Evidence map›Paper›PMID 35675116›Full record

ArticleJMIR formative research2022

Sociodemographic Characteristics Associated With an eHealth System Designed to Reduce Depressive Symptoms Among Patients With Breast or Prostate Cancer: Prospective Study.

Nuhamin Gebrewold Petros, Gergo Hadlaczky, Sara Carletto, Sergio Gonzalez Martinez, Luca Ostacoli, Manuel Ottaviano, Björn Meyer, Enzo Pasquale Scilingo, Vladimir Carli

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. 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

9 authors at 5 institutions in 4 countries.

Nuhamin Gebrewold PetrosNational Centre for Suicide Research and Prevention of Mental Ill-Health, Department of Learning, Informatics, Ethics and Management, Karolinska Institute, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-9738-2222
Gergo HadlaczkyNational Centre for Suicide Research and Prevention of Mental Ill-Health, Department of Learning, Informatics, Ethics and Management, Karolinska Institute, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-0556-6244
Sara CarlettoDepartment of Neuroscience "Rita Levi Montalcini", Università degli Studi di Torino, Turin, Italy.ORCID https://orcid.org/0000-0002-4951-7479
Sergio Gonzalez MartinezLife Supporting Technologies, Universidad Politecnica de Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0003-1256-6389
Luca OstacoliDepartment of Clinical and Biological Sciences, Universita degli studi di Torino, Turin, Italy.ORCID https://orcid.org/0000-0002-6874-1396
Manuel OttavianoLife Supporting Technologies, Universidad Politecnica de Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0003-0002-4988
Björn MeyerGAIA AG, Hamburg, Germany.ORCID https://orcid.org/0000-0003-1100-0260
Enzo Pasquale ScilingoResearch Center, School of Engineering, University of Pisa, Pisa, Italy.ORCID https://orcid.org/0000-0003-2588-4917
Vladimir CarliNational Centre for Suicide Research and Prevention of Mental Ill-Health, Department of Learning, Informatics, Ethics and Management, Karolinska Institute, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-6922-0675
Karolinska Institutet · SEUniversidad Politécnica de Madrid · ESUniversity of Turin · ITGAIA (Germany) · DEUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundeHealth interventions have become a topic of interest in the field of mental health owing to their increased coordination and integration of different elements of care, in treating and preventing mental ill health in patients with somatic illnesses. However, poor usability, learnability, and user engagement might affect the effectiveness of an eHealth intervention. Identifying different sociodemographic characteristics that might be associated with higher perceived usability can help improve the usability of eHealth interventions.

objectiveThis study aimed to identify the sociodemographic characteristics that might be associated with the perceived usability of the NEVERMIND (Neurobehavioural Predictive and Personalised Modelling of Depressive Symptoms During Primary Somatic Diseases) eHealth system, comprising a mobile app and a sensorized shirt, in reducing comorbid depressive symptoms in patients with breast or prostate cancer.

methodsThe study included a total of 129 patients diagnosed with breast (n=80, 62%) or prostate (n=49, 38%) cancer, who received a fully automated mobile app and sensorized shirt (NEVERMIND system). Sociodemographic data on age, sex, marital status, education level, and employment status were collected at baseline. Usability outcomes included the System Usability Scale (SUS), a subjective measure that covers different aspects of system usability; the user version of the Mobile App Rating Scale (uMARS), a user experience questionnaire; and a usage index, an indicator calculated from the number of days patients used the NEVERMIND system during the study period.

resultsThe analysis was based on 108 patients (n=68, 63%, patients with breast cancer and n=40, 37%, patients with prostate cancer) who used the NEVERMIND system for an average of 12 weeks and completed the study. The overall mean SUS score at 12 weeks was 73.4 (SD 12.5), which indicates that the NEVERMIND system has good usability, with no statistical differences among different sociodemographic characteristics. The global uMARS score was 3.8 (SD 0.3), and women rated the app higher than men (β=.16; P=.03, 95% CI 0.02-0.3), after adjusting for other covariates. No other sociodemographic characteristics were associated with higher uMARS scores. There was a statistical difference in the use of the NEVERMIND system between women and men. Women had significantly lower use (β=-0.13; P=.04, 95% CI -0.25 to -0.01), after adjusting for other covariates.

conclusionsThe findings suggest that the NEVERMIND system has good usability according to the SUS and uMARS scores. There was a higher favorability of mobile apps among women than among men. However, men had significantly higher use of the NEVERMIND system. Despite the small sample size and low variability, there is an indication that the NEVERMIND system does not suffer from the digital divide, where certain sociodemographic characteristics are more associated with higher usability.

trial registrationGerman Clinical Trials Register RKS00013391; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00013391.

Indexed as

breast cancerdepressioneHealthmental healthNeurobehavioural Predictive and Personalised Modelling of Depressive Symptoms During Primary Somatic DiseasesNEVERMIND systemprostate cancerSUSSystem Usability Scalethe user version of the Mobile App Rating ScaleuMARSusability

Identifiers

PMID35675116
PMCPMC9311385
OpenAlexW4240838103

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.