Evidence map›Paper›PMID 33135120›Full record

ArticleInternational journal of bipolar disorders2020

Smartphone-based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals.

Sharleny Stanislaus, Maj Vinberg, Sigurd Melbye, Mads Frost, Jonas Busk, Jakob E Bardram, Lars Vedel Kessing, Maria Faurholt-Jepsen

Registry-linked trialAbstract read
In one paragraph

Article in International journal of bipolar disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02888262 (The Bipolar Illness Onset Study), which is not on this map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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.

NCT02888262 active not recruitingnot on this map

The Bipolar Illness Onset Study (the BIO Study)

TypeobservationalSponsorMental Health Centre Copenhagen, Bispebjerg and Frederiksberg HospitalRan2016 to 2026Enrolled700ConditionsBipolar Disorder
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 2 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

8 authors.

Sharleny StanislausThe Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Department O, 6243, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark. sharleny.stanislaus.01@regionh.dk.ORCID http://orcid.org/0000-0003-1073-6436
Maj VinbergThe Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Department O, 6243, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
Sigurd MelbyeThe Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Department O, 6243, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
Mads FrostMonsenso ApS, Langelinie Allé 47, Copenhagen, Denmark.
Jonas BuskCopenhagen Center for Health Technology (CACHET), Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Jakob E BardramCopenhagen Center for Health Technology (CACHET), Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Lars Vedel KessingThe Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Department O, 6243, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
Maria Faurholt-JepsenThe Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Department O, 6243, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.

Funding

Augustinus Fonden (DK) 16-0083Gangstedfonden (DK) A29594Helsefonden (DK) 16-B-0063Innovationsfonden (DK) 5164-00001BLundbeckfonden (DK) R215-2015-4121Markedsmodningsfonden (DK) 2015-310Sundhed og Sygdom, Det Frie Forskningsråd (DK) DFF - 4183-00570
6 · The paper itself

Abstract

backgroundIn DSM-5 activity is a core criterion for diagnosing hypomania and mania. However, there are no guidelines for quantifying changes in activity. The objectives of the study were (1) to investigate daily smartphone-based self-reported and automatically-generated activity, respectively, against validated measurements of activity; (2) to validate daily smartphone-based self-reported activity and automatically-generated activity against each other; (3) to investigate differences in daily self-reported and automatically-generated smartphone-based activity between patients with bipolar disorder (BD), unaffected relatives (UR) and healthy control individuals (HC).

methodsA total of 203 patients with BD, 54 UR, and 109 HC were included. On a smartphone-based app, the participants daily reported their activity level on a scale from -3 to + 3. Additionally, participants owning an android smartphone provided automatically-generated data, including step counts, screen on/off logs, and call- and text-logs. Smartphone-based activity was validated against an activity questionnaire the International Physical Activity Questionnaire (IPAQ) and activity items on observer-based rating scales of depression using the Hamilton Depression Rating scale (HAMD), mania using Young Mania Rating scale (YMRS) and functioning using the Functional Assessment Short Test (FAST). In these analyses, we calculated averages of smartphone-based activity measurements reported in the period corresponding to the days assessed by the questionnaires and rating scales.

results(1) Smartphone-based self-reported activity was a valid measure according to scores on the IPAQ and activity items on the HAMD and YMRS, and was associated with FAST scores, whereas the majority of automatically-generated smartphone-based activity measurements were not. (2) Daily smartphone-based self-reported and automatically-generated activity correlated with each other with nearly all measurements. (3) Patients with BD had decreased daily self-reported activity compared with HC. Patients with BD had decreased physical (number of steps) and social activity (more missed calls) but a longer call duration compared with HC. UR also had decreased physical activity compared with HC but did not differ on daily self-reported activity or social activity.

conclusionDaily self-reported activity measured via smartphone represents overall activity and correlates with measurements of automatically generated smartphone-based activity. Detecting activity levels using smartphones may be clinically helpful in diagnosis and illness monitoring in patients with bipolar disorder. Trial registration clinicaltrials.gov NCT02888262.

Indexed as

ActivityBipolar disorderElectronic monitoringRemote monitoringSmartphone

Identifiers

PMID33135120
PMCPMC7604277

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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.