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Efficacy and Conflicts of Interest in RCTs Evaluating Headspace and Calm Apps: A Systematic Review (Preprint)

July 2022
JMIR Mental Health 9(9)

DOI:10.2196/40924

License
CC BY 4.0

Authors:

Alison O'Daffer

University of California, San Diego

Akash Wasil

University of Pennsylvania

Background: Although there are thousands of mental health apps, 2 apps, Headspace and Calm, claim a large percentage of the marketplace. These two mindfulness and meditation apps have reached tens of millions of active users. To guide consumers, clinicians, and researchers, we performed a systematic review of randomized controlled trials (RCTs) of Headspace and Calm. Objective: Our study aimed to evaluate intervention efficacy, risk of bias, and conflicts of interest (COIs) in the evidence base for Headspace and Calm, the two most popular mental health apps at the time of our search. Methods: To identify studies, we searched academic databases (Google Scholar, MEDLINE, and PsycINFO) and the websites of Headspace and Calm in May 2021 for RCTs of Headspace and Calm testing efficacy via original data collection, published in English in peer-reviewed journals. For each study, we coded (1) study characteristics (eg, participants, sample size, and outcome measures), (2) intervention characteristics (eg, free vs paid version of the app and intended frequency of app usage), (3) all study outcomes, (4) Cochrane risk of bias variables, and (5) COI variables (eg, presence or absence of a preregistration and the presence or absence of a COI statement involving the company). Results: We identified 14 RCTs of Headspace and 1 RCT of Calm. Overall, 93% (13/14) of RCTs of Headspace and 100% (1/1) of RCTs of Calm recruited participants from a nonclinical population. Studies commonly measured mindfulness, well-being, stress, depressive symptoms, and anxiety symptoms. Headspace use improved depression in 75% of studies that evaluated it as an outcome. Findings were mixed for mindfulness, well-being, stress, and anxiety, but at least 40% of studies showed improvement for each of these outcomes. Studies were generally underpowered to detect "small" or "medium" effect sizes. Furthermore, 50% (7/14) of RCTs of Headspace and 0% (0/1) of RCTs of Calm reported a COI that involved Headspace or Calm (the companies). The most common COI was the app company providing premium app access for free for participants, and notably, 14% (2/14) of RCTs of Headspace reported Headspace employee involvement in study design, execution, and data analysis. Only 36% (5/14) of RCTs of Headspace were preregistered, and the 1 RCT of Calm was not preregistered. Conclusions: The empirical research on Headspace appears promising, whereas there is an absence of randomized trials on Calm. Limitations of this study include an inability to compare Headspace and Calm owing to the dearth of RCTs studying Calm and the reliance on author reports to evaluate COIs. When determining whether or not mental health apps are of high quality, identification of high-quality apps and evaluation of their effectiveness and investigators' COIs should be ensured.

Available via license: CC BY 4.0

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Records identified from:

PsycInfo (n = 19)

MEDLINE (n = 59)

Google Scholar (n= 34,310)

Records removed before

screening:

Duplicate records removed

(n = 16,328)

Records screened

(n = 18,060)

Records excluded:

Not studying Headspace or

Calm (n = 17,997)

Reports assessed for eligibility

(n = 63)

Reports excluded:

Non-RCT (n = 48)

Records identified from:

Headspace Website (n = 25)

Calm Website (n = 22)

Reports assessed for eligibility

(n = 47)

Reports excluded:

Non-RCT (n = 38)

Studies included in review

(n = 15)

Identification of studies via databases and registers

Identification of studies via other methods

Identification

Screening

Included

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Anxiety and trauma related disorders are highly prevalent, causing suffering and high costs for society. Current treatment strategies, although effective, only show moderate effect-sizes when compared to adequate control groups demonstrating a need to develop new forms of treatment or optimize existing ones. In order to achieve this, an increased understanding of what mechanisms are involved is needed. An emerging literature indicates that mindfulness training (MFT) can be used to treat fear and anxiety related disorders, but the treatment mechanisms are unclear. One hypothesis, largely based on findings from neuroimaging studies, states that MFT may improve extinction retention, but this has not been demonstrated empirically. To investigate this question healthy subjects either completed a 4-week MFT- intervention delivered through a smart-phone app (n = 14) or were assigned to a waitlist (n = 15). Subsequently, subjects participated in a two-day experimental protocol using pavlovian aversive conditioning, evaluating acquisition and extinction of threat-related responses on day 1, and extinction retention on day 2. Results showed that the MFT group displayed reduced spontaneous recovery of threat related arousal responses, as compared to the waitlist control group, on day 2. MFT did not however, have an effect on either the acquisition or extinction of conditioned responses day 1. This clarifies the positive effect of MFT on emotional functioning and could have implications for the treatment of anxiety and trauma related disorders.

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Oct 2019
BEHAV RES THER

Smartphone applications for the treatment of depression and anxiety have acquired millions of users, yet little is known about whether they include evidence-based therapeutic content. We examined the extent to which popular mental health applications (MH apps) for depression and anxiety contain treatment elements found in empirically supported psychotherapy protocols (i.e., "common elements"). Of the 27 MH apps reviewed, 23 included at least one common element, with a median of three elements. Psychoeducation (in 52% of apps), relaxation (44%), meditation (41%), mindfulness (37%), and assessment (37%) were the most frequent elements, whereas several elements (e.g., problem solving) were not found in any apps. We also identified gaps between app content and empirically supported treatments. Cognitive restructuring was more common in depression protocols than in depression apps (75% of protocols vs. 31% of apps), as was problem solving (34% vs. 0%). For anxiety, exposure (85%, 12%), cognitive restructuring (60%, 12%), and problem solving (25%, 0%) were more common in protocols than apps. Overall, our findings highlight empirically supported treatment elements that are poorly represented in current MH apps. The absence of several core treatment elements underscores the need for future research, including randomized trials testing the effectiveness of popular MH apps.

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Article

Mar 2021

Objective This article analyzes the changes in downloads and activity of users of select popular mental health mobile applications (mHealth apps) during coronavirus disease 2019 (COVID-19). Background The outbreak of the COVID-19 crisis has shown a negative impact on public mental health. Mobile health has the potential to help address the psychological needs of existing and new patients during the pandemic and beyond. Method Downloads data of 16 widely used apps were analyzed. The quality of apps was reviewed using the Mobile Application Rating Scale (MARS) framework. Correlation analysis was conducted to investigate the relationship between app quality and app popularity. Results Among the 16 apps, 10 were meditational in nature, 13 showed increased downloads, with 11 apps showing above 10% increase in the downloads after the pandemic started. The popular apps were satisfactory in terms of functionality and esthetics but lacked clinical grounding and evidence base. There exists a gap between app quality and app popularity. Conclusion This study provided evidence for increased downloads of mental mHealth apps (primarily meditation apps) during the COVID-19 pandemic but revealed several gaps and opportunities to address deficiencies in evidence-based design, usability and effective assessment, and integration into current workflows. Application The COVID-19 pandemic is a potential turning point for mHealth applications for mental health care. Whereas the evidence suggests a need for alternative delivery of care, human factors and ergonomics methods should be utilized to ensure these tools are user-centered, easy to use, evidence-based, well-integrated with professional care, and used sustainably.

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