Protocol
Abstract
Background: Major depressive disorder (MDD) is common worldwide and can be highly disabling. People with MDD face many barriers to treatment and may not experience full symptom relief even when treated. Therefore, new treatment modalities are needed for MDD. Digital therapeutics (DTx) may provide people with MDD an additional treatment option.
Objective: This study aimed to describe a phase 3 remote, multicenter, randomized, masked, sham-controlled trial evaluating the efficacy of a smartphone app–based DTx (CT-152) in adult participants diagnosed with MDD, used as an adjunct to antidepressant therapy (ADT).
Methods: Participants aged 22-64 years with a current primary diagnosis of MDD and an inadequate response to ADT were included. Participants were randomized 1:1 to CT-152 or a sham DTx. CT-152 is a smartphone app–based DTx that delivers a cognitive-emotional and behavioral therapeutic intervention. The core components of CT-152 are the Emotional Faces Memory Task exercises, brief lessons to learn and apply key therapeutic skills, and SMS text messaging to reinforce lessons and encourage engagement with the app. The sham DTx is a digital working memory exercise with emotionally neutral stimuli designed to match CT-152 for time and attention. Participants took part in the trial for up to 13 weeks. The trial included a screening period of up to 3 weeks, a treatment period of 6 weeks, and an extension period of 4 weeks to assess the durability of the effect. Sites and participants had the option of an in-person or remote screening visit; the remaining trial visits were remote. Efficacy was evaluated using the Montgomery-Åsberg Depression Rating Scale, the Generalized Anxiety Disorder-7, Clinical Global Impression–Severity scale, the Patient Health Questionnaire-9, and the World Health Organization Disability Assessment Schedule 2.0. The durability of the effect was evaluated with the Montgomery-Åsberg Depression Rating Scale and Generalized Anxiety Disorder-7 scale. Adverse events were also assessed. Satisfaction, measured by the Participant and Healthcare Professional Satisfaction Scales, and health status, measured by the EQ-5D-5L, were summarized using descriptive statistics.
Results: This study was initiated in February 2021 and had a primary completion date in October 2022.
Conclusions: This represents the methodological design for the first evaluation of CT-152 as an adjunct to ADT. This study protocol is methodologically robust and incorporates many aspects of conventional pivotal pharmaceutical phase 3 trial design, such as randomization and safety end points. Novel considerations included the use of a sham comparator, masking considerations for visible app content, and outcome measures relevant to DTx. The rigor of this methodology will provide a more comprehensive understanding of the effectiveness of CT-152.
Trial Registration: ClinicalTrials.gov NCT04770285; https://clinicaltrials.gov/study/NCT04770285
International Registered Report Identifier (IRRID): RR1-10.2196/56960
doi:10.2196/56960
Keywords
Introduction
Depression is a disabling and common disorder that affected 279.6 million people (5% of adults) worldwide in 2019 [
- ]. Major depressive disorder (MDD) accounted for 32.8 million years lived with disability globally in 2017, a 12.6% increase from 2007, and is predicted to be the leading global cause of disability by 2030 [ , ].Early effective treatment of MDD is associated with better outcomes, and decreasing the duration of the depressive episode can reduce symptoms, improve clinical and functional outcomes, and increase the chance of full symptom relief [
- ]. However, people with MDD face many barriers to antidepressant therapy (ADT) and psychotherapy treatment, including access to mental health care professionals (HCPs) [ , ], logistical challenges such as long wait times for appointment scheduling and limited schedules due to work and family demands [ ], and the stigma associated with mental illness [ ]. In 2022, only 61.5% of US adults with a major depressive episode (MDE) in the past year received treatment for depression [ ]. Global treatment rates are lower, with only 34.8% of people with depression receiving treatment annually [ ].Even when people with MDD can access treatment, it is not always successful. Many people with MDD do not respond to or achieve remission with ADT alone [
]. In the foundational Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial, only 48.6% and 36.8% of participants showed treatment response and achieved remission after first-line ADT, respectively, with lower percentages responding and remitting at each subsequent treatment step [ ]. Psychotherapy may also not be effective for all patients; a meta-analysis of 193 studies of psychotherapy for the treatment of depression found a response rate of 41% at a 2-month follow-up [ ]. Although ADT and psychotherapy alone may not work for all patients, data support that combining the 2 approaches is more effective for treating MDD symptoms than either approach alone [ - ].Current treatment options may be difficult to access and are not effective for all people with MDD; therefore, new approaches for treating MDD are needed. One approach that may address this unmet need is the use of digital therapeutics (DTx), a subset of digital health [
- ]. DTx are software programs that deliver evidence-based interventions for medical conditions [ ]. DTx may address a medical condition, manage, prevent, or treat a medical disorder or disease, or optimize medication [ ]. When used to treat mental disorders, DTx may help overcome some barriers to treatment [ ]. These software programs can be accessed remotely, allowing people with MDD more options than what may be available locally, and to access treatment on their own schedule [ - ]. Remote access to treatment can also ease stigma concerns and allow for more privacy [ ]. DTx may offer an additional option for nonpharmacological treatment, expanding patient choice [ ]. However, there are different types of digital health products in the United States that require different levels of regulatory oversight. Products that claim a treatment benefit must be cleared by the US Food and Drug Administration (FDA) and may require a prescription [ , , ].Otsuka Pharmaceutical Development & Commercialization, Inc, in collaboration with Click Therapeutics, Inc, has developed a smartphone app–based DTx, CT-152, for depression, used as an adjunct to ADT with the goal of reducing symptoms of depression. The core components of CT-152 are evidence-based training exercises (Emotional Faces Memory Task [EFMT]), brief lessons and activities to learn and apply key therapeutic skills, and supportive SMS text messaging to reinforce lessons and encourage engagement with the app. Although there are no comparable FDA-authorized digital therapeutics for MDD in the United States, there are some digital tools designed to support patients with MDD in addition to standard treatment that are available under FDA enforcement discretion (software that meets the regulatory definition of a device but pose minimal risk to patients, which can be obtained without a prescription). These tools have psychotherapy-based components but do not have training exercises [
]. The EFMT component of CT-152 was developed to adjust the connectivity in the affective network and regions of the cognitive control network that provide cognitive control over emotions [ , ].A growing body of research has linked MDD with impaired cognitive control of emotionally salient information [
, ]. Impaired cognitive control is believed to manifest in perseverative thinking patterns (eg, rumination) [ ]; these patterns serve to maintain or exacerbate the sad or depressed mood component in MDD [ - ]. Cognitive-emotional training, such as EFMT, has been shown to enhance cognitive control over emotions in people with MDD [ ].The goal of the EFMT exercises is to modify connectivity between the amygdala and dorsolateral prefrontal cortex by simultaneous emotion recognition and working memory tasks [
, ]. In 2 randomized controlled trials (RCTs), an improvement in depression symptoms was found to be statistically significant for participants with MDD who completed a digital EFMT regimen (4 and 6 weeks, respectively) compared with control participants who were not being treated with ADT or cognitive behavioral therapy (CBT) [ ]. A follow-up study with participants who completed the 6-week EFMT regimen indicated that EFMT use altered connectivity between the amygdala with the right dorsolateral prefrontal cortex and bilateral dorsal anterior cingulate cortex; these altered connections correlated with improved symptoms [ ].The MIRAI trial (ClinicalTrials.gov NCT04770285) was designed to measure the effectiveness and safety of CT-152 for reducing depressive symptoms in patients diagnosed with MDD who were on ADT monotherapy for the treatment of depression. Data from MIRAI supported the FDA application for this product to be cleared as a prescription DTx for the treatment of people with MDD. There is also the potential to use these data to support regulatory approvals in other global markets.
MIRAI had design components reflecting conventional phase 3 pharmaceutical trials and novel components designed for DTx evaluation specifically. Conventional components included a control group and the evaluation of both effectiveness and safety. Effectiveness end points were established from gold-standard scales that are acceptable to the FDA [
- ]. Safety was evaluated by the frequency and severity of adverse events (AEs). Novel considerations in MIRAI included a sham comparator. The sham DTx consisted of a digital working memory exercise with emotionally neutral stimuli and was matched to CT-152 for time, attention, and expectation of benefit. The sham DTx also had an SMS text message component. Another consideration was treatment masking, which is important when designing studies for DTx [ ]. Both participants and sites were masked to the treatment assignment. In DTx trials, a participant can spontaneously speak to an investigator, clinical raters, or study site staff about the exercises on the app (eg, participants reporting having difficulty with recognizing emotions on faces), leading to unmasking treatment assignment and introducing bias. Thus, additional masking considerations are required for both participants and investigators; steps taken in the MIRAI trial are listed in the Methods section. Finally, MIRAI incorporated outcomes that are relevant to DTx, including participant satisfaction with the treatment and adherence metrics.There is a growing body of literature calling for DTx to be held to the same evidentiary standards as pharmacotherapy [
- ]. It is critical that the effectiveness and safety of these novel DTx are evaluated in RCTs with adequate sample sizes and clinically meaningful end points [ - ]. This trial will extend the findings from earlier EFMT studies and provide data on the efficacy and safety of this DTx. If shown to be effective, CT-152 may be considered a novel nonpharmacological option for people diagnosed with MDD to use as an adjunct to ADT. Here, we review the rationale and study design for the MIRAI trial, including procedures to enable a methodologically rigorous investigation of the new treatment options offered with DTx.Methods
Overview
This was a phase 3 multicenter, randomized, masked, sham-controlled trial to evaluate the efficacy of CT-152 in adult participants diagnosed with MDD who were taking ADT. Participants took part in the trial for up to 13 weeks. The trial included a screening period of up to 3 weeks, a treatment period of 6 weeks, and an extension period of 4 weeks to assess the durability of the effect (
). Given the COVID-19 pandemic and the advantages of remote trials, especially for a DTx, MIRAI was run as a remote study. Except the screening visit, all visits took place remotely; the screening visit had an in-person or remote option per investigator and patient preference. Due to the DTx nature of this trial, participants needed routine access to their smartphones in their work and home life.![](https://asset.jmir.pub/assets/9f747ce2ec2591bd9b81df768182724d.png)
Study Participants
Key participant inclusion and exclusion criteria are listed in
.Inclusion criteria
- Aged 22 to 64 years at the time of informed consent.
- Fluent in written and spoken English.
- Taking antidepressant therapy (ADT) monotherapy with a current primary diagnosis of major depressive disorder (MDD) based on the criteria in the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]), single or recurrent episode, without psychotic features, and did not meet the criteria for MDD with mixed features subtype.
- Had a score for the Hamilton Rating Scale for Depression, 17-item of ≥18 at screening and the baseline visit (day 1).
- Had a reported history of inadequate response to an adequate trial of ADT in the current episode.
- Inadequate response was defined as a reduction in depression symptom severity <50% per the Massachusetts General Hospital-Antidepressant Treatment Response Questionnaire (MGH-ATRQ).
- An adequate trial was defined as at least 6 weeks at a minimum therapeutic dose (or higher), according to the MGH-ATRQ.
- Were willing to maintain their current ADT at the current dose for the duration of their participation in the trial.
- Were currently using a smartphone not shared with anyone else, with an Android operating system 9.0 or greater capabilities or with iPhone Operating System 13.0 (Apple, Inc) or greater capabilities and agreed to download and use the smartphone app as required by the protocol.
- Had completed the onboarding module in the smartphone app during the screening period, continued consent to participate in the trial, and understood how to use the app at the baseline visit.
Exclusion criteria
- Had a reported inadequate response to >1 adequate trial of ADT (as defined in the inclusion criteria) for the current major depressive episode (MDE).
- Had been treated with psychopharmacological augmentation (eg, lithium, triiodothyronine, antipsychotics added to ADT, and multiple ADT) for any past episode or the current episode.
- Had received psychotherapy within 90 days before screening.
- Had significant suicidal ideation within the last year, suicidal behavior within the past 2 years, or presented a serious risk of suicide (in the opinion of the investigator).
- Had been treated with electroconvulsive therapy or neuromodulation devices (ie, transcranial magnetic stimulation, vagus nerve stimulation, or transcranial direct current stimulation) for MDD in the past.
- Were currently using a computer, web, or smartphone software–based application or equivalent for mental health or MDD; participants could enroll if this app was discontinued before the baseline visit.
- Had been in a current MDE lasting longer than 2 years.
- Were considered resistant or refractory to treatment by history and per investigator judgment.
- Had a lifetime diagnosis of schizophrenia, schizoaffective disorder, other psychotic disorder, bipolar I or II disorder, or current posttraumatic stress disorder, panic disorder, or obsessive-compulsive disorder.
- Had been diagnosed with any DSM-5 personality disorder.
- Had MDD due to a general medical condition or a neurologic disorder.
Ethical Considerations
This trial was conducted in accordance with local laws, the International Conference on Harmonization Good Clinical Practice guidelines, and the Declaration of Helsinki. The protocol was reviewed and approved by the governing institutional review board (IRB) for each investigational site. Of the 54 study sites, IRB services were provided by Advarra (approval number 00000971) for 53 sites, and WCG IRB (approval number 1-1377994-1) for 1 site. IRB approvals were granted between November 2020 and January 2021. All participants were asked to provide consent to participate in this study before enrollment and agree to its privacy policy and terms of service required for the remote collection of their information. All information collected in the trial was considered confidential and was only used in accordance with the protocol. Participants were identified only by a unique identification number in eSource. However, regulatory officials or sponsor personnel could be allowed access to records, consistent with local requirements. Participants could withdraw from the trial at any time without justification. Participants received a stipend to help cover the costs associated with being in the study. Participants also had the option to have their ADT provided to them by the sponsor at no charge for the length of the study.
Intervention
CT-152 is a smartphone app–based DTx that delivers a proprietary interactive cognitive-emotional and behavioral intervention, intended for use as an adjunct to ADT. The core components of CT-152 are the EFMT exercises; brief CBT-based lessons, each paired with an out-of-app activity or guided audio psychotherapy exercise targeting the most common MDD symptoms; and SMS text messaging to reinforce the CBT-based lessons and encourage engagement with the app. Each treatment session consisted of an EFMT exercise and a brief lesson with an activity. During the EFMT exercises, participants were presented with a series of pictures of faces, tasked with identifying the emotions they observed and remembering the sequence of emotions [
]. Using an N-back working memory training paradigm, for each face observed, participants indicated whether the emotion is the same as the emotion N faces back [ ]. To date, CT-152 has only been developed in English.A sham DTx served as a control and provided a cognitive training exercise designed to retain user interest while minimizing therapeutic effects. Each sham session consisted of a Shapes Memory Task (SMT) exercise. The SMT is a working memory task that provides users with an analogous structure, matched for time and attention, to the cognitive-emotional training exercise (EFMT) in CT-152. The sham DTx did not include EFMT exercises or lessons to retain its intended nontherapeutic nature. Participants in the control group also received supportive SMS text messages related to maintaining engagement with study treatment. The SMT exercise has been previously used in EFMT pilot studies as the control condition [
, ].In order to be eligible to participate, during the screening period, participants had to complete an N-back working memory task simulating basic features of CT-152 to ensure they had the necessary skills to use it. This also confirmed their interest in participating in the study. After eligibility was confirmed, participants were randomized 1:1 to either CT-152 or sham DTx at the baseline visit (day 1). The participants progressed through a treatment schedule of 18 sessions at a rate of 3 sessions per week over the 6-week treatment period (day 1 to week 6). Participants had a remote study visit at weeks 2, 4, and 6 and were contacted by telephone at weeks 1, 3, and 5.
After week 6, participants continued in the trial during the extension period (weeks 7 to 10) to assess the durability of the effect. In the extension period, the smartphone app remained installed for each group; no new therapeutic content was introduced, and EFMT and SMT exercises were not available. The 2 groups each received brief supportive SMS text messages in the extension period with content related to the previously completed exercises. Participants had a remote study visit at weeks 8 and 10 and were contacted by the trial site by telephone at weeks 7 and 9.
A dedicated call center was available to support the participants and the trial sites on the initial downloading of and access to the smartphone app, as well as any technical issues with the app throughout the trial.
Outcomes and Assessments
The primary objective of the trial was to evaluate the efficacy of CT-152 in improving depressive symptoms versus the sham DTx, which served as a control. The primary efficacy end point was the change from baseline to week 6 in the Montgomery-Åsberg Depression Rating Scale (MADRS) total score.
Other efficacy end points included assessment of the MADRS at weeks 2 and 4; Generalized Anxiety Disorder-7 (GAD-7) scores at weeks 2, 4, and 6; the Clinical Global Impression–Severity scale scores (CGI-S) at weeks 2, 4, and 6; and the Patient Health Questionnaire-9 (PHQ-9) scores at weeks 4 and 6. Functional outcomes were assessed by World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) scores and quality of life by EQ-5D-5L scores at week 6. To evaluate the durability of the effect of the DTx, the change from baseline in MADRS and GAD-7 total score as well as MADRS response and remission rates were evaluated at weeks 8 and 10. The MADRS was conducted by trained and calibrated independent raters. Trial site staff administered the CGI-S. Participants completed the GAD-7, PHQ-9, WHODAS 2.0, and EQ-5D-5L (for scale descriptions, refer to
).Scales | Description |
MGH-ATRQa | A 6-item, participant self-reported scale to evaluate treatment-resistant depression [ | , ]
HAM-D17b | A 17-item, observer-reported scale to evaluate depression severity and response to treatment [ | ]
MADRSc | A 10-item, HCPd-reported scale to evaluate depression severity [ | ]
CGI-Se | A single-item, observer-reported scale to evaluate the severity of mental illness over the past week [ | ]
PHQ-9f | A 9-item, participant self-reported scale to screen for and assess depression severity [ | ]
GAD-7g | A 7-item, participant self-reported scale to screen for and assess the severity of general anxiety disorder [ | ]
WHODAS 2.0h | A 36-item, participant self-reported scale to assess the impact of a health condition on functioning [ | ]
Participant satisfaction scale | A 9-item, participant self-reported scale designed for the MIRAI trial to assess participants’ satisfaction with their DTxi assignment for the trial |
HCP satisfaction scale | A 2-item, HCP self-reported scale designed for the MIRAI trial to assess HCP satisfaction with delivering the DTx used by their patients during the trial |
EQ-5D-5L | A 5-item, participant self-reported scale to measure overall health status. It includes a vertical visual analog scale for participants to indicate their perception of their overall health [ | ]
C-SSRSj | A 6-item, participant self-reported scale to assess suicide risk, severity of risk, and support needed [ | ]
aMGH-ATRQ: Massachusetts General Hospital-Antidepressant Treatment Response Questionnaire.
bHAM-D17: Hamilton Rating Scale for Depression, 17-item.
cMADRS: Montgomery-Åsberg Depression Rating Scale.
dHCP: health care professional.
eCGI-S: Clinical Global Impressions-Severity.
fPHQ-9: Patient Health Questionnaire-9.
gGAD-7: Generalized Anxiety Disorder-7.
hWHODAS: World Health Organization Disability Assessment Schedule.
iDTx: digital therapeutics.
jC-SSRS: Columbia-Suicide Severity Rating Scale.
The safety objective was to assess the safety of CT-152 in adult participants with MDD who were concurrently taking ADT. Safety was evaluated by the frequency and severity of AEs, serious AEs, and discontinuations from the trial due to AEs. AEs related to smartphone use may include dizziness, fatigue, or headache and were anticipated as potential AEs reported by the participants [
, ]. Previous research did not assess AEs related to EFMT use [ , ]. Participants were required to be on ADT monotherapy, and the safety profile of ADTs used for MDD is well understood. Based on the known risks of ADT and smartphone use and a preliminary understanding of the risks of EFMT use, no additional risks were anticipated as related to CT-152 use. All participants were assessed weekly for both anticipated and unanticipated AEs; any participants reporting serious AEs were monitored.Participant adherence was monitored weekly. Furthermore, the number of CT-152 or sham sessions completed over the entire trial course was recorded.
Masking Considerations
In addition to masking the participants and trial sites for the treatment assignment, masked independent raters conducted the MADRS assessment by telephone. The independent raters had no access to trial procedures, treatment assignment, trial data, or clinical information other than what was solicited for the assessment. In addition, both independent raters and participants were instructed to avoid discussion of the DTx content and other aspects of the trial.
To minimize potential bias, trial sites had designated administrators of the other efficacy assessments. Administrators had limited contact with the participants and did not perform adherence checks. Participants completed self-reported outcomes independently and remotely.
The hypothesis of this trial—CT-152 would lead to greater improvement in MDD symptoms versus the sham DTx—was masked, and participants were informed that either DTx may be effective. This approach was intended to optimize adherence in both arms and limit the risk of participant unmasking and associated expectation biases. At the end of the study, participants were informed of the trial hypothesis, but were not informed of which DTx they had received.
CT-152 meets the definition of a nonsignificant risk device per 21 Code of Federal Regulations § 812.3(m) and a low- to moderate-risk device per Software as a Medical Device [
, ]. The masking approaches used in this trial were only used because (1) CT-152 posed minimal risks, (2) masking did not adversely affect the participants, and (3) the trial could only be conducted by withholding the information on participant treatment assignment.Sample Size Calculation
The initial sample size was calculated to detect a 3-unit difference between the CT-152 plus ADT and sham DTx plus ADT in the change from baseline in MADRS total score, with 85% power at a 2-sided α=.05 level. The resulting sample size was 324 evaluable participants in total (162 in each arm). The full analysis set was defined as all randomized participants who received at least 1 CT-152 or sham DTx session and had at least 2 MADRS total score assessments, 1 of which was at baseline. To compensate for participants who failed to have evaluable assessments of MADRS total score in the full analysis set sample (estimated at up to 10% of all participants), a total of approximately 360 participants (180 in each arm) were planned to be randomized. The trial randomized eligible participants 1:1 across 54 sites. The sample size at any single trial site was capped at approximately 15% of the total number of randomized participants. Randomization was stratified by the trial site.
Due to the limitations of applying assumptions on the treatment effect size, and to ensure adequate power of the trial, an unmasked interim analysis was conducted by a data monitoring committee, whose members recommended continuing the trial with the planned sample size of 360 participants (actual enrollment included 386 participants).
Statistical Methods
Baseline and demographic characteristics, including age, sex, race, and ethnicity, were summarized using descriptive statistics.
End Points and Assessments
The primary efficacy analysis was based on the mixed-model repeated measurements method and the change from baseline score to week 6 for the MADRS. The MADRS score change from baseline to weeks 2 and 4 was also assessed. Additional efficacy analyses included changes from baseline to predetermined end points for the GAD-7, CGI-S, WHODAS 2.0, and PHQ-9. MADRS partial and full response rates (≥30% to <50% from baseline and ≥50% reduction from baseline, respectively) at weeks 2, 4, and 6 were analyzed; MADRS response rates were also analyzed during weeks 8 and 10 of the extension period. All efficacy end points were based on the full analysis set.
The durability of the treatment effect was assessed based on MADRS and GAD-7 scores during the extension period. The SAS Enterprise Guide version 8.3 (SAS Institute Inc.) was used for statistical analyses.
Plan for Missing Data in Efficacy End Points
All data collected during the trial treatment period and extension period were used for statistical analysis. The mixed-model repeated measurements method assumed data were missing at random, which is a reasonable assumption for longitudinal clinical trials in MDD [
]. However, the possibility of missing not at random data was also considered. As sensitivity analyses, pattern-mixture models were used to explore data missing mechanisms of missing not at random and investigate the response profile of participants by dropout reason.Exploratory End Points
MADRS remission rates at weeks 2, 4, and 6 were analyzed. Remission was defined as a MADRS total score of ≤10 and a decrease of 50% or more of the total score from baseline. Satisfaction, measured by the Participant and Healthcare Professional Satisfaction Scales, and health status, measured by the EQ-5D-5L, were summarized using descriptive statistics.
Safety End Points
All AEs were coded by system organ class and Medical Dictionary for Regulatory Activities (MedDRA)-preferred term. The incidence of the following events was summarized by treatment group: (1) AEs that are potentially causally related to the treatment or sham DTx, (2) AEs with an outcome of death, serious AEs, and (3) AEs leading to discontinuation from the trial.
Adherence
Adherence was evaluated for all participants as the percentage of sessions completed over the course of the trial.
Results
The MIRAI study was funded in September 2020. It was initiated in February 2021, with a primary completion date of October 2022. As of study completion, 386 participants were enrolled. The primary data analysis is complete and expected to be published in the fall of 2024.
Discussion
Principal Findings
This was the first investigation of CT-152 as an adjunct to ADT for the treatment of depression. CT-152 has both cognitive-emotional training and behavioral intervention components, which is a novel combination compared with other digital tools designed to support patients with MDD currently available under FDA enforcement discretion [
]. This protocol incorporated aspects of conventional phase 3 pharmaceutical trials, including using a randomized controlled design and gold-standard scales for evaluating effectiveness. In addition, the safety analyses were intended to evaluate if CT-152, designed to provide a clinical intervention, had a low safety risk and was well tolerated by participants. MIRAI also considered factors that are not typical for DTx study design. The use of a sham DTx comparator minimized the potential that any changes between groups were because of CT-152 and not due to the demand characteristics of using a DTx. Bias related to knowledge of study treatment assignment was managed through robust masking procedures. Adherence was evaluated for both CT-152 and the sham DTx arms.Safety
Although DTx for mental disorders may be less likely to lead to AEs than pharmacotherapy, AEs, such as dizziness, fatigue, and headache, that are associated with mobile device use may also be associated with DTx [
, , ]. Therefore, it is important to assess the safety of DTx. Other current clinical trials for DTx for MDD do not assess safety outcomes [ ]. Among 11 protocols for clinical trials assessing DTx for MDD published recently, only 1 mentions assessing AEs along with suicide risk [ ]; 5 others assess suicide risk only [ - ]. Unlike the pivotal trials for current FDA-cleared DTx for mental disorders, the MIRAI trial assessed safety outcomes [ - ]. CT-152 was expected to be well tolerated due to the digital delivery of therapy and the mechanisms of action of its core therapeutic modules.Sham Comparator
In trials for pharmacological treatments, masking is typically achieved through a placebo that resembles the treatment being tested. In RCTs for DTx, having a placebo that allows for masking can be challenging [
]. Of 11 clinical trial protocols published in the past few years that evaluated digital interventions for MDD, only 5 involved masking; 1 of the 5 trials masked both participants and interviewers [ ]. When a participant is waitlisted or given treatment as usual during a trial of digital intervention, they may become aware of not receiving the treatment under study, which could impact their involvement and expectations [ ]. In conclusion, there are masking advantages to using a sham comparator.The variability in comparator arms in DTx trials can lead to challenges in understanding the effects of digital treatments as a class and relative to one another. In total, 3 meta-analyses of digital interventions for depression found lower effect sizes in studies of smartphone interventions that included comparators that controlled for time and attention but did not provide therapeutic intervention, compared with those studies with inactive comparators or waitlist controls [
- ]. This suggests that smartphone use alone may confer psychological benefits [ , - ]. Using a digital comparator may raise the evidentiary standard for evaluating a digital treatment [ , ]. Given these recent findings and the potential confounding factors when using a nondigital comparator for the control group (eg, waitlist or treatment as usual), a digital comparator is important for a more unbiased and accurate understanding of the effectiveness of a DTx [ - ].The MIRAI trial design is innovative because it included a sham DTx as the comparator, which helps to ensure that the comparison reflected a true change in symptoms (if any), rather than a nonspecific benefit related to digital interventions more broadly [
, , ]. The sham DTx more easily allowed for masking, with less risk of participants and investigators becoming unmasked.Outcomes Important for DTx
An important consideration for any treatment is understanding the relationship between improvement in patient symptoms and increased patient adherence to the treatment; this is a novel consideration for digital interventions [
, ]. For MDD specifically, among 11 study protocols involving DTx for MDD, 9 protocols described adherence assessments [ ]. While data on adherence were collected, none of the protocols defined adherence or how it would be evaluated.A systematic literature review on adherence and engagement with digital interventions for MDD defined adherence as the percentage of sessions completed (the number of sessions completed divided by the total number of sessions) and found that only 38 out of 94 studies reviewed had this information available [
]. Their findings highlight the importance of establishing a standardized metric for adherence to digital interventions to better compare results across studies and different types of interventions [ ]. The MIRAI study was designed to collect data that can be used to measure the percentage of sessions completed, which will contribute to the body of literature measuring adherence to digital interventions in a way that can be compared across studies.Another novel consideration for DTx that does not often apply to pharmacological treatments is the consideration of patient satisfaction with and the ability to easily use the intervention. This can include features such as an easy onboarding practice, personalizing app content, and text reminders for patients [
]. CT-152 includes text messages to remind participants of what they learned and to engage them with treatment. In addition, MIRAI had both a participant and an HCP satisfaction survey to gain further insights into how easy CT-152 was to use and how satisfied participants were with their experience.Limitations
While this study design addressed many common concerns about trials for digital interventions, it had limitations, such as not including adults younger than 22 years or older than 65 years. Therefore, potential benefits for these populations will need to be explored in future research [
]. The inclusion criterion for MDD severity was a Hamilton Rating Scale for Depression, 17-item score of ≥18, potentially excluding participants with milder MDD. A further limitation is that the MIRAI trial assessed CT-152 as an adjunct to ADT, and thus the results cannot be generalized to using the digital intervention without ADT.There were also potential limitations related to remote trials and digital interventions, such as limited access to technology or low digital literacy. In this study, participants were required to own a smartphone and had to complete an onboarding module to show they had an interest in study participation and the skills necessary to use CT-152 or the sham DTx. These requirements limited the potential for low digital access or literacy to impact participation.
In addition, a common occurrence in trials for digital interventions or that use remote data collection is participant attrition [
, ]. Although most clinical trials have some participants discontinue or be unresponsive to follow-up, this is more likely to happen in studies involving DTx [ , ]. Participant attrition was evaluated after the trial but was expected to be similar to what is seen in the literature. Participant engagement and adherence to digital interventions were also concerns [ ]. Both CT-152 and the sham DTx had text messages designed to encourage participant adherence and engagement throughout the study. To encourage overall continued adherence to the study program, participants were informed before enrolling that remote visits would be required, and they reviewed the visit schedule with trial site staff once randomized to a treatment arm. Adherence checks were also performed during the treatment period and adherence was monitored remotely through the DTx. Any signs of nonadherence were addressed by the investigator to remind and encourage participants to continue adhering to the study program.Conclusions
DTx has the potential to address many barriers to MDD treatment, including increasing access to more treatment options, allowing for remote access, easily fitting into a patient’s schedule, and easing stigma concerns [
- , ]. However, it is important that the effectiveness and safety of DTx are evaluated in RCTs with rigorous study design [ - ].Many considerations in conventional phase 3 trial design, such as safety end points, adherence, and the use of a sham comparator, have been incorporated into this protocol to assess the efficacy of CT-152 for MDD, although the way these considerations are assessed is often different for pharmacological treatment. Incorporating safety and adherence considerations, along with participant masking to the treatment, are not yet typical for DTx evaluation. Moreover, rigorous assessments of these outcomes will provide a more comprehensive understanding of the effectiveness of CT-152.
Acknowledgments
This study was funded and supported by Otsuka Pharmaceutical Development & Commercialization, Inc. Click Therapeutics was a codevelopment collaborator. Medical writing support for this manuscript was provided by Caroline Leitschuh, PhD, and Madeline Keleher, PhD, of Oxford Pharma Genesis Inc, Newtown, Pennsylvania, which was funded by Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, New Jersey.
Authors' Contributions
BR, MS, AS, EL, MF, DC, D Chen, and AF made a significant contribution to the conception, study design, execution, acquisition of data, analysis, and interpretation of the work reported. AJR and MHT made a significant contribution to the conception, study design, and interpretation of the work reported. BR, MS, AS, AJR, MHT, EL, MF, DC, D Chen, and AF took part in drafting, revising, and critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agreed to be accountable for all aspects of the work.
Conflicts of Interest
BR, MS, EL, MF, D Chen, and AF are employees of Otsuka Pharmaceutical Development & Commercialization, Inc, and DC is an employee of Otsuka Precision Health, Inc. AS is an employee of Click Therapeutics, Inc. MHT is a consultant for Otsuka Pharmaceutical Development & Commercialization, Inc. AJR has received consulting fees from Compass Inc., Curbstone Consultant LLC, Emmes Corp., Evecxia Therapeutics, Inc, Holmusk Technologies, Inc, ICON, PLC, Johnson & Johnson (Janssen), Liva-Nova, MindStreet, Inc, Neurocrine Biosciences Inc, Otsuka-US; speaking fees from Liva-Nova, Johnson & Johnson (Janssen); and royalties from Wolters Kluwer Health, Guilford Press, and the University of Texas Southwestern Medical Center, Dallas, TX.
References
- GBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. Feb 2022;9(2):137-150. [FREE Full text] [CrossRef] [Medline]
- Depression. World Health Organization. 2021. URL: https://www.who.int/news-room/fact-sheets/detail/depression [accessed 2021-12-11]
- Greenberg PE, Fournier AA, Sisitsky T, Simes M, Berman R, Koenigsberg SH, et al. The economic burden of adults with major depressive disorder in the United States (2010 and 2018). Pharmacoeconomics. Jun 2021;39(6):653-665. [FREE Full text] [CrossRef] [Medline]
- GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the global burden of disease study 2017. Lancet. 2018;392(10159):1789-1858. [FREE Full text] [CrossRef] [Medline]
- Liu Q, He H, Yang J, Feng X, Zhao F, Lyu J. Changes in the global burden of depression from 1990 to 2017: Findings from the Global Burden of Disease study. J Psychiatr Res. Jul 2020;126:134-140. [FREE Full text] [CrossRef] [Medline]
- Borentain S, Nash AI, Dayal R, DiBernardo A. Patient-reported outcomes in major depressive disorder with suicidal ideation: a real-world data analysis using PatientsLikeMe platform. BMC Psychiatry. Jul 23, 2020;20(1):384. [FREE Full text] [CrossRef] [Medline]
- Dong M, Zeng LN, Lu L, Li XH, Ungvari GS, Ng CH, et al. Prevalence of suicide attempt in individuals with major depressive disorder: a meta-analysis of observational surveys. Psychol Med. Jul 2019;49(10):1691-1704. [CrossRef] [Medline]
- Habert J, Katzman MA, Oluboka OJ, McIntyre RS, McIntosh D, MacQueen GM, et al. Functional recovery in major depressive disorder: focus on early optimized treatment. Prim Care Companion CNS Disord. Sep 01, 2016;18(5). [FREE Full text] [CrossRef] [Medline]
- Mongelli F, Georgakopoulos P, Pato MT. Challenges and opportunities to meet the mental health needs of underserved and disenfranchised populations in the United States. Focus (Am Psychiatr Publ). Jan 2020;18(1):16-24. [FREE Full text] [CrossRef] [Medline]
- Andrilla CHA, Patterson DG, Garberson LA, Coulthard C, Larson EH. Geographic variation in the supply of selected behavioral health providers. Am J Prev Med. Jun 2018;54(6 Suppl 3):S199-S207. [FREE Full text] [CrossRef] [Medline]
- Ofonedu ME, Belcher HME, Budhathoki C, Gross DA. Understanding Barriers to Initial Treatment Engagement among Underserved Families Seeking Mental Health Services. J Child Fam Stud. Mar 2017;26(3):863-876. [FREE Full text] [CrossRef] [Medline]
- Arnaez JM, Krendl AC, McCormick BP, Chen Z, Chomistek AK. The association of depression stigma with barriers to seeking mental health care: a cross-sectional analysis. J Ment Health. Apr 2020;29(2):182-190. [CrossRef] [Medline]
- Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: results from the 2022 National Survey on Drug Use and Health (HHS Publication No. PEP23-07-01-006, NSDUH Series H-58). URL: https://www.samhsa.gov/data/sites/default/files/reports/rpt42731/2022-nsduh-nnr.pdf [accessed 2024-07-11]
- Mekonen T, Chan GCK, Connor JP, Hides L, Leung J. Estimating the global treatment rates for depression: a systematic review and meta-analysis. J Affect Disord. 2021;295:1234-1242. [CrossRef] [Medline]
- Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905-1917. [CrossRef] [Medline]
- Cuijpers P, Karyotaki E, Ciharova M, Miguel C, Noma H, Furukawa TA. The effects of psychotherapies for depression on response, remission, reliable change, and deterioration: a meta-analysis. Acta Psychiatr Scand. 2021;144(3):288-299. [FREE Full text] [CrossRef] [Medline]
- Cuijpers P, Berking M, Andersson G, Quigley L, Kleiboer A, Dobson KS. A meta-analysis of cognitive-behavioural therapy for adult depression, alone and in comparison with other treatments. Can J Psychiatry. 2013;58(7):376-385. [FREE Full text] [CrossRef] [Medline]
- Karyotaki E, Smit Y, Holdt Henningsen K, Huibers MJH, Robays J, de Beurs D, et al. Combining pharmacotherapy and psychotherapy or monotherapy for major depression? A meta-analysis on the long-term effects. J Affect Disord. 2016;194:144-152. [CrossRef] [Medline]
- Kamenov K, Twomey C, Cabello M, Prina AM, Ayuso-Mateos JL. The efficacy of psychotherapy, pharmacotherapy and their combination on functioning and quality of life in depression: a meta-analysis. Psychol Med. 2017;47(3):414-425. [FREE Full text] [CrossRef] [Medline]
- Williams LM. Getting personalized: brain scan biomarkers for guiding depression interventions. Am J Psychiatry. 2017;174(6):503-505. [CrossRef] [Medline]
- Hallgren KA, Bauer AM, Atkins DC. Digital technology and clinical decision making in depression treatment: current findings and future opportunities. Depress Anxiety. 2017;34(6):494-501. [FREE Full text] [CrossRef] [Medline]
- Lake J, Turner MS. Urgent need for improved mental health care and a more collaborative model of care. Perm J. 2017;21:17-24. [FREE Full text] [CrossRef] [Medline]
- Ormel J, Cuijpers P, Jorm A, Schoevers RA. What is needed to eradicate the depression epidemic, and why. Mental Health & Prevention. 2020;17:1-11. [CrossRef]
- Ceskova E, Silhan P. Novel treatment options in depression and psychosis. Neuropsychiatr Dis Treat. 2018;14:741-747. [FREE Full text] [CrossRef] [Medline]
- Digital therapeutics: combining technology and evidence-based medicine to transform personalized patient care. Digital Therapeutics Alliance. 2018. URL: https://www.dtxalliance.org/wp-content/uploads/2018/09/DTA-Report_DTx-Industry-Foundations.pdf [accessed 2022-08-04]
- Lord SE, Campbell ANC, Brunette MF, Cubillos L, Bartels SM, Torrey WC, et al. Workshop on implementation science and digital therapeutics for behavioral health. JMIR Ment Health. 2021;8(1):e17662. [FREE Full text] [CrossRef] [Medline]
- Dang A, Arora D, Rane P. Role of digital therapeutics and the changing future of health care. J Family Med Prim Care. 2020;9(5):2207-2213. [FREE Full text] [CrossRef] [Medline]
- Muñoz RF, Pineda BS, Barrera AZ, Bunge E, Leykin Y. Digital tools for prevention and treatment of depression: lessons from the Institute for International Internet Interventions for Health. Clínica y Salud. 2021;32(1):37-40. [CrossRef]
- Renfrew ME, Morton DP, Morton JK, Hinze JS, Przybylko G, Craig BA. The influence of three modes of human support on attrition and adherence to a web- and mobile app-based mental health promotion intervention in a nonclinical cohort: randomized comparative study. J Med Internet Res. 2020;22(9):e19945. [FREE Full text] [CrossRef] [Medline]
- Hassanpour S, Tomita N, DeLise T, Crosier B, Marsch LA. Identifying substance use risk based on deep neural networks and instagram social media data. Neuropsychopharmacology. 2019;44(3):487-494. [FREE Full text] [CrossRef] [Medline]
- Carl JR, Jones DJ, Lindhiem OJ, Doss BD, Weingardt KR, Timmons AC, et al. Regulating digital therapeutics for mental health: opportunities, challenges, and the essential role of psychologists. Br J Clin Psychol. 2022;61 Suppl 1:130-135. [CrossRef] [Medline]
- General wellness: policy for low risk devices guidance for industry and Food and Drug Administration staff. United States Food and Drug Administration. 2019. URL: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/general-wellness-policy-low-risk-devices [accessed 2022-08-10]
- Policy for device software functions and mobile medical applications: guidance for industry and Food and Drug Administration staff. United States Food and Drug Administration. 2019. URL: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/policy-device-software-functions-and-mobile-medical-applications [accessed 2022-08-10]
- McIntyre RS, Greenleaf W, Bulaj G, Taylor ST, Mitsi G, Saliu D, et al. Digital health technologies and major depressive disorder. CNS Spectr. 2023;28(6):662-673. [CrossRef] [Medline]
- Iacoviello BM, Wu G, Alvarez E, Huryk K, Collins KA, Murrough JW, et al. Cognitive-emotional training as an intervention for major depressive disorder. Depress Anxiety. 2014;31(8):699-706. [CrossRef] [Medline]
- Iacoviello BM, Murrough JW, Hoch MM, Huryk KM, Collins KA, Cutter GR, et al. A randomized, controlled pilot trial of the emotional faces memory task: a digital therapeutic for depression. NPJ Digit Med. 2018;1:21. [FREE Full text] [CrossRef] [Medline]
- Iacoviello BM, Charney DS. Developing cognitive-emotional training exercises as interventions for mood and anxiety disorders. Eur Psychiatry. 2015;30(1):75-81. [CrossRef] [Medline]
- Murrough JW, Iacoviello B, Neumeister A, Charney DS, Iosifescu DV. Cognitive dysfunction in depression: neurocircuitry and new therapeutic strategies. Neurobiol Learn Mem. 2011;96(4):553-563. [CrossRef] [Medline]
- Watkins ER. Constructive and unconstructive repetitive thought. Psychol Bull. 2008;134(2):163-206. [FREE Full text] [CrossRef] [Medline]
- Hoch MM, Doucet GE, Moser DA, Hee Lee W, Collins KA, Huryk KM, et al. Initial evidence for brain plasticity following a digital therapeutic intervention for depression. Chronic Stress (Thousand Oaks). 2019;3:2470547019877880. [FREE Full text] [CrossRef] [Medline]
- Patient-focused drug development: incorporating clinical outcome assessments into endpoints for regulatory decision-making guidance for industry, Food and Drug Administration staff, and other stakeholders (draft guidance). United States Food and Drug Administration. 2023. URL: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-focused-drug-development-incorporating-clinical-outcome-assessments-endpoints-regulatory [accessed 2023-06-09]
- Löwe B, Kroenke K, Herzog W, Gräfe K. Measuring depression outcome with a brief self-report instrument: sensitivity to change of the patient health questionnaire (PHQ-9). J Affect Disord. 2004;81(1):61-66. [CrossRef] [Medline]
- Hudgens S, Floden L, Blackowicz M, Jamieson C, Popova V, Fedgchin M, et al. Meaningful change in depression symptoms assessed with the Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) among patients with treatment resistant depression in two, randomized, double-blind, active-controlled trials of esketamine nasal spray combined with a new oral antidepressant. J Affect Disord. 2021;281:767-775. [FREE Full text] [CrossRef] [Medline]
- Lutz J, Offidani E, Taraboanta L, Lakhan SE, Campellone TR. Appropriate controls for digital therapeutic clinical trials: a narrative review of control conditions in clinical trials of digital therapeutics (DTx) deploying psychosocial, cognitive, or behavioral content. Front Digit Health. 2022;4:823977. [FREE Full text] [CrossRef] [Medline]
- Espie CA, Firth J, Torous J. Evidence-informed is not enough: digital therapeutics also need to be evidence-based. World Psychiatry. 2022;21(2):320-321. [FREE Full text] [CrossRef] [Medline]
- Ghaemi SN, Sverdlov O, van Dam J, Campellone T, Gerwien R. A smartphone-based intervention as an adjunct to standard-of-care treatment for schizophrenia: randomized controlled trial. JMIR Form Res. 2022;6(3):e29154. [FREE Full text] [CrossRef] [Medline]
- Insel TR. The NIMH experimental medicine initiative. World Psychiatry. 2015;14(2):151-153. [FREE Full text] [CrossRef] [Medline]
- Bernstein EE, Weingarden H, Wolfe EC, Hall MD, Snorrason I, Wilhelm S. Human support in app-based cognitive behavioral therapies for emotional disorders: scoping review. J Med Internet Res. 2022;24(4):e33307. [FREE Full text] [CrossRef] [Medline]
- Torous J, Bucci S, Bell IH, Kessing LV, Faurholt-Jepsen M, Whelan P, et al. The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry. 2021;20(3):318-335. [FREE Full text] [CrossRef] [Medline]
- Dang A, Dang D, Rane P. The expanding role of digital therapeutics in the post-Covid-19 era. The Open COVID Journal. 2021;1(1):32-37. [CrossRef]
- Developing novel endpoints generated by digital health technology for use in clinical trials. Clinical Trial Transformation Initiative. 2022. URL: https://ctti-clinicaltrials.org/wp-content/uploads/2022/03/CTTI-Digital-Health-Trials-Novel-Endpoint-Acceptance-Recommendations.pdf [accessed 2023-01-05]
- Murray E, Hekler EB, Andersson G, Collins LM, Doherty A, Hollis C, et al. Evaluating digital health interventions: key questions and approaches. Am J Prev Med. 2016;51(5):843-851. [FREE Full text] [CrossRef] [Medline]
- Weir K. The ascent of digital therapies. 2018. URL: https://www.apa.org/monitor/2018/11/cover-digital-therapies [accessed 2022-09-13]
- Chandler GM, Iosifescu DV, Pollack MH, Targum SD, Fava M. RESEARCH: Validation of the Massachusetts General Hospital Antidepressant Treatment History Questionnaire (ATRQ). CNS Neurosci Ther. 2010;16(5):322-325. [FREE Full text] [CrossRef] [Medline]
- Desseilles M, Witte J, Chang TE, Iovieno N, Dording CM, Ashih H, et al. Assessing the adequacy of past antidepressant trials: a clinician's guide to the antidepressant treatment response questionnaire. J Clin Psychiatry. 2011;72(8):1152-1154. [FREE Full text] [CrossRef] [Medline]
- Ma S, Yang J, Yang B, Kang L, Wang P, Zhang N, et al. The patient health questionnaire-9 vs. the hamilton rating scale for depression in assessing major depressive disorder. Front Psychiatry. 2021;12:747139. [CrossRef]
- Quilty LC, Robinson JJ, Rolland JP, Fruyt FD, Rouillon F, Bagby RM. The structure of the montgomery-asberg depression rating scale over the course of treatment for depression. Int J Methods Psychiatr Res. 2013;22(3):175-184. [FREE Full text] [CrossRef] [Medline]
- Busner J, Targum SD. The clinical global impressions scale: applying a research tool in clinical practice. Psychiatry (Edgmont). 2007;4(7):28-37. [FREE Full text] [Medline]
- Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092-1097. [CrossRef] [Medline]
- Measuring health and disability: manual for WHO disability assessment schedule (?WHODAS 2.0). World Health Organization. 2010. URL: https://www.who.int/publications/i/item/measuring-health-and-disability-manual-for-who-disability-assessment-schedule-(-whodas-2.0) [accessed 2023-03-21]
- EQ-5D-5L user guide (version 3.0). EuroQol Research Foundation. 2019. URL: https://euroqol.org/wp-content/uploads/2023/03/EQ-5D-5LUserguide-08-0421.pdf [accessed 2023-03-21]
- The columbia protocol (C0SSRS): about the protocol. The Columbia Lighthouse Project. 2016. URL: https://cssrs.columbia.edu/the-columbia-scale-c-ssrs/about-the-scale/ [accessed 2023-03-21]
- Chung JY. Digital therapeutics and clinical pharmacology. Transl Clin Pharmacol. 2019;27(1):6-11. [FREE Full text] [CrossRef] [Medline]
- Kollins SH, DeLoss DJ, Cañadas E, Lutz J, Findling RL, Keefe RSE, et al. A novel digital intervention for actively reducing severity of paediatric ADHD (STARS-ADHD): a randomised controlled trial. Lancet Digit Health. 2020;2(4):e168-e178. [FREE Full text] [CrossRef] [Medline]
- Guidance for the content of premarket submissions for software contained in medical devices. United States Food and Drug Administration. 2005. URL: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/content-premarket-submissions-device-software-functions [accessed 2023-04-17]
- 21 Code of Federal Regulations part 812. United States Food and Drug Administration. 2023. URL: https://www.ecfr.gov/current/title-21/chapter-I/subchapter-H [accessed 2023-04-17]
- Siddiqui O, Hung HMJ, O'Neill R. MMRM vs. LOCF: a comprehensive comparison based on simulation study and 25 NDA datasets. J Biopharm Stat. 2009;19(2):227-246. [CrossRef] [Medline]
- Crisafulli S, Santoro E, Recchia G, Trifirò G. Digital therapeutics in perspective: from regulatory challenges to post-marketing surveillance. Front Drug Saf Regul. 2022;2. [CrossRef]
- Software treatments for actively reducing severity of cognitive deficits in MDD (STARS-MDD). ClinicalTrials.gov. 2018. URL: https://clinicaltrials.gov/ct2/show/NCT03310281 [accessed 2022-09-14]
- Antle BF, Owen JJ, Eells TD, Wells MJ, Harris LM, Cappiccie A, et al. Dissemination of computer-assisted cognitive-behavior therapy for depression in primary care. Contemp Clin Trials. 2019;78:46-52. [CrossRef] [Medline]
- Fitzsimmons-Craft EE, Taylor CB, Newman MG, Zainal NH, Rojas-Ashe EE, Lipson SK, et al. Harnessing mobile technology to reduce mental health disorders in college populations: a randomized controlled trial study protocol. Contemp Clin Trials. 2021;103:106320. [FREE Full text] [CrossRef] [Medline]
- Williams C, McClay CA, Martinez R, Morrison J, Haig C, Jones R, et al. Online CBT life skills programme for low mood and anxiety: study protocol for a pilot randomized controlled trial. Trials. 2016;17(1):220. [FREE Full text] [CrossRef] [Medline]
- Weisel KK, Zarski AC, Berger T, Schaub MP, Krieger T, Moser CT, et al. Transdiagnostic tailored internet- and mobile-based guided treatment for major depressive disorder and comorbid anxiety: study protocol of a randomized controlled trial. Front Psychiatry. 2018;9:274. [FREE Full text] [CrossRef] [Medline]
- Krämer R, Köhler S. Evaluation of the online-based self-help programme "selfapy" in patients with unipolar depression: study protocol for a randomized, blinded parallel group dismantling study. Trials. 2021;22(1):264. [FREE Full text] [CrossRef] [Medline]
- Richards D, Duffy D, Blackburn B, Earley C, Enrique A, Palacios J, et al. Digital IAPT: the effectiveness & cost-effectiveness of internet-delivered interventions for depression and anxiety disorders in the Improving Access to Psychological Therapies programme: study protocol for a randomised control trial. BMC Psychiatry. 2018;18(1):59. [FREE Full text] [CrossRef] [Medline]
- Campbell AN, Nunes EV, Matthews AG, Stitzer M, Miele GM, Polsky D, et al. Internet-delivered treatment for substance abuse: a multisite randomized controlled trial. Am J Psychiatry. 2014;171(6):683-690. [FREE Full text] [CrossRef] [Medline]
- Christensen DR, Landes RD, Jackson L, Marsch LA, Mancino MJ, Chopra MP, et al. Adding an internet-delivered treatment to an efficacious treatment package for opioid dependence. J Consult Clin Psychol. 2014;82(6):964-972. [FREE Full text] [CrossRef] [Medline]
- Investigation of the freespira breathing system in the treatment of post traumatic stress disorder (PTSD). ClinicalTrials.gov. 2020. URL: https://clinicaltrials.gov/ct2/show/NCT03039231 [accessed 2022-08-16]
- Christensen H, Batterham PJ, Gosling JA, Ritterband LM, Griffiths KM, Thorndike FP, et al. Effectiveness of an online insomnia program (SHUTi) for prevention of depressive episodes (the GoodNight Study): a randomised controlled trial. Lancet Psychiatry. 2016;3(4):333-341. [CrossRef] [Medline]
- Forbes A, Keleher MR, Venditto M, DiBiasi F. Assessing patient adherence to and engagement with digital interventions for depression in clinical trials: systematic literature review. J Med Internet Res. 2023;25:e43727. [FREE Full text] [CrossRef] [Medline]
- Firth J, Torous J, Nicholas J, Carney R, Rosenbaum S, Sarris J. Can smartphone mental health interventions reduce symptoms of anxiety? a meta-analysis of randomized controlled trials. J Affect Disord. 2017;218:15-22. [FREE Full text] [CrossRef] [Medline]
- Firth J, Torous J, Nicholas J, Carney R, Pratap A, Rosenbaum S, et al. The efficacy of smartphone-based mental health interventions for depressive symptoms: a meta-analysis of randomized controlled trials. World Psychiatry. 2017;16(3):287-298. [FREE Full text] [CrossRef] [Medline]
- Goldberg SB, Lam SU, Simonsson O, Torous J, Sun S. Mobile phone-based interventions for mental health: a systematic meta-review of 14 meta-analyses of randomized controlled trials. PLOS Digit Health. 2022;1(1):e0000002. [FREE Full text] [CrossRef] [Medline]
- Linardon J, Cuijpers P, Carlbring P, Messer M, Fuller-Tyszkiewicz M. The efficacy of app-supported smartphone interventions for mental health problems: a meta-analysis of randomized controlled trials. World Psychiatry. 2019;18(3):325-336. [FREE Full text] [CrossRef] [Medline]
- Moritz S, Schilling L, Hauschildt M, Schröder J, Treszl A. A randomized controlled trial of internet-based therapy in depression. Behav Res Ther. 2012;50(7-8):513-521. [CrossRef] [Medline]
- MacLean S, Corsi DJ, Litchfield S, Kucharski J, Genise K, Selaman Z, et al. Coach-facilitated web-based therapy compared with information about web-based resources in patients referred to secondary mental health care for depression: randomized controlled trial. J Med Internet Res. 2020;22(6):e15001. [FREE Full text] [CrossRef]
- Dahlhausen F, Zinner M, Bieske L, Ehlers JP, Boehme P, Fehring L. There's an app for that, but nobody's using it: insights on improving patient access and adherence to digital therapeutics in Germany. Digit Health. 2022;8:20552076221104672. [FREE Full text] [CrossRef] [Medline]
- Walker DM, Hefner JL, Fareed N, Huerta TR, McAlearney AS. Exploring the digital divide: age and race disparities in use of an inpatient portal. Telemed J E Health. 2020;26(5):603-613. [FREE Full text] [CrossRef] [Medline]
- Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of attrition and dropout in app-based interventions for chronic disease: systematic review and meta-analysis. J Med Internet Res. 2020;22(9):e20283. [FREE Full text] [CrossRef] [Medline]
- Pratap A, Neto EC, Snyder P, Stepnowsky C, Elhadad N, Grant D, et al. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. NPJ Digit Med. 2020;3:21. [FREE Full text] [CrossRef] [Medline]
Abbreviations
ADT: antidepressant therapy |
AE: adverse event |
CBT: cognitive behavioral therapy |
CGI-S: Clinical Global Impression–Severity scale |
DTx: digital therapeutics |
EFMT: Emotional Faces Memory Task |
FDA: US Food and Drug Administration |
GAD-7: General Anxiety Disorder-7 scale |
HCP: health care professional |
IRB: institutional review board |
MADRS: Montgomery-Åsberg Depression Rating Scale |
MDD: major depressive disorder |
MDE: major depressive episode |
MedDRA: Medical Dictionary for Regulatory Activities |
PHQ-9: Patient Health Questionnaire-9 |
RCT: randomized controlled trial |
SMT: Shapes Memory Task |
STAR*D: Sequenced Treatment Alternatives to Relieve Depression |
WHODAS 2.0: World Health Organization Disability Assessment Schedule 2.0 |
Edited by S Ma; submitted 01.02.24; peer-reviewed by B Imbert; comments to author 01.03.24; revised version received 31.05.24; accepted 17.06.24; published 20.08.24.
Copyright©Brian Rothman, Mary Slomkowski, Austin Speier, A John Rush, Madhukar H Trivedi, Erica Lawson, Michael Fahmy, Daniel Carpenter, Dalei Chen, Ainslie Forbes. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 20.08.2024.
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