JMIR FORMATIVE RESEARCH

Goldin et al

Original Paper

Feasibility of a Therapist-Supported, Mobile Phone–Delivered
Online Intervention for Depression: Longitudinal Observational
Study
Philippe R Goldin1, PhD; Riku Lindholm2, MSc; Kristian Ranta2, MSc; Outi Hilgert2, MD; Tiia Helteenvuori2, MA;
Anu Raevuori2, MD, PhD
1

Betty Irene Moore School of Nursing, University of California Davis, Sacramento, CA, United States

2

Meru Health Inc, Palo Alto, CA, United States

Corresponding Author:
Philippe R Goldin, PhD
Betty Irene Moore School of Nursing
University of California Davis
4610 X Street
Sacramento, CA, 95817
United States
Phone: 1 4156769793
Email: philippegoldin@gmail.com

Abstract
Background: Depression is a very common condition that impairs functioning and is often untreated. More than 60% of thetreatments for depressive disorder are administered in primary care settings by care providers who lack the time and expertise totreat depression. To address this issue, we developed Ascend, a therapist-supported, mobile phone–delivered 8-week intervention
administered at the Meru Health Online Clinic in Finland.
Objective: We conducted two pilot studies to examine the feasibility of the Ascend intervention, specifically, dropout rates,
daily practice, weekly group chat use, and changes in depression symptoms. We also explored whether daily practice and weekly
group chat use were associated with changes in depression symptoms.
Methods: A total of 117 Finnish adults with elevated depressive symptoms enrolled in Ascend, a program that included daily
cognitive behavioral and mindfulness meditation exercises delivered through a mobile phone app, anonymous group chat withother users, and chat/phone access to a licensed therapist. Eight weekly themes were delivered in a fixed, sequential format.
Depression symptoms were measured at baseline, every second week during the intervention, immediately after the intervention,and 4 weeks after completion of the intervention. Data were analyzed using intent-to-treat repeated-measures analysis of varianceand linear regression models.
Results: For studies 1 and 2, we observed dropout rates of 27% and 15%, respectively, decreasing daily practice and group chatuse, and decreased depression symptoms from baseline to immediately and 4 weeks after the intervention (P<.001). We foundthat both more daily practice and chat group use predicted the occurrence of fewer depressive symptoms at 4 weeks postintervention(Study 1: ∆R2=.38, P=.004 and ∆R2=.38, P=.002, respectively; Study 2: ∆R2=.16, P<.001 and ∆R2=.08, P=.002, respectively).
Conclusions: This therapist-supported, mobile phone–delivered treatment for depression is feasible and associated with reduced
depression symptoms. Design features that enhance daily practice and group chat use are areas of future investigation. Validationof these results using a controlled study design is needed to establish the evidence base for the Ascend intervention.
(JMIR Formativ Res 2019;3(1):e11509) doi: 10.2196/11509
KEYWORDS
cognitive therapy; depression; digital health; digital therapeutics; mindfulness; online intervention

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Introduction
Background
Depression is one of the most common mental disorders,
impacting more than 300 million people worldwide according
to the World Health Organization (WHO) [1]. In addition,
depression carries the heaviest burden of disability among all
mental and behavioral disorders [2]. People who suffer fromdepression often experience significant problems with
employment, physical health, interpersonal functioning, suicidal
ideation, and suicidal attempts. Thus, depression inflicts asignificant burden on the individual, the network of family andfriends, and society at large.
There are several effective psychological [3,4] andpharmacological interventions [5] for depression. However, theWHO estimates that less than 50% of people with major
depression receive any care for their symptoms. Many people
with depression do not have access to effective clinical care andare not willing to use antidepressant medications. Others arehesitant to obtain mental health treatment due to individual andsocial stigma [6]. Furthermore, when treated withantidepressants, roughly one-third of patients do not experiencesignificant alleviation in symptoms [7]. In primary care settings,
only 20% of patients who are referred to psychotherapy follow
up, and of those, more than 50% drop out of treatment [8]. Thus,
from a public health perspective, there is a need to examine
other ways of delivering interventions for depression that bypass
these obstacles.
Online interventions for mental disorders, especially depression
and anxiety, have gained increasing popularity during the last
decade. These online interventions can be delivered in manydifferent formats including psychoeducation, self-help programs,
chat support groups, interactive health coaching, andprofessional-led online therapy [9]. Online interventions havethe advantage of being accessible to patients who previously
did not have access to such mental health care. Further
advantages include their ability to be self-paced, be
programmable to record practice, and have a flexible sequenceof clinical content and exercise that can be tailored to theindividual patient. Importantly, they are also able to support
clinical techniques such as cognitive reappraisal and mindfulness
meditation practices in real-time and natural contexts.
Furthermore, there is evidence that web-based interventions
that include human support or coaching increase adherence andproduce better outcomes [10].
There is a growing body of evidence for the beneficial effectof online interventions for depression. A recent meta-analysis[11] of controlled trials from a 10-year period (2006-2016)
showed that therapist-supported online cognitive behavioral
therapy (CBT) and in-person CBT were equally effective in
reducing depressive symptoms and superior to treatment as
usual, waitlist controls, and attention controls. Furthermore,this meta-analysis did not find an interaction between depression
severity and CBT efficacy, suggesting that therapist-supported
online CBT may be helpful for patients at all levels of depression
severity. A meta-analysis [12] of 15 randomized controlled
trials (RCTs) demonstrated a significant impact of online
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Goldin et al
mindfulness-based interventions on depression symptoms.
Studies also suggest the cost effectiveness and cost utility[13,14] of online interventions for depression over traditional
treatment modalities. Improved cost effectiveness combinedwith high scalability makes online interventions a promisingarea for development and dissemination of empirically supported
interventions, especially for traditionally underserved patients.
More recently, the increased use and flexibility of mobile phones
has presented a more promising route to extend the reach ofclinical interventions. A recent meta-analysis involving 3414
participants across 18 RCTs of mobile phone–based
interventions for depression [15] showed a small reduction in
depression symptoms compared to an active control group(Hedge g=.22) and a moderate reduction compared to an inactive
control group (g=.56). This study also found no statisticaldifference between the effect of mobile phone only and mobile
phone plus human/computerized components for the treatment
of depression. Furthermore, apps focused on mental healthproduced a greater reduction in depression symptoms than apps
focused on cognitive training. Interestingly, the integration of
specific features, including mood monitoring, CBT, andmindfulness, did not alter the observed effects sizes. In addition,a more conservative subanalysis of studies (n=16) that used
intention-to-treat analyses or reported complete outcome data
showed a moderate effect of these treatment methods on
depression symptoms (g=.40). This meta-analysis suggests thatmobile phone apps may be a potentially effective tool tointroduce self-management skill training for adults withdepression. However, we need to better understand the potential
mechanisms (ie, mediators) and pretreatment patient features(ie, moderators) that predict outcome and help us refine mobile
phone–delivered interventions for depression.
To address the public health need for more accessible
interventions for depression, we developed a new mobile
phone–delivered intervention that includes self-help modules,
support from a personal remote therapist, and chat group accessto an anonymous patient peer-group support.

Present Study
The goal of this pilot study was to examine the feasibility of a
newly developed mobile phone–delivered, therapist-supported
8-week intervention for depression in self-referred depressedindividuals. We examined dropout, number of days of practice,
and weekly use of an online group chat. For symptom reduction,
we examined intervention-related changes in depression
symptoms and whether daily practice and weekly group chatuse predicted a reduction in depression symptoms. We proposed
three hypotheses. First, we expected a dropout of ≤30% among
all participants, daily practice on at least half of the days (ie,28/56 days), and weekly group chat use for at least half (4/8)
of the weekly group chat sessions. We also examined the patternof change in daily practice and weekly group chat over the
8-week intervention. Second, we expected the Ascend program
to be associated with significant decreases in depression
symptoms. In study 1, we used the Beck Depression Inventory-II(BDI-II) [16] to measure depression symptoms. In study 2, we
shifted to the Patient Health Questionnaire 9-item version(PHQ-9) [17], because it is more commonly used than BDI-II
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in primary health care. Third, we expected that greater amountof daily practice and weekly group chat use during the 8-weekintervention would predict reductions in depression symptoms.

Methods
Recruitment
For studies 1 and 2, participants were recruited from March to
September 2017 in Finland via online Facebook advertisements
for the Meru Health Online Clinic, a national remote health careprovider approved by the Finnish National Supervisory
Authority for Welfare and Health (Valvira approval number
V/25535/2017). Meru Health operates under HIPAA (Health
Insurance Portability and Accountability Act); legislation andall protected health information is stored in a HIPAA-compliant
cloud storage hosted by a company called Datica [18]. All data
are encrypted in transit, end to end, and at rest.
Participants were offered a free online intervention for
depression that included mobile phone–delivered content,
anonymous weekly chat group, and private phone/chat accessto therapists. All participants were required to have a mobile
phone. To enter the study, participants had to demonstrate somedepression symptoms based on the BDI-II (>9) in study 1 andat least mild depression symptoms based on the PHQ-9 (>4) instudy 2. We increased the depression symptom cut-off in study
2 to match the validated score of PHQ-9 for screening mild
depression. Other inclusion criteria included the perceived
ability of the participant by both the participant and therapist
to commit to an 8-week online intervention with a minimum of
20 minutes of practice 6 days per week. The exclusion criteria
included previous suicide attempts, severe suicidal ideation witha specific plan, severe self-harm, active substance abuse, and ahistory of psychotic disorder.

Procedures
We informed participants that the goal of the study was to
examine an online intervention for depression, delivered througha mobile phone app. Participants provided informed consent
through the Ascend mobile phone app for their anonymous data
to be used for further intervention refinement and research
purposes. Participants were not compensated for their
participation. They enrolled in the program at no cost.
Institutional review board exemption was granted by Pearl IRB(Indianapolis, IN) for analyses of previously collected anddeidentified data.
We provided participants a link to download the Meru Health
Ascend app on their mobile phone to access the intervention
content. Participants used a unique identification number torecord depression symptoms at baseline, during the intervention,
immediately after the intervention, and 4 weeks after theintervention. We trained participants on how to access ananonymous chat group and converse with the study therapist
via direct one-to-one chat messaging or, in few exceptions,phone calls.
As part of the standard treatment procedure at the Meru Health
Online Clinic, Ascend study therapists conducted phoneinterviews to examine inclusion and exclusion criteria before
enrollment and determine participant suitability for the online
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Goldin et alintervention. After the program, the study therapist spoke toparticipants via phone calls to assess the participant’s
experiences and address any further needs. In addition,
participants had an opportunity to speak directly with thetherapist via phone calls during the program. This occurred inonly a few cases when a participant had a specific concern orquestion that could not be properly communicated by chatmessaging with the study therapist.

Ascend Program
The Ascend program consists of 8 modules delivered in a fixedorder through a mobile phone app over an 8-week period,
including practices derived from mindfulness-based stress
reduction [19], mindfulness-based cognitive therapy [20], CBT[21], and behavioral activation therapy [22] treatment protocols.
Modules are delivered each week in the following sequence:
Introduction to mindfulness, Low mood and motivation,
Self-compassion, Managing worry, Overcoming thinking traps,
Rethinking your life values, Being aware of your relationships,
and Relapse prevention. The content was designed to teachparticipants skills based on mindfulness meditation and cognitive
behavioral therapy. The content for each week unlocked
automatically during each of the 8 weeks of the Ascendintervention without the need to view prior content and complete
prior exercises. The Ascend program has high standards of data
security and adheres to the European Union General Data
Protection Regulation requirements (EU 2016/679). If there
were any signs of mental state deterioration during theintervention, the study therapist conducted an additional
phone-based assessment of the participant’s condition. For
emergencies such as severe suicidality, the Ascend intervention
includes a written security plan that all participants reviewed
with the therapist before starting the program.
The Meru Health therapists provided ongoing individual support
as needed and curation of the group chat during the Ascendintervention. The interaction took place primarily via chatmessaging and, in a few instances, phone calls. Therapists
included one medical doctor and two master’s-level clinicalpsychologists, each of whom had training in mindfulness-based
stress reduction or mindfulness-based cognitive therapy. The
patients could reach out to their therapist whenever they wanted.
However, more than 50% of the communication was initiatedby the therapist, not the patient. The therapist would normallycheck in with the patient via chat at least 2-3 times/week to see
how the patient was doing. On an average, the therapist spent
20 minutes on each patient per week, including time spentchatting with the patient and reviewing the patient’s data andprogress.
Study therapists used a Professional Dashboard (Meru Health
Inc, CA), which is a secure web-based tool to monitor
participant progress and chat with participants. The mobile
phone app hosted all the weekly program content, including
text, video, audio, and graphics. The intervention included video
lessons every week, audio-guided mindfulness-meditation
practices, visual graphics that illustrated cognitive-behavioral
principles, and journaling prompts.
The mobile phone app consisted of the following components:a “Me” screen to access the daily practices and learning
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Goldin et almaterials; a “Program” screen to view the structure of the whole
Ascend program, identify where on the timeline one is currently
located, and access already completed modules and practices;a “Group” screen to view other anonymous participants’ written
reflections on different practices and lessons (the Group screen
did not allow any commenting, but rather only reading oftherapist’s and other participants’ comments); a “Notifications”
screen to track therapists’ messages and newly available lessons
or practices; and an “Other” screen to view the Emergency Plan,
Privacy Policy, Terms of Use, and a single button to contact
the therapist via chat messaging.

participant had to score a minimum of 5 points at baseline. Priorlarge-scale studies have shown that the PHQ-9 has excellent
internal reliability, with Cronbach alpha of 0.89 in primary caresettings, and excellent test-retest reliability [24].

Measures

Statistical Analysis

We used multiple measures to assess the feasibility of the
Ascend intervention. We measured dropout from theintervention, operationally defined as less than 4 weeks of active
participation during the 8-week intervention. We also measured
completion of mobile phone–delivered practices (number ofdays during the 8 weeks) and participation in the once-weekly
chat group (a binary yes/no measure). As stated above, we
shifted from the BDI-II in study 1 to the PHQ-9 in study 2 tomeasure depression symptoms, because it became clear that thelatter self-report measure is more commonly used across a wide
variety of health care settings.

We computed descriptive statistics for different indicators ofintervention engagement. We plotted the number of days per
week of practice during the intervention and the number ofweeks of chat group use and used a repeated-measures analysis
of variance (ANOVA) with Huynh-Feldt correction for
autocorrelation of adjacent time points to examine whether there
was significant change over time in the number of days ofpractice completed and online chat group use.

Depression Symptoms
Beck Depression Inventory-II
Depressive symptoms were measured using the BDI-II, a scale
containing 21 items rated 0-3 points in terms of intensity, withtotal scores ranging from 0 to 63. BDI-II scores of 14-19 points
suggest mild depression; 20-28 points suggest moderate
depression, and 29-63 points suggest severe depression. To
enter the Ascend intervention, the participant had to score aminimum of 10 points at baseline. The BDI-II has demonstrated
high internal consistency (Cronbach alpha=0.9) in outpatient
samples [23].

Therapist Rating Questionnaire
To assess the patient-therapist interaction, we used a single-item
question: “How valuable has the therapist interaction been foryou?” This rating ranged from 1 to 5, with higher values
indicating greater value. The patient-therapist interaction wasassessed at weeks 1, 3, and 6 and after the intervention.

We used an intent-to-treat analysis that included all participants
regardless of whether they completed or dropped out of theintervention. We used the more conservative method of last
observation carried forward to insert missing data immediately
postintervention and during the 4 weeks of follow-up. We
implemented repeated-measures ANOVA and reported effectsize as partial eta-squared (η2p) using SPSS, version 25 (IBMCorp, Armonk, NY). We also computed a depression-change
score from the baseline to the 4-week follow-up to be used as
the dependent variable in subsequent linear regressions.
Using linear regression analysis controlling for baseline levelsof depression, we examined whether change in depression
symptoms from baseline to 4 weeks postintervention waspredicted by the number of days of practice during theintervention or the number of weeks of group chat use.

Patient Health Questionnaire-9
The PHQ-9 is the 9-item depression scale extracted from thefull PHQ. Because each of the 9 items can be scored from 0(not at all) to 3 (nearly every day), the PHQ-9 score can range
from 0 to 27 points. PHQ-9 scores of 5-9 points suggest mild
depression, 10-14 points suggest moderate depression, 15-19
points suggest moderately severe depression, and 20-27 points
suggest severe depression. To enter the Ascend program, theResults
Participant Characteristics
As shown in Table 1, participants were primarily female, young
adults, and college educated and all Caucasian. Thus, thesamples in studies 1 and 2 were similar and uniform.

Table 1. Characteristics of participants.
Characteristic

Study 1 (n=22)

Study 2 (n=95)

Women, n (%)

22 (100)

76 (80.0)

Age (years), mean (SD)23.2 (1.1)

32.0 (9.85)

Education (years), mean (SD)

17.4 (3.3)

16.3 (2.1)

Ethnicity (Caucasian), n (%)

22 (100)

95 (100)

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Goldin et alStudy 1

Depression Symptoms

Dropout, Daily Practice, and Weekly Group Chat

We used an intent-to-treat analysis that included all participants.
Repeated-measures ANOVA for depression symptoms measured
with the BDI-II revealed a significant reduction from before toafter the intervention (mean delta=–8.55, SD 9.17; F1,21=19.11;

Dropout from the 8-week Ascend intervention was observed in
6 of the 22 participants (27%). For mobile phone–delivered
exercises during the Ascend intervention, participants completed
daily practices on 42% of the 56 days (mean 23.8 days; SD
14.2; range 1-49 days). A repeated-measures ANOVA, with
Huynh-Feldt correction for autocorrelation of adjacent time
points, showed that the mean number of days per week ofpractice decreased significantly (F4.02=15.02, P<.001, η2p=.43)
from week 1 (mean 4.57 days [SD 1.72]) to week 8 (mean 1.52
[SD 1.83]) of the intervention (Figure 1). For the once-weekly
group chat, participants participated for an average of 4.87
weeks (SD 3.12; range 0-8 weeks). Repeated-measures
ANOVA, with Huynh-Feldt correction for autocorrelation of
adjacent time points, showed that the percentage of participants
who used the online chat group per week decreased significantly
from week 1 (78%) to week 8 (52%; F5.21=2.65, P=.03, η2p=.11,
g=.68). Participants reported a high and consistent level of theparticipant-therapist interaction across four time points during
the 8-week intervention (mean 4.12).

P<.001; η2p=.48) as well as from before to 4 weeks after theintervention (ie, week 12 assessment; mean delta=–10.91, SD
10.35; F1,21= 24.44; P<.001; η2p=.54; Figure 2).

Predictors of Change in Depression Symptoms
Using a linear regression controlling for baseline depression
symptoms, we found that greater number of days of practicesignificantly predicted a reduction in depressive symptoms fromthe baseline to 4 weeks postintervention (BDI-II; ∆ R2=.38; ∆F1,20=11.14; P=.004; unstandardized coefficient beta=–0.45,
standard error of beta=0.14, 95% CI=–0.74 to –0.17; Figure 3).
Similarly, we found that higher number of weeks of group chatuse predicted a reduction in depressive symptoms from baseline
to 4 weeks after the intervention (BDI-II; ∆ R2=.38; ∆F1,20=12.30; P=.002; unstandardized coefficient beta=–2.06,
SE of beta=.59, 95% CI=–3.29 to –0.83).

Figure 1. Number of days per week of mobile phone–delivered practices completed during the 8-week Ascend intervention during study 1. Error bars
indicate standard error of the mean.

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Figure 2. Depression symptoms during study 1 of the Ascend intervention. Error bars indicate standard error of the mean.

Figure 3. Daily practice and weekly group chat use during Ascend intervention predict pre-to-post change in depression symptoms in Ascend in study
1.

Study 2
Dropout, Daily Practice, and Weekly Group Chat
Dropout was noted in 14 of the 95 participants (15%).
Participants completed the mobile phone–delivered exercises
during the Ascend intervention on 55% of the days (mean 30.9
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days; SD 14.1; range 1-56 days). A repeated-measures ANOVA,
with Huynh-Feldt correction for autocorrelation of adjacenttime points, showed that the mean number of days per week ofpractice decreased significantly (F6.02, 535.33=38.4; P<.001;
η2p=.30) in a linear trajectory from week 1 (mean 5.04 days
[SD 1.71]) to week 8 (mean 2.63 [SD 2.31]) of the intervention
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JMIR FORMATIVE RESEARCH(Figure 4). For the once-weekly group chat, participants
participated in an average of 5.81 weeks (SD 2.63; range 0-8
weeks). A repeated-measures ANOVA, with Huynh-Feldt
correction for autocorrelation of adjacent time points, showedthat the percentage of participants who used the online chatgroup per week decreased significantly from week 1 (85%) to
week 8 (59%; F5.59, 514.50=6.09; P<.001; η2p=.06). Participants
reported high and consistent levels of participant-therapist
interaction across four time points during the 8-weekintervention (mean=4.13).

Depression Symptoms
A repeated-measures ANOVA of depression symptoms
measured with the PHQ-9 revealed a significant reduction frombefore to after the intervention (mean delta=–4.39, SD 5.07;
F1,94=71.20; P<.001; η2p=.43) as well as from before to 4 weeks

Goldin et al
after the intervention (ie, week 12; F1,94=71.88; P<.001; η2p=.43;
Figure 5).

Predictors Of Change in Depression Symptoms
Using linear regression, we found that higher number of daysof practice significantly predicted lower residual depression
symptoms at 4 weeks postintervention (∆R2=.16, F1,89=16.46,
P<.001; unstandardized beta=–0.028, standard error ofbeta=0.01, 95% CI=–0.041 to –0.014; Figure 6).
We also found that higher number of weeks of group chat use
predicted reduced depressive symptoms at 4 weeks
postintervention (∆ R2=.08, ∆ F1,91=9.92, P=.002;
unstandardized coefficient beta=–0.63, standard error ofbeta=0.20, 95% CI=–1.03 to –0.23; Figure 6).

Figure 4. Number of days per week of mobile phone–delivered practices completed during the 8-week Ascend intervention during study 2. Error bars
indicate standard error of the mean.

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Figure 5. Depression symptoms during study 2 of the Ascend intervention. Error bars indicate standard error of the mean.

Figure 6. Daily practice and weekly group chat use during Ascend intervention predict pre-to-post change in depression symptoms in Ascend in study
2.

Discussion
Principal Findings
Findings from this study suggest that the mobile
phone–delivered, therapist-supported Ascend intervention was
associated with acceptable levels of dropout, linear decreasing
daily practice, and weekly group chat use as well as significant
decreases in depression symptoms in a sample of self-referred
depressed individuals. Furthermore, the amount of daily practiceand weekly group chat use during the intervention wereassociated with a reduction in depression symptoms frombaseline to 4 weeks postintervention.

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Comparison with Prior WorkA recent RCT of CBT for major depression reported 33%
dropout from mobile-delivered CBT (mobile phone or iPad)versus 30% dropout from computer-delivered CBT [25]. For
comparison with nonmobile phone internet-delivered
intervention for depression, a recent study [21] that employeda coach to guide people through online therapy for depressed
patients reported a 37% dropout rate. Thus, the dropout rate
observed in our pilot study (17%, 20/117 participants) was
comparable to both other mobile phone– and internet-delivered
interventions.
Daily practice of mobile phone–delivered exercises decreased
linearly over the course of the 8-week Ascend intervention inboth pilot studies. Given that the amount of daily practice
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significantly predicted a reduction in depression symptoms ineach of the two pilot studies, this finding is disconcerting andstrongly suggests that further effort is needed to investigate
methods to support sustained practice, as it may lead to greater
clinical improvement. This may involve introducing more novel
types of practices or different modes of delivery of practices tomaintain the participant’s attention and sustained engagement.
Ongoing measurement of engagement during the intervention
and tailoring the delivery to individual participants may help
increase sustained practice. This could involve the use ofindividual participant feedback after each practice to direct what
type of practice and modality is to be used when delivering
subsequent practices. A brief motivational interview by thetherapist may also identify and overcome obstacles toengagement. This is a component of internet interventions thatwould benefit from further research. Sustained engagement may
likely increase the effect of the Ascend intervention and possibly
reduce the probability of depression relapses.
Group chat, often referred to as synchronous text-based
dialogue, is an increasingly important component of online
mental health interventions. In our studies, the number of weeks
of chat group use decreased significantly over the 8-weekintervention. Like daily practice, group chat use was a significant
predictor of a reduction in depressive symptoms. A recent
review [26] found that interventions using one-on-one
synchronous chat reduced clinical symptoms more than waitlists,
but not more than treatment as usual (face-to-face and telephonecounseling). Research has found that text-based chatcommunication involves approximately 50% fewer words thanoral conversation [27]. In our study, however, the chat group,
which included intervention participants and curation by thetherapist, was only one component of the intervention. Moreresearch is needed to better understand the factors that encourage
and inhibit group chat use in mobile phone–delivered
interventions for depression.
The Ascend intervention was associated with a reduction in
depression symptoms across two pilot studies. However, because
we did not incorporate a comparison control group, we cannot
rule out regression to the mean as a reason for the reduced
depression symptoms. Nonetheless, our intent-to-treat analysis
revealed a moderate effect (g=.43 to .54) for reduction ofdepression symptoms across the two pilot studies. Our findings
are in line with the results from a recent meta-analysis [15] ofmobile phone–delivered interventions for depression that foundmoderate effect sizes for intent-to-treat or complete outcome
data trials (g=.40), CBT-based interventions (g=.53), andinterventions that included mindfulness practices (g=.49).
Importantly, subanalyses in this meta-analysis that focused on
diagnosed mood disordered samples showed that mobile
phone–delivered interventions were most effective for patientswith self-reported mild-to-moderate levels of depression
symptoms (g=.52). This is important because individuals with
mild-to-moderate depression symptoms are most likely to havethe capacity to use mobile phone and other online interventions.
Identification of predictors of better outcomes is essential for
determining how to refine and optimize a clinical intervention.
We found that higher number of days of completing mobile
phone–delivered practices predicted a greater reduction in
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self-reported depression symptoms. Variance in the reductionof depression symptoms explained by practice during the 8-week
Ascend intervention ranged from 7% to 38%. Additionally, inboth pilot studies, we found that greater chat group use predicted
reduced depression symptoms. Although these findings arepromising, they also suggest that there likely are other factorsthat predict outcome and may interact with subgroups ofpatients. It will be important to determine which specificpractices and what amount of group chat use are most effective
for reducing depression symptoms.
Identifying patient characteristics that predict the impact of
online interventions on depression symptoms is essential. A
well-controlled study comparing self-guided internet-delivered
interpersonal psychotherapy, CBT, and MoodGYM found thatfemale gender, lower mastery, and lower dysfunctional attitudes
predicted lesser depression symptoms following 4 weeks oftreatment and 6 months of follow-up regardless of theintervention type [28]. Understanding how these patientcharacteristics interact with daily practice and group chat use
should be examined in future studies.
Given that novelty captures attention, one approach is to explore
on an individual participant level whether introducing newmodalities of delivery of didactic content and practices might
recapture attention and dedication to practice. An algorithm
could be used to detect when the number of days of practicebegins to decrease and then introduce new videos, practices, orcommunication from other participants and psychotherapist to
buttress against further reduction in practice. Another method
would be to show each individual their own week-to-weekrelationship between practice and depression symptoms tofurther motivate engagement with the Ascend program.

Limitations
Participants in this study were self-referred, and thus, there may
be a sampling bias in that these individuals were more motivatedto participate than the normative population of depressedindividuals. Furthermore, the sample consisted of 80%-100%
women, which is also not representative of the population ofindividuals with depression in clinical settings or the community.
This pilot study did not include any control group with orwithout an active comparison intervention, which limits theinferences that can be made regarding the efficacy or comparisonof the effect sizes between the Ascend program and otherinterventions. Future studies will benefit from comparison of
Ascend to gold-standard psychosocial (eg, CBT) andpharmacological interventions as well as a control group without
an active intervention. Although this study provides initialevidence of a reduction in depression symptoms, future studies
should include diagnostic assessment of participants. In addition
to changes in clinical symptoms, it will be important to measureputative mediators of the Ascend intervention related to
mindfulness meditation (eg, mindfulness skills) and CBT (eg,cognitive reappraisal). Future studies might consider determining
whether the amount (eg, duration in minutes and frequency of
events) or type of therapist-patient interaction (eg, chat, phone,and email) predicts intervention outcome.

JMIR Formativ Res 2019 | vol. 3 | iss. 1 | e11509 | p. 9
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Conclusions
The overall finding from this pilot study is that the 8-weekonline Ascend intervention was associated with reduced

Goldin et al
depression symptoms. However, more rigorous controlled trials
that compare the Ascend intervention with both other online
mental health interventions and gold-standard clinicalinterventions for major depression are needed.

Acknowledgments
We wish to express our gratitude to the staff at Meru Health who collected and archived the data in Finland.

Conflicts of Interest
PRG owns options of Meru Health Inc. RL serves as the chief operating officer of Meru Health Inc, owns a large share of thecompany’s stocks, and receives a salary from the company. KR serves as the chief executive officer of Meru Health Inc, owns alarge share of the company's stocks, and receives a salary from the company. OH is employed as a chief therapist by Meru Health
Inc, owns stocks and options, and receives a salary from the company. At the time of the study, TH was employed as a therapist
by Meru Health Inc and received a salary from the company. AR is employed as a medical director by Meru Health Inc, owns
stocks and options, and receives a salary from the company.

References
1.
2.
3.

4.
5.

6.

7.
8.

9.
10.
11.

12.

13.

14.

15.

Depression and Other Common Mental Disorders: Global Health Estimates. Geneva, Switzerland: WHO Document
Production Services; 2017. URL: http://www.who.int/sorry/ [accessed 2019-01-09] [WebCite Cache ID 75IhZpDfu]
Lépine JP, Briley M. The increasing burden of depression. Neuropsychiatr Dis Treat 2011;7(Suppl 1):3-7 [FREE Full text][doi: 10.2147/NDT.S19617] [Medline: 21750622]
Piet J, Hougaard E. The effect of mindfulness-based cognitive therapy for prevention of relapse in recurrent major depressive
disorder: a systematic review and meta-analysis. Clin Psychol Rev 2011 Aug;31(6):1032-1040. [doi:10.1016/j.cpr.2011.05.002] [Medline: 21802618]
Butler AC, Chapman JE, Forman EM, Beck AT. The empirical status of cognitive-behavioral therapy: a review ofmeta-analyses. Clin Psychol Rev 2006 Jan;26(1):17-31. [doi: 10.1016/j.cpr.2005.07.003] [Medline: 16199119]
Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, et al. Comparative efficacy and acceptabilityof 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network
meta-analysis. Lancet 2018 Dec 07;391(10128):1357-1366. [doi: 10.1016/S0140-6736(17)32802-7] [Medline: 29477251]
Aromaa E, Tolvanen A, Tuulari J, Wahlbeck K. Personal stigma and use of mental health services among people withdepression in a general population in Finland. BMC Psychiatry 2011 Mar 31;11:52 [FREE Full text] [doi:10.1186/1471-244X-11-52] [Medline: 21453504]
Warden D, Rush AJ, Trivedi MH, Fava M, Wisniewski SR. The STAR*D Project results: a comprehensive review offindings. Curr Psychiatry Rep 2007 Dec;9(6):449-459. [Medline: 18221624]
Mohr DC, Hart SL, Howard I, Julian L, Vella L, Catledge C, et al. Barriers to psychotherapy among depressed andnondepressed primary care patients. Ann Behav Med 2006 Dec;32(3):254-258. [doi: 10.1207/s15324796abm3203_12][Medline: 17107299]
Barak A, Grohol JM. Current and Future Trends in Internet-Supported Mental Health Interventions. Journal of Technology
in Human Services 2011 Jul;29(3):155-196. [doi: 10.1080/15228835.2011.616939]
Mohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence
to eHealth interventions. J Med Internet Res 2011;13(1):e30 [FREE Full text] [doi: 10.2196/jmir.1602] [Medline: 21393123]
Ahern E, Kinsella S, Semkovska M. Clinical efficacy and economic evaluation of online cognitive behavioral therapy for
major depressive disorder: a systematic review and meta-analysis. Expert Rev Pharmacoecon Outcomes Res 2018
Feb;18(1):25-41. [doi: 10.1080/14737167.2018.1407245] [Medline: 29145746]
Spijkerman MPJ, Pots WTM, Bohlmeijer ET. Effectiveness of online mindfulness-based interventions in improving mental
health: A review and meta-analysis of randomised controlled trials. Clin Psychol Rev 2016 Apr;45:102-114 [FREE Fulltext] [doi: 10.1016/j.cpr.2016.03.009] [Medline: 27111302]
Donker T, Blankers M, Hedman E, Ljótsson B, Petrie K, Christensen H. Economic evaluations of Internet interventions
for mental health: a systematic review. Psychol Med 2015 Dec;45(16):3357-3376. [doi: 10.1017/S0033291715001427][Medline: 26235445]
Romero-Sanchiz P, Nogueira-Arjona R, García-Ruiz A, Luciano JV, García CJ, Gili M, et al. Economic evaluation of aguided and unguided internet-based CBT intervention for major depression: Results from a multi-center, three-armed
randomized controlled trial conducted in primary care. PLoS One 2017;12(2):e0172741 [FREE Full text] [doi:10.1371/journal.pone.0172741] [Medline: 28241025]
Firth J, Torous J, Nicholas J, Carney R, Pratap A, Rosenbaum S, et al. The efficacy of smartphone-based mental healthinterventions for depressive symptoms: a meta-analysis of randomized controlled trials. World Psychiatry 2017
Oct;16(3):287-298 [FREE Full text] [doi: 10.1002/wps.20472] [Medline: 28941113]

http://formative.jmir.org/2019/1/e11509/

XSL• FO
RenderX

JMIR Formativ Res 2019 | vol. 3 | iss. 1 | e11509 | p. 10(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
16.
17.
18.
19.
20.
21.
22.
23.
24.

25.

26.

27.
28.

Goldin et al

Beck A, Steer R, Brown G. Beck Depression Inventory - Second Edition Manual. San Antonio, TX: The Psychological
Corporation; 1996.
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001
Sep;16(9):606-613 [FREE Full text] [Medline: 11556941]
Datica. 2019 Jan 09. URL: https://datica.com/ [accessed 2019-01-09] [WebCite Cache ID 75IeSsC1x]
Kabat-Zinn J. Full catastrophe living: using the wisdom of your body and mind to face stress, pain, and illness. New York,
NY: Dell Publishing; 1990.
Segal ZV, Williams JMG, Teasdale JD. Mindfulness-based Cognitive Therapy For Depression: A New Approach To
Preventing Relapse. New York: The Guilford Press; 2002.
Beck AT. Cognitive Therapy and the Emotional Disorders. USA: Penguin Group; 1979.
Jacobson N, Martell C, Dimidjian S. Behavioral activation treatment for depression: returning to contextual roots. ClinicalPsychology Science and Practice 2001 May 22;8(3):255-270. [doi: 10.1093/clipsy.8.3.255]
Wang Y, Gorenstein C. Psychometric properties of the Beck Depression Inventory-II: a comprehensive review. Rev Bras
Psiquiatr 2013;35(4):416-431 [FREE Full text] [doi: 10.1590/1516-4446-2012-1048] [Medline: 24402217]
Kayrouz R, Dear BF, Kayrouz B, Karin E, Gandy M, Titov N. Meta-analysis of the efficacy and acceptability ofcognitive-behavioural therapy for Arab adult populations experiencing anxiety, depression or post-traumatic stress disorder.
Cogn Behav Ther 2018 May 01:1-19. [doi: 10.1080/16506073.2018.1445124] [Medline: 29714106]
Watts S, Mackenzie A, Thomas C, Griskaitis A, Mewton L, Williams A, et al. CBT for depression: a pilot RCT comparing
mobile phone vs. computer. BMC Psychiatry 2013;13:49 [FREE Full text] [doi: 10.1186/1471-244X-13-49] [Medline:
23391304]
Hoermann S, McCabe KL, Milne DN, Calvo RA. Application of Synchronous Text-Based Dialogue Systems in Mental
Health Interventions: Systematic Review. J Med Internet Res 2017 Jul 21;19(8):e267 [FREE Full text] [doi:10.2196/jmir.7023] [Medline: 28784594]
Rodda S, Lubman DI. Characteristics of gamblers using a national online counselling service for problem gambling. J
Gambl Stud 2014 Jun;30(2):277-289. [doi: 10.1007/s10899-012-9352-7] [Medline: 23297169]
Donker T, Batterham PJ, Warmerdam L, Bennett K, Bennett A, Cuijpers P, et al. Predictors and moderators of response tointernet-delivered Interpersonal Psychotherapy and Cognitive Behavior Therapy for depression. J Affect Disord 2013
Oct;151(1):343-351. [doi: 10.1016/j.jad.2013.06.020] [Medline: 23953024]

Abbreviations
ANOVA: analysis of variance
BDI-II: Beck Depressive Inventory-II
CBT: cognitive behavioral therapy
HIPAA: Health Insurance Portability and Accountability Act
PHQ-9: Patient Health Questionnaire 9-item version
RCT: randomized controlled trial
WHO: World Health Organization

Edited by G Eysenbach; submitted 06.07.18; peer-reviewed by S Hatcher, M Gandy, P Romero-Sanchiz, J Nicholas; comments toauthor 14.08.18; revised version received 12.10.18; accepted 10.12.18; published 22.01.19
Please cite as:Goldin PR, Lindholm R, Ranta K, Hilgert O, Helteenvuori T, Raevuori A
Feasibility of a Therapist-Supported, Mobile Phone–Delivered Online Intervention for Depression: Longitudinal Observational StudyJMIR Formativ Res 2019;3(1):e11509
URL: http://formative.jmir.org/2019/1/e11509/
doi: 10.2196/11509
PMID:©Philippe R Goldin, Riku Lindholm, Kristian Ranta, Outi Hilgert, Tiia Helteenvuori, Anu Raevuori. Originally published in
JMIR Formative Research (http://formative.jmir.org), 22.01.2019. This is an open-access article distributed under the terms of
the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly
cited. The complete bibliographic information, a link to the original publication on http://formative.jmir.org, as well as thiscopyright and license information must be included.

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