Evidence map›Paper›PMID 31359866›Full record

ReviewJMIR mHealth and uHealth2019

Specialized Smartphone Intervention Apps: Review of 2014 to 2018 NIH Funded Grants.

William B Hansen, Lawrence M Scheier

Registry-linked trialAbstract readComparative StudyReview
PubMed Full text at PMC Publisher
In one paragraph

Review in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07247955 (Effectiveness of the Guided and Traditional Cognitive Behavioral Therapy Protocol in a Patient With Treatment-resistant Panic Disorder), which is not on this map. Cited by 14 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 4 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.

NCT07247955 nacompletednot on this mapstarted 2023, after this paper: background citation

Effectiveness of the Guided and Traditional Cognitive Behavioral Therapy Protocol in a Patient With Treatment-resistant Panic Disorder

TypeinterventionalSponsorUniversidade Federal do Rio de JaneiroRan2023 to 2025Enrolled46ConditionsPanic DisorderArmsThe group intervention used the sessions described in traditional form, The group intervention used the sessions described in a self-guided format using an application
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

2 authors.

William B Hansen *Prevention Strategies, LLC, Brown Summit, NC, United States.ORCID 0000-0002-0970-8000
Lawrence M Scheier *LARS Research Institute, Scottsdale, AZ, United States.ORCID 0000-0003-2254-0123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe widespread adoption of smartphones provides researchers with expanded opportunities for developing, testing and implementing interventions. National Institutes of Health (NIH) funds competitive, investigator-initiated grant applications. Funded grants represent the state of the science and therefore are expected to anticipate the progression of research in the near future.

objectiveThe objective of this paper is to provide an analysis of the kinds of smartphone-based intervention apps funded in NIH research grants during the five-year period between 2014 and 2018.

methodsWe queried NIH Reporter to identify candidate funded grants that addressed mHealth and the use of smartphones. From 1524 potential grants, we identified 397 that met the requisites of including an intervention app. Each grant's abstract was analyzed to understand the focus of intervention. The year of funding, type of activity (eg, R01, R34, and so on) and funding were noted.

resultsWe identified 13 categories of strategies employed in funded smartphone intervention apps. Most grants included either one (35.0%) or two (39.0%) intervention approaches. These included artificial intelligence (57 apps), bionic adaptation (33 apps), cognitive and behavioral therapies (68 apps), contingency management (24 apps), education and information (85 apps), enhanced motivation (50 apps), facilitating, reminding and referring (60 apps), gaming and gamification (52 apps), mindfulness training (18 apps), monitoring and feedback (192 apps), norm setting (7 apps), skills training (85 apps) and social support and social networking (59 apps). The most frequently observed grant types included Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) grants (40.8%) and Research Project Grants (R01s) (26.2%). The number of grants funded increased through the five-year period from 60 in 2014 to 112 in 2018.

conclusionsSmartphone intervention apps are increasingly competitive for NIH funding. They reflect a wide diversity of approaches that have significant potential for use in applied settings.

Indexed as

Artificial IntelligenceBionicsCognitive Behavioral TherapyEducationFinancial ManagementFinancing, OrganizedHumansInformation ManagementMobile ApplicationsNational Institutes of Health (U.S.)Research PersonnelSmall BusinessSmartphoneTechnology TransferTelemedicineUnited Statesfunded grantsinterventionmobile phonesmartphone

Identifiers

PMID31359866
PMCPMC6690163

What OpenQuestion holds

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Registered trials

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.