementation strategies, highlighting the importance of planning and optimizing strategies before their implementation. By addressing these limitations, healthcare providers and policymakers can enhance the adoption of digital health innovations, ultimately improving access to mental health care for a broader population.

Indexed as

DiGADigitale Gesundheitsanwendungendigital health applicationshealthcare professionalsimplementation scienceinternet-based interventionsmental healthmultiphase optimization strategy

Identifiers

PMID40018441
PMCPMC11865092

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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.