PreprintCited by 28Digital Mental Health InterventionsCOVID-19 and Mental HealthMobile Health and mHealth Applications

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Effect of a Mobile-based Intervention on Mental Health in Frontline Healthcare Workers Against COVID-19: Protocol for a Randomized Controlled Trial

Open access
Serrano-Ripoll, Maria J., Ricci-Cabello, Ignacio, Jiménez, Rafael, Zamanillo-Campos, Rocío, Yañez Juan, Aina M., Bennasar-Veny, Miquel, Sitges, Carolina, Gervilla, Elena, Leiva, Alfonso, García-Campayo, Javier, García-Buades, Maria Esther, García-Toro, Mauro, Pastor Moreno, Guadalupe, Ruiz-Perez, Isabel, Alonso-Coello, Pablo, Llobera Canaves, Joan, Fiol-Deroque, Maria A.·2020·Journal of Advanced Nursing

Preprint — published as 10.1111/jan.14813 · Paper page

Abstract

Aim: To evaluate the impact of a psychoeducational, mobile health intervention based on cognitive behavioural therapy and mindfulness-based approaches on the mental health of healthcare workers at the frontline against COVID-19 in Spain. Design: We will carry out a two-week, individually randomised, parallel group, controlled trial. Participants will be individually randomised to receive the PsyCovidApp intervention or control App intervention. Methods: The PsyCovidApp intervention will include five modules: emotional skills, lifestyle behaviour, work stress and burnout, social support, and practical tools. Healthcare workers having attended COVID-19 patients will be randomized to receive the PsyCovidApp intervention (intervention group) or a control App intervention (control group). A total of 440 healthcare workers will be necessary to assure statistical power. Measures will be collected telephonically by a team of psychologists at baseline and immediately after the two weeks intervention period. Measures will include stress, depression and anxiety (DASS-21 questionnaire – primary endpoint), insomnia (ISI), burnout (MBI-HSS), post-traumatic stress disorder (DTS), and self-efficacy (GSE). The study was funded in May 2020, and was ethically approved in June 2020. Trial participants, outcome assessors and data analysts will be blinded to group allocation. Discussion: Despite the increasing use of mobile health interventions to deliver mental health care, this area of research is still on its infancy. This study will help increase the scientific evidence regarding the effectiveness of this type of intervention on this specific population and context. Impact: Despite the lack of solid evidence about their effectiveness, mobile-based health interventions are already being widely implemented because of their low cost and high scalability. The findings from this study will help health services and organizations to make informed decisions in relation to the development and implementation of this type of interventions, allowing them pondering not only their attractive implementability features, but also empirical data about its benefits. Clinical trial registration: NCT04393818 ( ClinicalTrials.gov identifier)

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Research works printed but not linked: 30

  1. 10.3390/ijerph17176180 · DOI
  2. 10.1590/2237-6089-2020-0081 · DOI
  3. 10.1016/j.psychres.2020.112936 · DOI
  4. 10.1136/bmj.m1211 · DOI · Paper page
  5. 10.1016/j.jad.2020.08.034 · DOI · Paper page
  6. 10.1016/j.psychres.2020.113426 · DOI
  7. 10.1213/ane.0000000000004912 · DOI
  8. 10.3389/fpsyt.2020.00511 · DOI
  9. 10.1037/tra0000802 · DOI
  10. 10.1080/09540261.2020.1750800 · DOI
  11. 10.1371/journal.pone.0152285 · DOI · Paper page
  12. 10.2196/mhealth.4930 · DOI · Paper page
  13. 10.2196/12493 · DOI
  14. 10.2196/mhealth.7088 · DOI · Paper page
  15. 10.2196/14897 · DOI · Paper page
  16. 10.1038/s41746-019-0188-8 · DOI · Paper page
  17. 10.1007/s10597-020-00689-2 · DOI
  18. 10.5694/j.1326-5377.2003.tb05552.x · DOI
  19. 10.1089/tmj.2020.0287 · DOI
  20. 2017, Memo: An mHealth intervention to prevent the onset of depression in adolescents: A double-blind, randomised, placebo-controlled trial, Journal of Child Psychology and Psychiatry, 58, 1014, 10.1111/jcpp.12753 · DOI · Paper page
  21. Bandyopadhyay S , Baticulon RE , Kadhum M , et al. Infection and mortality of healthcare workers worldwide from COVID-19: a scoping review. medRxiv 2020
  22. 2020, Symptoms of posttraumatic stress, anxiety, depression, levels of resilience and burnout in spanish health personnel during the COVID-19 Pandemic, International journal of environmental research and public health, 17, 5514, 10.3390/ijerph17155514 · DOI
  23. 10.7326/0003-4819-158-3-201302050-00583 · DOI · Paper page
  24. 2016, Mental health smartphone apps: review and evidence-based recommendations for future developments, JMIR mental health, 3, e7, 10.2196/mental.4984 · DOI · Paper page
  25. 2005, Psycometric properties of the Spanish version of depression, anxiety and stress scales (DASS), Psicothema, 17, 679
  26. 10.1590/S0034-89102005000100001 · DOI · Paper page
  27. 10.1016/S1389-9457(00)00065-4 · DOI · Paper page
  28. 10.1016/j.comppsych.2014.05.015 · DOI
  29. 10.1080/10447310802205776 · DOI · Paper page
  30. 10.1017/S0033291708004224 · DOI · Paper page

Metadata

Authors
Serrano-Ripoll, M. J., Ricci-Cabello, I., Jiménez, R., Zamanillo-Campos, R., Yañez Juan, A. M., Bennasar-Veny, M., Sitges, C., Gervilla, E., Leiva, A., García-Campayo, J., García-Buades, M. E., García-Toro, M., Pastor Moreno, G., Ruiz-Perez, I., Alonso-Coello, P., Llobera Canaves, J., & Fiol-Deroque, M. A.
Affiliations
  • Health Research Institute of the Balearic Islands (ES)
  • Servei de Salut de les Illes Balears (ES)
Venue
Journal of Advanced Nursing
Publisher
openRxiv
Published
2020-11-06
Volume
77
Issue
6
Pages
2898-2907
ISSN
0309-2402 (ISSN-L)
OpenAlex
W3133785622
Cited by
28
References
1
Citations by year
2026: 2 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 7 · 2021: 7
FWCI
5.11
Type
journal article
Language
en
Open access
Locations
  • Journal of Advanced Nursing (publishedVersion)
  • medRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • RISalud Institutional Health Repository of Andalucía (submittedVersion, other-oa)
  • Docusalut (Conselleria de Salut i Consum del Govern de les Illes Balears) (submittedVersion, cc-by-nc-nd)
  • Hispana (submittedVersion, cc-by-nc-nd)
Funders
Govern de les Illes Balears
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
mobile health intervention, mental health, frontline health workers, COVID-19 pandemic, psychoeducation, cognitive behavioral therapy, mindfulness, burnout, occupational stress, depression, anxiety, post-traumatic stress disorder, insomnia, self-efficacy, social support
MeSH terms
COVID-19, SARS-CoV-2, Health Personnel, Humans, Mental Health, Spain, Randomized Controlled Trials as Topic, Treatment Outcome

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