Evidence map›Paper›PMID 32138381›Full record

ArticleInternational journal of environmental research and public health2020

Measuring Mental Effort for Creating Mobile Data Collection Applications.

Johannes Schobel, Thomas Probst, Manfred Reichert, Winfried Schlee, Marc Schickler, Hans A Kestler, Rüdiger Pryss

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 4 institutions in 2 countries.

Johannes SchobelInstitute of Medical Systems Biology, Ulm University, 89069 Ulm, Germany.ORCID 0000-0002-6874-9478
Thomas ProbstDepartment for Psychotherapy and Biopsychosocial Health, Danube University Krems, 3500 Krems, Austria.ORCID 0000-0002-6113-2133
Manfred ReichertInstitute of Databases and Information Systems, Ulm University, 89069 Ulm, Germany.
Winfried SchleeDepartment of Psychiatry and Psychotherapy, University of Regensburg, 93053 Regensburg, Germany.
Marc SchicklerInstitute of Databases and Information Systems, Ulm University, 89069 Ulm, Germany.
Hans A KestlerInstitute of Medical Systems Biology, Ulm University, 89069 Ulm, Germany.ORCID 0000-0002-4759-5254
Rüdiger PryssInstitute of Clinical Epidemiology and Biometry, University of Würzburg, 97070 Würzburg, Germany.
Universität Ulm · DEUniversität für Weiterbildung Krems · ATUniversity of Regensburg · DEUniversity of Würzburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with N = 80 participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials.

Indexed as

Mobile ApplicationsTelemedicineText MessagingChildCognitionData CollectionFemaleHumansMaleSelf Reportdata collectionend-user programmingmental effortsmart mobile devicesusability study

Identifiers

PMID32138381
PMCPMC7084515
OpenAlexW3010109773

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.