Accepted for/Published in: JMIR Research Protocols
Date Submitted: Apr 11, 2020
Date Accepted: Jun 4, 2020
Date Submitted to PubMed: Jun 5, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
COVID-19: Closing the Psychological Treatment Gap during the Pandemic, a Protocol for Implementation and Evaluation of Text4Hope (a Supportive Text Message Program)
ABSTRACT
Background:
Coronavirus disease 2019 (COVID-19) has spread globally with far-reaching, significant and unprecedented impacts on health and way of life. Threats to mental health, psychological safety and well being are now emerging, increasing the impact of this virus on world health. Providing support for these challenges is difficult because of very high numbers of people requiring support in the context of a need to maintain physical distancing. This protocol describes use of text messaging (Text4Hope) as a convenient, cost-effective, and accessible population-level mental health intervention. This program is evidence-based, with prior research supporting good outcomes and high user satisfaction.
Objective:
The project goal is to implement a program of daily supportive text messaging (Text4Hope) to reduce distress related to the COVID-19 crisis initially amongst Canadians. Prevalence of stress, anxiety and depressive symptoms, demographic correlates of the same, and the outcomes of the Text4Hope intervention in mitigating distress will be evaluated.
Methods:
Self-administered, anonymous, online questionnaires will be used to assess stress (Perceived Stress Scale), anxiety (GAD-7), and depressive symptoms (PHQ-9). Data will be collected at baseline (onset of text messaging), at program midpoint (6-weeks), and end (12-weeks).
Results:
Data analysis will include parametric and non-parametric techniques, focussing on primary outcomes (i.e., stress, anxiety, depressive symptoms) and metrics of use, including number of subscribers and user satisfaction. Given the large size of the data set, machine learning and data-mining methods will also be used.
Conclusions:
This COVID-19 project will provide key information regarding prevalence rates of stress, anxiety, and depressive symptoms during the pandemic, demographic correlates of distress, and outcome data related to this scalable population-level intervention. Information from this study will be valuable for practitioners, as useful for informing policy and decision-making regarding psychological interventions during the pandemic. Clinical Trial: Ethics approval has been granted by the University of Alberta Health Research Ethics Board (Pro00086163).
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Copyright
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