Evidence map›Paper›PMID 28739561›Full record

SynthesisJournal of medical Internet research2017

Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review.

Ezgi Dogan, Christian Sander, Xenija Wagner, Ulrich Hegerl, Elisabeth Kohls

Registry-linked trialOpen access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05810636 (Hyperactivity Assessment in Children With Attention-deficit Hyperactivity Disorder), which is not on this map. Cited by 79 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 6 pooled it
19.3field-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.

NCT05810636 enrolling by invitationnot on this mapstarted 2022, after this paper: background citation

Hyperactivity Assessment in Children With Attention-deficit Hyperactivity Disorder

Typeobservational_patient_registrySponsorNational Taiwan University HospitalRan2022 to 2026Enrolled200ConditionsAttention Deficit Disorder With HyperactivityArmsGarmin Vivosmart wearable device
3 · Its place in the literature

Who cites it

79 citing papers in PubMed, 6 syntheses or guidelines pooled it, 193 citations in OpenAlex.

  1. Pooled it
  2. A Systematic Review of Location Data for Depression Prediction.International journal of environmental research and public health · 2023
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. An exploration of actigraphy in the context of ketamine and treatment-resistant depression.International journal of methods in psychiatric research · 2023
    Article
  20. Article

19 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

5 authors at 2 institutions in 1 country.

Ezgi DoganMedical Faculty, Department of Psychiatry and Psychotherapy, University Leipzig, Leipzig, Germany.ORCID 0000-0003-0148-2163
Christian SanderMedical Faculty, Department of Psychiatry and Psychotherapy, University Leipzig, Leipzig, Germany.ORCID 0000-0002-5402-6631
Xenija WagnerMedical Faculty, Department of Psychiatry and Psychotherapy, University Leipzig, Leipzig, Germany.ORCID 0000-0002-5971-5196
Ulrich HegerlMedical Faculty, Department of Psychiatry and Psychotherapy, University Leipzig, Leipzig, Germany.ORCID 0000-0002-3039-7470
Elisabeth KohlsMedical Faculty, Department of Psychiatry and Psychotherapy, University Leipzig, Leipzig, Germany.ORCID 0000-0001-9093-6547
Leipzig University · DEEuropean Alliance Against Depression · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic mental health interventions for mood disorders have increased rapidly over the past decade, most recently in the form of various systems and apps that are delivered via smartphones.

objectiveWe aim to provide an overview of studies on smartphone-based systems that combine subjective ratings with objectively measured data for longitudinal monitoring of patients with affective disorders. Specifically, we aim to examine current knowledge on: (1) the feasibility of, and adherence to, such systems; (2) the association of monitored data with mood status; and (3) the effects of monitoring on clinical outcomes.

methodsWe systematically searched PubMed, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials for relevant articles published in the last ten years (2007-2017) by applying Boolean search operators with an iterative combination of search terms, which was conducted in February 2017. Additional articles were identified via pearling, author correspondence, selected reference lists, and trial protocols.

resultsA total of 3463 unique records were identified. Twenty-nine studies met the inclusion criteria and were included in the review. The majority of articles represented feasibility studies (n=27); two articles reported results from one randomized controlled trial (RCT). In total, six different self-monitoring systems for affective disorders that used subjective mood ratings and objective measurements were included. These objective parameters included physiological data (heart rate variability), behavioral data (phone usage, physical activity, voice features), and context/environmental information (light exposure and location). The included articles contained results regarding feasibility of such systems in affective disorders, showed reasonable accuracy in predicting mood status and mood fluctuations based on the objectively monitored data, and reported observations about the impact of monitoring on clinical state and adherence of patients to the system usage.

conclusionsThe included observational studies and RCT substantiate the value of smartphone-based approaches for gathering long-term objective data (aside from self-ratings to monitor clinical symptoms) to predict changes in clinical states, and to investigate causal inferences about state changes in patients with affective disorders. Although promising, a much larger evidence-base is necessary to fully assess the potential and the risks of these approaches. Methodological limitations of the available studies (eg, small sample sizes, variations in the number of observations or monitoring duration, lack of RCT, and heterogeneity of methods) restrict the interpretability of the results. However, a number of study protocols stated ambitions to expand and intensify research in this emerging and promising field.

Indexed as

FemaleHumansMaleMood DisordersSmartphoneecological momentary assessmentmood disordersreviewsmartphone

Identifiers

PMID28739561
PMCPMC5547249
OpenAlexW2737034073

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.