Accepted for/Published in: JMIR Research Protocols
Date Submitted: May 14, 2020
Date Accepted: Jul 26, 2020
Date Submitted to PubMed: Aug 4, 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Warning: This is an author submission that is not peer-reviewed or edited.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.
Closing the COVID-19 Psychological Treatment Gap for Cancer Patients in Alberta: Protocol for Implementation and Evaluation of Text4Hope-Cancer Care
ABSTRACT
Background:
Cancer diagnoses and treatments are usually engender significant anxiety and depressive symptoms in patients, close relatives, and caregivers. During the COVID-19 pandemic providing psychological support in this context presents additional challenges due to self-isolation, and social or physical distancing measures in place to limit viral spread. This protocol describes use of text messaging (Text4Hope-Cancer Care) 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:
We will implement daily supportive text messaging (Text4Hope-Cancer Care) to reduce anxiety and depression related to cancer diagnosis and treatment in Alberta. Prevalence of anxiety and depressive symptoms, their demographic correlates, and Text4Hope-Cancer Care induced changes in anxiety and depression will be evaluated.
Methods:
Alberta residents with a cancer diagnosis and those dealing with the cancer diagnosis of a loved one can self-subscribe to the Text4Hope-Cancer Care program by texting “CancerCare” to a sort code number. Self-administered, anonymous, online questionnaires will be used to assess anxiety and depressive symptoms using the Hospital Anxiety and Depression Scale (HADS). Data will be collected at onset of clients receiving text messages and at 6 ad endpoints of the programs (i.e., 6- and 12-weeks).
Results:
Data will be analyzed with parametric and non-parametric statistics for primary outcomes (i.e., anxiety and depressive symptoms) and metrics of use, including number of subscribers and user satisfaction. In addition, data-mining and machine learning analysis will focus on determining characteristics of subscribers that predict high levels of symptoms of mental disorders, and may subsequently predict changes in those measures in response to the Text4Hope-Cancer program.
Conclusions:
Text4Hope-Cancer has potential to provide key information regarding prevalence rates of anxiety and depressive symptoms in patients diagnosed or receiving care for cancer and their caregivers. The study will generate demographic correlates of anxiety and depression, and outcome data related to this scalable, population-level intervention. Information from this study will be valuable for healthcare practitioners working in cancer care and will inform policy and decision-making regarding psychological interventions for cancer care.
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