Mental Health Outreach via Supportive Text Messages during the COVID-19 Pandemic: Improved Mental Health and Reduced Suicidal Ideation after Six Weeks in Subscribers of Text4Hope Compared to a Control Population

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Abstract

Background: In March 2020, Alberta Health Services launched Text4Hope, a free mental health text-message service. The service aimed to alleviate pandemic-associated stress, generalized anxiety disorder (GAD), major depressive disorder (MDD), and suicidal propensity. The effectiveness of Text4Hope was evaluated by comparing psychiatric parameters between two subscriber groups. Methods: A comparative cross-sectional study with two arms: Text4Hope subscribers who received daily texts for six weeks, the intervention group (IG); and new Text4Hope subscribers who were yet to receive messages, the control group (CG). Logistic regression models were used in the analysis. Results: Participants in the IG had lower prevalence rates for moderate/high stress (78.8% vs. 88.0%), likely GAD (31.4% vs. 46.5%), and likely MDD (36.8% vs. 52.1%), respectively, compared to respondents in the CG. After controlling for demographic variables, the IG remained less likely to self-report symptoms of moderate/high stress (OR = 0.56; 95% CI = 0.41–0.75), likely GAD (OR = 0.55; 95% CI = 0.44–0.68), and likely MDD (OR = 0.50; 95% CI = 0.47–0.73). The mean Composite Mental Health score, the sum of mean scores on the PSS, GAD-7, and PHQ-9 was 20.9% higher in the CG. Conclusions: Text4Hope is an effective population-level intervention that helps reduce stress, anxiety, depression, and suicidal thoughts during the COVID-19 pandemic. Similar texting services should be implemented during global crises.

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Most cited references 42

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A brief measure for assessing generalized anxiety disorder: the GAD-7.

Robert L Spitzer, Kurt Kroenke, Janet B W Williams … (2006)

Generalized anxiety disorder (GAD) is one of the most common mental disorders; however, there is no brief clinical measure for assessing GAD. The objective of this study was to develop a brief self-report scale to identify probable cases of GAD and evaluate its reliability and validity. A criterion-standard study was performed in 15 primary care clinics in the United States from November 2004 through June 2005. Of a total of 2740 adult patients completing a study questionnaire, 965 patients had a telephone interview with a mental health professional within 1 week. For criterion and construct validity, GAD self-report scale diagnoses were compared with independent diagnoses made by mental health professionals; functional status measures; disability days; and health care use. A 7-item anxiety scale (GAD-7) had good reliability, as well as criterion, construct, factorial, and procedural validity. A cut point was identified that optimized sensitivity (89%) and specificity (82%). Increasing scores on the scale were strongly associated with multiple domains of functional impairment (all 6 Medical Outcomes Study Short-Form General Health Survey scales and disability days). Although GAD and depression symptoms frequently co-occurred, factor analysis confirmed them as distinct dimensions. Moreover, GAD and depression symptoms had differing but independent effects on functional impairment and disability. There was good agreement between self-report and interviewer-administered versions of the scale. The GAD-7 is a valid and efficient tool for screening for GAD and assessing its severity in clinical practice and research.

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The PHQ-9: validity of a brief depression severity measure.

K Kroenke, R L Spitzer, J B Williams (2001)

While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.

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An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

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Author and article information

Contributors

Chang Won Lee: Role: Academic Editor

Journal

Journal ID (nlm-ta): Int J Environ Res Public Health

Journal ID (iso-abbrev): Int J Environ Res Public Health

Journal ID (publisher-id): ijerph

Title: International Journal of Environmental Research and Public Health

Publisher: MDPI

ISSN (Print): 1661-7827

ISSN (Electronic): 1660-4601

Publication date (Electronic): 23 February 2021

Publication date (Print): February 2021

Volume: 18

Issue: 4

Electronic Location Identifier: 2157

Affiliations

[1 ]Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2B7, Canada; rshalaby@ 123456ualberta.ca (R.S.); marianne.hrabok1@ 123456ucalgary.ca (M.H.); jmbrown1@ 123456ualberta.ca (J.M.N.); Daniel.Li@ 123456albertahealthservices.ca (D.L.); cloudbocao@ 123456gmail.com (B.C.); Xinmin@ 123456ualberta.ca (X.-M.L.); rgreiner@ 123456ualberta.ca (R.G.); andy.greenshaw@ 123456ualberta.ca (A.J.G.)

[2 ]Addiction and Mental Health, Alberta Health Services, Edmonton, AB T6G 2B7, Canada; Wesley.Vuong@ 123456albertahealthservices.ca (W.V.); April.Gusnowski@ 123456albertahealthservices.ca (A.G.); Mark.Snaterse@ 123456albertahealthservices.ca (M.S.); shireen.surood@ 123456albertahealthservices.ca (S.S.)

[3 ]Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada

[4 ]Institute of Health Economics, 1200 10405 Jasper Avenue Edmonton, AB T5J 3N4, Canada

[5 ]Strategic Clinical NetworksTM, Provincial Clinical Excellence, Alberta Health Services, Calgary, AB T2P 2M5, Canada; Kelly.Mrklas@ 123456albertahealthservices.ca

[6 ]Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada

[7 ]Department of Computing Science, Faculty of Science, University of Alberta, Edmonton, AB T6G 2B7, Canada

[8 ]Alberta Machine Intelligence Institute, Edmonton, AB T6G 2B7, Canada

[9 ]Asia-Pacific Economic Cooperation (APEC) Digital Hub for Mental Health, Canada

Author notes

[* ]Correspondence: agyapong@ 123456ualberta.ca ; Tel.: +1-780-215-7771; Fax: +1-780-743-3896

Author information

Vincent I. O. Agyapong https://orcid.org/0000-0002-2743-0372

Reham Shalaby https://orcid.org/0000-0002-3717-6398

Wesley Vuong https://orcid.org/0000-0001-8990-4804

Jasmine M. Noble https://orcid.org/0000-0001-5979-136X

Russell Greiner https://orcid.org/0000-0001-8327-934X

Andrew J. Greenshaw https://orcid.org/0000-0002-9097-900X

Article

Publisher ID: ijerph-18-02157

DOI: 10.3390/ijerph18042157

PMC ID: 7927101

PubMed ID: 33672120

SO-VID: 06367a7d-a729-4d67-a686-9c789e23b733

License:

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

History

Date received : 16 December 2020

Date accepted : 18 February 2021

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Mental Health Outreach via Supportive Text Messages during the COVID-19 Pandemic: Improved Mental Health and Reduced Suicidal Ideation after Six Weeks in Subscribers of Text4Hope Compared to a Control Population

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Novel Coronavirus Disease COVID-19

Most cited references 42

A brief measure for assessing generalized anxiety disorder: the GAD-7.

The PHQ-9: validity of a brief depression severity measure.

An interactive web-based dashboard to track COVID-19 in real time

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