A Web-Based App for Emotional Management During the COVID-19 Pandemic: Platform Development and Retrospective Analysis of its Use Throughout Two Waves of the Outbreak in Spain
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Abstract
Quarantines and nationwide lockdowns implemented for containing the spread of the COVID-19 pandemic may lead to distress and increase the frequency of anxiety and depression symptoms among the general population. During the nationwide lockdown of the first wave of the COVID-19 outbreak in Spain, we developed and launched a web-based app to promote emotional self-care in the general population and facilitate contact with health care professionals.
Objective
This study aimed to describe a web-based app and analyze its utilization pattern throughout 2 successive waves of the COVID-19 outbreak in Spain.
Methods
Our web-based app targeted all individuals aged 18 years or more and was designed by adapting the contents of a mobile app for adjuvant treatment of posttraumatic stress disorder (ie, the PTSD Coach app) to the general population and the pandemic or lockdown scenario. We retrospectively assessed the utilization pattern of the web-based app using data systematically retrieved from Google Analytics. Data were grouped into 3 time periods, defined using Joinpoint regression analysis of COVID-19 incidence in our area: first wave, between-wave period, and second wave.
Results
The resulting web-based app, named gesioemocional.cat, maintains the navigation structure of the PTSD Coach app, with three main modules: tools for emotional self-care, a self-assessment test, and professional resources for on-demand contact. The self-assessment test combines the Patient Health Questionnaire-2 and the 7-item Generalized Anxiety Disorder scale and offers professional contact in the advent of a high level of depression and anxiety; contact is prioritized in accordance with a screening questionnaire administered at the time of obtaining individual consent to be contacted. The tools for emotional self-care can be accessed either on-demand or symptom-driven. The utilization analysis showed a high number of weekly accesses during the first wave. In this period, press releases regarding critical events of the pandemic progression and government decisions on containment measures were followed by a utilization peak, irrespective of the sense (ie, positive or negative) of the information. Positive information pieces (eg, relaxation of containment measures due to a reduction of COVID-19 cases) resulted in a sharp increase in utilization immediately after information release, followed by a successive decline in utilization. The second wave was characterized by a lower and less responsive utilization of the web-based app.
Conclusions
mHealth tools may help the general population cope with stressful conditions associated with the pandemic scenario. Future studies shall investigate the effectiveness of these tools among the general population—including individuals without diagnosed mental illnesses—and strategies to reach as many people as possible.
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SciScore for 10.1101/2021.08.11.21261793: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:One of the most remarkable consequences of this limitation is the lack of data at a user level, which precludes discriminating between entries of new users and regular access of the same user. More importantly, the lack of historical records of users …
SciScore for 10.1101/2021.08.11.21261793: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:One of the most remarkable consequences of this limitation is the lack of data at a user level, which precludes discriminating between entries of new users and regular access of the same user. More importantly, the lack of historical records of users prevents us from analyzing improvement or worsening of mental health state. Finally, we could not analyse Web App utilization according to socioeconomic status, which has been highlighted as a source of inequality in other aspects associated with access to COVID-19 resources (Amengual-Moreno et al., 2020; Baena-Díez et al., 2020). Nevertheless, while all these limitations compromise analytical approaches of the Web App, the absence of personal questions and no need for signing in are likely to promote the platform use, in line with the overarching goal of the project, which was to help the population during the stressful circumstances of the lockdown.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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