Evidence map›Paper›PMID 40604855›Full record

ArticleBMC medicine2025

A scoping review of outcome selection and accuracy of conclusions in complex digital health interventions for young people (2017-2023): methodological proposals for population health intervention research.

Claire Collin, Clara Eyraud, Philippe Martin, Morgane Michel, Enora Le Roux, Corinne Alberti

Abstract readScoping Review
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
–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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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

6 authors.

Claire CollinUniversité Paris Cité, Inserm, ECEVE, Paris, F-75010, France. ccollin.contact@gmail.com.ORCID http://orcid.org/0000-0002-7219-9085
Clara EyraudUniversité Paris Cité, Inserm, ECEVE, Paris, F-75010, France.ORCID http://orcid.org/0000-0001-9914-6488
Philippe MartinUniversité Paris Cité, Inserm, ECEVE, Paris, F-75010, France.ORCID http://orcid.org/0000-0002-3249-5840
Morgane MichelUniversité Paris Cité, Inserm, ECEVE, Paris, F-75010, France.ORCID http://orcid.org/0000-0001-6090-8211
Enora Le RouxUniversité Paris Cité, Inserm, ECEVE, Paris, F-75010, France.ORCID http://orcid.org/0000-0002-2238-7133
Corinne AlbertiUniversité Paris Cité, Inserm, ECEVE, Paris, F-75010, France.ORCID http://orcid.org/0000-0002-9336-1395

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDetermining the success of population health interventions often involves assessing multiple, multidimensional outcomes rather than a single one, which presents significant methodological challenges under the evidence-based medicine paradigm. This scoping review examines outcome selection, analysis, and interpretation, and the accuracy of conclusions in complex digital health interventions promoting health among adolescents and young adults (DHI-AYA).

methodsA comprehensive search of PubMed, EMBASE, ClinicalTrials.gov, PsycINFO, and CINAHL identified DHI-AYA implemented between 2017 and 2023. Studies were categorised by methodological choice regarding outcome hierarchical position: unique primary, multiple primary, or non-hierarchised outcomes. Outcomes were further classified into effectiveness, process, or economic categories. The authors' conclusions on intervention success were compared with conclusions drawn by the research team based on the reported outcome analysis strategy. Secondly, four analytical strategies were applied to a subset of selected interventions to illustrate the impact of outcome hierarchical position and number on conclusions about intervention success.

resultsAnalysis of 100 studies linked to 26 DHI-AYA identified 251 distinct outcomes: 164 effectiveness, 78 process, and 9 economic outcomes. Seven interventions were evaluated using a unique primary outcome, 10 using multiple primary outcomes, and 9 using multiple non-hierarchised outcomes. Primary and secondary outcomes were predominantly effectiveness endpoints. The research team reclassified nine interventions (35%) deemed successful by authors as non-conclusive due to statistically conflicting results across outcomes. Most interventions deemed non-conclusive by the research team were evaluated using non-hierarchised outcomes (7/10, 70%). The choice of outcome analysis strategy substantially affected conclusions on intervention success.

conclusionsDiscrepancies in intervention success assessments highlight the need for enhanced transparency, robustness, and trustworthiness in conclusion-drawing processes. In response, five methodological proposals are formulated: (1) developing core outcome sets specific to population health intervention research (PHIR), (2) collaboratively selecting multidimensional outcomes through a steering committee that accounts for stakeholder preferences and existing theoretical models, (3) exploring multi-criteria decision analysis and consensus-driven methods to transparently combine outcomes, (4) enhancing methodological reporting through intervention development and evaluation to improve scientific integrity and reproducibility, and (5) increasing PHIR expert involvement in ethics, funding, and evaluation committees to improve recognition of evidence produced in this field. PROSPERO REGISTRATION NUMBER: CRD42023401979.

Indexed as

Digital HealthHealth PromotionOutcome Assessment, Health CarePopulation HealthAdolescentHumansResearch DesignYoung AdultInterventionsMethodological researchOutcomesPopulation health intervention researchScoping review

Identifiers

PMID40604855
PMCPMC12224660

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.