Evidence map›Paper›PMID 23563184›Full record

Trial reportJournal of medical Internet research2013

A comparison of two delivery modalities of a mobile phone-based assessment for serious mental illness: native smartphone application vs text-messaging only implementations.

John Ainsworth, Jasper E Palmier-Claus, Matthew Machin, Christine Barrowclough, Graham Dunn, Anne Rogers, Iain Buchan, Emma Barkus, Shitij Kapur, Til Wykes and 2 more

Open access · goldAbstract readComparative StudyRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 8 pooled it
12.9field-weighted citation impact, top 1% of its field
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

76 citing papers in PubMed, 8 syntheses or guidelines pooled it, 168 citations in OpenAlex.

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16 more citing papers are in PubMed but not listed here.

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

12 authors at 6 institutions in 3 countries.

John AinsworthNIBHI Manchester Health e-Research Centre, Institue of Population Health, University of Manchester, Manchester, UK. John.Ainsworth@manchester.ac.uk
Jasper E Palmier-Claus
Matthew Machin
Christine Barrowclough
Graham Dunn
Anne Rogers
Iain Buchan
Emma Barkus
Shitij Kapur
Til Wykes
Richard S Hopkins
Shôn Lewis
University of Manchester · GBKing's College - North Carolina · USManchester Academic Health Science Centre · GBNIHR Manchester Biomedical Research Centre · GBUniversity of Southampton · GBUniversity of Wollongong · AU

Funding

Medical Research Council G0701748Medical Research Council MC_PC_13042Medical Research Council MR/K006665/1
6 · The paper itself

Abstract

backgroundMobile phone-based assessment may represent a cost-effective and clinically effective method of monitoring psychotic symptoms in real-time. There are several software options, including the use of native smartphone applications and text messages (short message service, SMS). Little is known about the strengths and limitations of these two approaches in monitoring symptoms in individuals with serious mental illness.

objectiveThe objective of this study was to compare two different delivery modalities of the same diagnostic assessment for individuals with non-affective psychosis-a native smartphone application employing a graphical, touch user interface against an SMS text-only implementation. The overall hypothesis of the study was that patient participants with sewrious mental illness would find both delivery modalities feasible and acceptable to use, measured by the quantitative post-assessment feedback questionnaire scores, the number of data points completed, and the time taken to complete the assessment. It was also predicted that a native smartphone application would (1) yield a greater number of data points, (2) take less time, and (3) be more positively appraised by patient participant users than the text-based system.

methodsA randomized repeated measures crossover design was employed. Participants with currently treated Diagnostic and Statistical Manual (Fourth Edition) schizophrenia or related disorders (n=24) were randomly allocated to completing 6 days of assessment (four sets of questions per day) with a native smartphone application or the SMS text-only implementation. There was then a 1-week break before completing a further 6 days with the alternative delivery modality. Quantitative feedback questionnaires were administered at the end of each period of sampling.

resultsA greater proportion of data points were completed with the native smartphone application in comparison to the SMS text-only implementation (β = -.25, SE=.11, P=.02), which also took significantly less time to complete (β =.78, SE= .09, P<.001). Although there were no significant differences in participants' quantitative feedback for the two delivery modalities, most participants reported preferring the native smartphone application (67%; n=16) and found it easier to use (71%; n=16). 33% of participants reported that they would be willing to complete mobile phone assessment for 5 weeks or longer.

conclusionsNative smartphone applications and SMS text are both valuable methods of delivering real-time assessment in individuals with schizophrenia. However, a more streamlined graphical user interface may lead to better compliance and shorter entry times. Further research is needed to test the efficacy of this technology within clinical services, to assess validity over longer periods of time and when delivered on patients' own phones.

Indexed as

Cell PhoneText MessagingCross-Over StudiesHumansPatient CompliancePsychotic DisordersSchizophreniaSurveys and QuestionnairesTelemedicine

Identifiers

PMID23563184
PMCPMC3636800
OpenAlexW2096358051

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.