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van Mierlo T, Rondina R, Fournier R. Nudges and Prompts Increase Engagement in Self-Guided Digital Health Treatment for Depression and Anxiety: Results From a 3-Arm Randomized Controlled Trial. JMIR Form Res 2024; 8:e52558. [PMID: 38592752 DOI: 10.2196/52558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/04/2024] [Accepted: 02/13/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Accessible and effective approaches to mental health treatment are important because of common barriers such as cost, stigma, and provider shortage. The effectiveness of self-guided treatment is well established, and its use has intensified because of the COVID-19 pandemic. Engagement remains important as dose-response relationships have been observed. Platforms such as Facebook (Meta Platform, Inc), LinkedIn (Microsoft Corp), and X Corp (formerly known as Twitter, Inc) use principles of behavioral economics to increase engagement. We hypothesized that similar concepts would increase engagement in self-guided digital health. OBJECTIVE This 3-arm randomized controlled trial aimed to test whether members of 2 digital self-health courses for anxiety and depression would engage with behavioral nudges and prompts. Our primary hypothesis was that members would click on 2 features: tips and a to-do checklist. Our secondary hypothesis was that members would prefer to engage with directive tips in arm 2 versus social proof and present bias tips in arm 3. Our tertiary hypothesis was that rotating tips and a to-do checklist would increase completion rates. The results of this study will form a baseline for future artificial intelligence-directed research. METHODS Overall, 13,224 new members registered between November 2021 and May 2022 for Evolution Health's self-guided treatment courses for anxiety and depression. The control arm featured a member home page without nudges or prompts. Arm 2 featured a home page with a tip-of-the-day section. Arm 3 featured a home page with a tip-of-the-day section and a to-do checklist. The research protocol for this study was published in JMIR Research Protocols on August 15, 2022. RESULTS Arm 3 had significantly younger members (F2,4564=40.97; P<.001) and significantly more female members (χ24=92.2; P<.001) than the other 2 arms. Control arm members (1788/13,224, 13.52%) completed an average of 1.5 course components. Arm 2 members (865/13,224, 6.54%) clicked on 5% of tips and completed an average of 1.8 course components. Arm 3 members (1914/13,224, 14.47%) clicked on 5% of tips, completed 2.7 of 8 to-do checklist items, and completed an average of 2.11 course components. Completion rates in arm 2 were greater than those in arm 1 (z score=3.37; P<.001), and completion rates in arm 3 were greater than those in arm 1 (z score=12.23; P<.001). Engagement in all 8 components in arm 3 was higher than that in arm 2 (z score=1.31; P<.001). CONCLUSIONS Members engaged with behavioral nudges and prompts. The results of this study may be important because efficacy is related to increased engagement. Due to its novel approach, the outcomes of this study should be interpreted with caution and used as a guideline for future research in this nascent field. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.2196/37231.
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Affiliation(s)
| | - Renante Rondina
- Rotman School of Managment, University of Toronto, Toronto, ON, Canada
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Alfaro AJ, Wielgosz J, Kuhn E, Carlson C, Gould CE. Determinants and outcome correlates of engagement with a mobile mental health intervention for depression and anxiety in middle-aged and older adults. J Clin Psychol 2024; 80:509-521. [PMID: 38157399 DOI: 10.1002/jclp.23636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 11/13/2023] [Accepted: 12/15/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVES To examine baseline factors (i.e., age, gender, mobile device proficiency, sensory impairment) associated with app engagement in a 12-week mental health app intervention and to explore whether app engagement predicts changes in depression and anxiety symptoms among middle-aged and older adults. METHOD Mobile device proficiency, sensory impairment, depression, and anxiety symptoms were measured using questionnaires. App engagement was defined by metrics characterizing the core intervention features (i.e., messages sent to therapist, mindfulness meditation minutes, action tasks completed). Multiple regressions and multilevel models were conducted. RESULTS Forty-nine participants (M age = 57.40, SD = 11.09 years) enrolled. Women (β = .35, p < .05) and participants with less sensory impairment completed more action tasks (β = -.40, p < .05). Depressive and anxiety symptoms measured within the app declined significantly across treatment. Clinical significant improvements were observed for depression in 48.9% and for anxiety in 40% of participants. App engagement metrics were not predictive of depression or anxiety symptoms, either incrementally in time-lagged models or cumulatively in hierarchical linear regression analyses. CONCLUSION App engagement is multifaceted; participants engaged differently by gender and ability. Participation in this digital mental health intervention reduced depression and anxiety symptoms, but these findings should be interpreted with caution as the study did not include a control condition. Our findings underscore the importance of considering individual factors that may influence use of a digital mental health intervention.
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Affiliation(s)
- Ana J Alfaro
- Geriatric Research Education and Clinical Center (GRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Joseph Wielgosz
- National Center for Posttraumatic Stress Disorder, Dissemination & Training Division, Veterans Affairs Palo Alto Health Care System, Menlo Park, California, USA
| | - Eric Kuhn
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
- National Center for Posttraumatic Stress Disorder, Dissemination & Training Division, Veterans Affairs Palo Alto Health Care System, Menlo Park, California, USA
| | - Chalise Carlson
- Geriatric Research Education and Clinical Center (GRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA
| | - Christine E Gould
- Geriatric Research Education and Clinical Center (GRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
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Chiauzzi E, Williams A, Mariano TY, Pajarito S, Robinson A, Kirvin-Quamme A, Forman-Hoffman V. Demographic and clinical characteristics associated with anxiety and depressive symptom outcomes in users of a digital mental health intervention incorporating a relational agent. BMC Psychiatry 2024; 24:79. [PMID: 38291369 PMCID: PMC10826101 DOI: 10.1186/s12888-024-05532-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 01/17/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Digital mental health interventions (DMHIs) may reduce treatment access issues for those experiencing depressive and/or anxiety symptoms. DMHIs that incorporate relational agents may offer unique ways to engage and respond to users and to potentially help reduce provider burden. This study tested Woebot for Mood & Anxiety (W-MA-02), a DMHI that employs Woebot, a relational agent that incorporates elements of several evidence-based psychotherapies, among those with baseline clinical levels of depressive or anxiety symptoms. Changes in self-reported depressive and anxiety symptoms over 8 weeks were measured, along with the association between each of these outcomes and demographic and clinical characteristics. METHODS This exploratory, single-arm, 8-week study of 256 adults yielded non-mutually exclusive subsamples with either clinical levels of depressive or anxiety symptoms at baseline. Week 8 Patient Health Questionnaire-8 (PHQ-8) changes were measured in the depressive subsample (PHQ-8 ≥ 10). Week 8 Generalized Anxiety Disorder-7 (GAD-7) changes were measured in the anxiety subsample (GAD-7 ≥ 10). Demographic and clinical characteristics were examined in association with symptom changes via bivariate and multiple regression models adjusted for W-MA-02 utilization. Characteristics included age, sex at birth, race/ethnicity, marital status, education, sexual orientation, employment status, health insurance, baseline levels of depressive and anxiety symptoms, and concurrent psychotherapeutic or psychotropic medication treatments during the study. RESULTS Both the depressive and anxiety subsamples were predominantly female, educated, non-Hispanic white, and averaged 38 and 37 years of age, respectively. The depressive subsample had significant reductions in depressive symptoms at Week 8 (mean change =-7.28, SD = 5.91, Cohen's d = -1.23, p < 0.01); the anxiety subsample had significant reductions in anxiety symptoms at Week 8 (mean change = -7.45, SD = 5.99, Cohen's d = -1.24, p < 0.01). No significant associations were found between sex at birth, age, employment status, educational background and Week 8 symptom changes. Significant associations between depressive and anxiety symptom outcomes and sexual orientation, marital status, concurrent mental health treatment, and baseline symptom severity were found. CONCLUSIONS The present study suggests early promise for W-MA-02 as an intervention for depression and/or anxiety symptoms. Although exploratory in nature, this study revealed potential user characteristics associated with outcomes that can be investigated in future studies. TRIAL REGISTRATION This study was retrospectively registered on ClinicalTrials.gov (#NCT05672745) on January 5th, 2023.
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Affiliation(s)
- Emil Chiauzzi
- Woebot Health, 535 Mission Street, 14th Floor, San Francisco, CA, 94105, USA
| | - Andre Williams
- Woebot Health, 535 Mission Street, 14th Floor, San Francisco, CA, 94105, USA
| | - Timothy Y Mariano
- Woebot Health, 535 Mission Street, 14th Floor, San Francisco, CA, 94105, USA
- RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, USA
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Sarah Pajarito
- Woebot Health, 535 Mission Street, 14th Floor, San Francisco, CA, 94105, USA
| | - Athena Robinson
- Woebot Health, 535 Mission Street, 14th Floor, San Francisco, CA, 94105, USA
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Dzubur E, Yu J, Hoffman J, Painter S, James R, Shah B. The Effect of a Digital Mental Health Program on Anxiety and Depression Symptoms: Retrospective Analysis of Clinical Severity. JMIR Form Res 2023; 7:e36596. [PMID: 37788069 PMCID: PMC10582814 DOI: 10.2196/36596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 05/03/2022] [Accepted: 02/19/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Evidence-based digital health programs have shown efficacy in being primary tools to improve emotional and mental health, as well as offering supplementary support to individuals undergoing psychotherapy for anxiety, depression, and other mental health disorders. However, information is lacking about the dose response to digital mental health interventions. OBJECTIVE The objective of the study was to examine the effect of time in program and program usage on symptom change among individuals enrolled in a real-world comprehensive digital mental health program (myStrength) who are experiencing severe anxiety or depression. METHODS Eligible participants (N=18,626) were adults aged 18 years and older who were enrolled in myStrength for at least four weeks as part of their employee wellness benefit program, who completed baseline, the 2-week, 2-month, and 6-month surveys querying symptoms of anxiety (Generalized Anxiety Disorder-7 [GAD-7]) and depression (Patient Health Questionnaire-9 [PHQ-9]). Linear growth curve models were used to analyze the effect of average weekly program usage on subsequent GAD-7 and PHQ-9 scores for participants with scores indicating severe anxiety (GAD-7≥15) or depression (PHQ-9≥15). All models were adjusted for baseline score and demographics. RESULTS Participants in the study (N=1519) were 77.4% female (1176/1519), had a mean age of 45 years (SD 14 years), and had an average enrollment time of 3 months. At baseline, participants reported an average of 9.39 (SD 6.04) on the GAD-7 and 11.0 (SD 6.6) on the PHQ-9. Those who reported 6-month results had an average of 8.18 (SD 6.15) on the GAD-7 and 9.18 (SD 6.79) on the PHQ-9. Participants with severe scores (n=506) experienced a significant improvement of 2.97 (SE 0.35) and 3.97 (SE 0.46) at each time point for anxiety and depression, respectively (t=-8.53 and t=-8.69, respectively; Ps<.001). Those with severe baseline scores also saw a reduction of 0.27 (SE 0.08) and 0.25 (SE 0.09) points in anxiety and depression, respectively, for each additional program activity per week (t=-3.47 and t=-2.66, respectively; Ps<.05). CONCLUSIONS For participants with severe baseline scores, the study found a clinically significant reduction of approximately 9 points for anxiety and 12 points for depression after 6 months of enrollment, suggesting that interventions targeting mental health must maintain active, ongoing engagement when symptoms are present and be available as a continuous resource to maximize clinical impact, specifically in those experiencing severe anxiety or depression. Moreover, a dosing effect was shown, indicating improvement in outcomes among participants who engaged with the program every other day for both anxiety and depression. This suggests that digital mental health programs that provide both interesting and evidence-based activities could be more successful in further improving mental health outcomes.
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Affiliation(s)
| | - Jessica Yu
- Teladoc Health, Purchase, NY, United States
| | | | | | | | - Bimal Shah
- Duke University Medical School, Durham, NC, United States
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5
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Camacho E, Chang SM, Currey D, Torous J. The impact of guided versus supportive coaching on mental health app engagement and clinical outcomes. Health Informatics J 2023; 29:14604582231215872. [PMID: 38112116 DOI: 10.1177/14604582231215872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
Although mobile mental health apps have the unique potential to increase access to care, evidence reveals engagement is low unless coupled with coaching. However, most coaching protocols are limited in their scalability. This study assesses how human support and guidance from a Digital Navigator (DN), a scalable coach, can impact mental health app engagement and effectiveness on anxiety and depressive symptoms. This study aims to detach components of coaching, specifically personalized recommendations versus general support, to inform scalability of coaching models for mental health apps. 156 participants were split into the DN Guide versus DN Support groups for the 6-week study. Both groups utilized the mindLAMP app for the duration of the study and had equal time with the DN, but the Guide group received personalized app recommendations. The Guide group completed significantly more activities than the Support group. 34% (49/139) of all participants saw a 25% decrease in PHQ-9 scores and 38% (53/141) saw a 25% decrease in GAD-7 scores. These findings show mental health apps, especially when supported by DNs, can reduce depression and anxiety symptoms when coupled with coaching, suggesting a feasible path for large-scale deployment.
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Affiliation(s)
- Erica Camacho
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sarah M Chang
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Danielle Currey
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - John Torous
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
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6
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Haller K, Becker P, Niemeyer H, Boettcher J. Who benefits from guided internet-based interventions? A systematic review of predictors and moderators of treatment outcome. Internet Interv 2023; 33:100635. [PMID: 37449052 PMCID: PMC10336165 DOI: 10.1016/j.invent.2023.100635] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 05/23/2023] [Accepted: 06/07/2023] [Indexed: 07/18/2023] Open
Abstract
To our knowledge, no systematic review has been conducted on predictors or moderators of treatment outcome across diagnoses in guided internet-based interventions (IBIs) for adults. To identify who benefits from this specific format and therein inform future research on improving patient-treatment fit, we aimed to aggregate results of relevant studies. 2100 articles, identified by searching the databases PsycInfo, Ovid Medline, and Pubmed and through snowballing, were screened in April/May 2021 and October 2022. Risk of bias and intra- and interrater reliability were assessed. Variables were grouped by predictor category, then synthesized using vote counting based on direction of effect. N = 60 articles were included in the review. Grouping resulted in 88 predictors/moderators, of which adherence, baseline symptoms, education, age, and gender were most frequently assessed. Better adherence, treatment credibility, and working alliance emerged as conclusive predictors/moderators for better outcome, whereas higher baseline scores predicted more reliable change but higher post-treatment symptoms. Results of all other predictors/moderators were inconclusive or lacked data. Our review highlights that it is currently difficult to predict, across diagnoses, who will benefit from guided IBIs. Further rigorous research is needed to identify predictors and moderators based on a sufficient number of studies. PROSPERO registration: CRD42021242305.
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Affiliation(s)
- Katrin Haller
- Clinical Psychological Interventions, Freie Universität Berlin, Berlin, Germany
- Clinical Psychology and Psychotherapy, Psychologische Hochschule Berlin, Berlin, Germany
| | - Pauline Becker
- Clinical Psychology and Psychotherapy, Psychologische Hochschule Berlin, Berlin, Germany
| | - Helen Niemeyer
- Clinical Psychological Interventions, Freie Universität Berlin, Berlin, Germany
| | - Johanna Boettcher
- Clinical Psychology and Psychotherapy, Psychologische Hochschule Berlin, Berlin, Germany
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Cohen ZD, Schueller SM. Expanding, improving, and understanding behaviour research and therapy through digital mental health. Behav Res Ther 2023; 167:104358. [PMID: 37418857 DOI: 10.1016/j.brat.2023.104358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2023]
Affiliation(s)
- Zachary D Cohen
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, USA.
| | - Stephen M Schueller
- Department of Psychological Science, University of California, Irvine, USA; Department of Informatics, University of California, Irvine, USA
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Toyomoto R, Sakata M, Yoshida K, Luo Y, Nakagami Y, Uwatoko T, Shimamoto T, Sahker E, Tajika A, Suga H, Ito H, Sumi M, Muto T, Ito M, Ichikawa H, Ikegawa M, Shiraishi N, Watanabe T, Watkins ER, Noma H, Horikoshi M, Iwami T, Furukawa TA. Prognostic factors and effect modifiers for personalisation of internet-based cognitive behavioural therapy among university students with subthreshold depression: A secondary analysis of a factorial trial. J Affect Disord 2023; 322:156-162. [PMID: 36379323 DOI: 10.1016/j.jad.2022.11.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/12/2022] [Accepted: 11/07/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Internet-cognitive behavioural therapy (iCBT) for depression can include multiple components. This study explored depressive symptom improvement prognostic factors (PFs) and effect modifiers (EMs) for five common iCBT components including behavioural activation, cognitive restructuring, problem solving, self-monitoring, and assertion training. METHODS We used data from a factorial trial of iCBT for subthreshold depression among Japanese university students (N = 1093). The primary outcome was the change in PHQ-9 scores at 8 weeks from baseline. Interactions between each component and various baseline characteristics were estimated using a mixed-effects model for repeated measures. We calculated multiplicity-adjusted p-values at 5 % false discovery rate using the Benjamini-Hochberg procedure. RESULTS After multiplicity adjustment, the baseline PHQ-9 total score emerged as a PF and exercise habits as an EM for self-monitoring (adjusted p-values <0.05). The higher the PHQ-9 total score at baseline (range: 5-14), the greater the decrease after 8 weeks. For each 5-point increase at baseline, the change from baseline to 8 weeks was bigger by 2.8 points. The more frequent the exercise habits (range: 0-2 points), the less effective the self-monitoring component. The difference in PHQ-9 change scores between presence or absence of self-monitoring was smaller by 0.94 points when the participant exercised one level more frequently. Additionally, the study suggested seven out of 36 PFs and 14 out of 160 EMs examined were candidates for future research. LIMITATIONS Generalizability is limited to university students with subthreshold depression. CONCLUSIONS These results provide some helpful information for the future development of individualized iCBT algorithms for depression.
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Affiliation(s)
- Rie Toyomoto
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan.
| | - Masatsugu Sakata
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
| | - Kazufumi Yoshida
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
| | - Yan Luo
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
| | - Yukako Nakagami
- Agency for Student Support and Disability Resources, Kyoto University, Kyoto, Japan
| | - Teruhisa Uwatoko
- Department of Psychiatry, Kyoto University Hospital, Kyoto, Japan
| | - Tomonari Shimamoto
- Department of Preventive Services, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
| | - Ethan Sahker
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan; Population Health and Policy Research Unit, Medical Education Centre, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Aran Tajika
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
| | | | - Hiroshi Ito
- Ritsumeikan Medical Service Centre, Kyoto, Japan
| | | | - Takashi Muto
- Faculty of Psychology, Doshisha University, Kyoto, Japan
| | - Masataka Ito
- Department of Life Design, Biwako-Gakuin College, Higashiomi, Japan
| | - Hiroshi Ichikawa
- Department of Medical Life Systems, Doshisha University, Kyoto, Japan
| | - Masaya Ikegawa
- Department of Medical Life Systems, Doshisha University, Kyoto, Japan
| | - Nao Shiraishi
- Department of Psychiatry and Cognitive-Behavioural Medicine, Nagoya City University Graduate School of Medical Science, Nagoya, Japan
| | - Takafumi Watanabe
- Department of Psychiatry and Cognitive-Behavioural Medicine, Nagoya City University Graduate School of Medical Science, Nagoya, Japan
| | | | - Hisashi Noma
- Institute of Statistical Mathematics, Tokyo, Japan
| | - Masaru Horikoshi
- National Centre of Neurology and Psychiatry/National Centre for Cognitive Behaviour Therapy and Research, Tokyo, Japan
| | - Taku Iwami
- Department of Preventive Services, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
| | - Toshi A Furukawa
- Department of Health Promotion and Human Behaviour, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan
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Abstract
Despite the growing prevalence of mental health-related smartphone apps, low real-world engagement has prevented these apps from transforming the mental health landscape. Integrating mental health apps into more traditional therapeutic models appears to support better clinical outcomes, but also raises questions about the relationship between app engagement, the app itself, and the coach or clinician. This study explores patient app engagement patterns and the associated clinical outcomes gathered from piloting a digital clinic. Patients with anxiety or depression completed eight clinical visits and coach visits over a median of 83 days with a standard deviation of 17.25 days. Between clinical visits, patients completed therapeutic activities on the mindLAMP app. Mean PHQ-9 and GAD-7 scores decreased from the intake visit to both visit 4 and visit 8. Patients had high app engagement, but engagement did not correlate with outcomes. From intake visit to visit 4, the interaction effects indicate significant differences in the change of both PHQ-9 and GAD-7 depending on participants' average app satisfaction and clinician/coach satisfaction (as measured by WAI-SR) with engagement. Overall, results support the feasibility of incorporating an app into a hybrid clinic.
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Affiliation(s)
- Sarah Chang
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Lucy Gray
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - John Torous
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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Hudson G, Negbenose E, Neary M, Jansli SM, Schueller SM, Wykes T, Jilka S. Comparing Professional and Consumer Ratings of Mental Health Apps: Mixed Methods Study. JMIR Form Res 2022; 6:e39813. [PMID: 36149733 PMCID: PMC9547331 DOI: 10.2196/39813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Background As the number of mental health apps has grown, increasing efforts have been focused on establishing quality tailored reviews. These reviews prioritize clinician and academic views rather than the views of those who use them, particularly those with lived experiences of mental health problems. Given that the COVID-19 pandemic has increased reliance on web-based and mobile mental health support, understanding the views of those with mental health conditions is of increasing importance. Objective This study aimed to understand the opinions of people with mental health problems on mental health apps and how they differ from established ratings by professionals. Methods A mixed methods study was conducted using a web-based survey administered between December 2020 and April 2021, assessing 11 mental health apps. We recruited individuals who had experienced mental health problems to download and use 3 apps for 3 days and complete a survey. The survey consisted of the One Mind PsyberGuide Consumer Review Questionnaire and 2 items from the Mobile App Rating Scale (star and recommendation ratings from 1 to 5). The consumer review questionnaire contained a series of open-ended questions, which were thematically analyzed and using a predefined protocol, converted into binary (positive or negative) ratings, and compared with app ratings by professionals and star ratings from app stores. Results We found low agreement between the participants’ and professionals’ ratings. More than half of the app ratings showed disagreement between participants and professionals (198/372, 53.2%). Compared with participants, professionals gave the apps higher star ratings (3.58 vs 4.56) and were more likely to recommend the apps to others (3.44 vs 4.39). Participants’ star ratings were weakly positively correlated with app store ratings (r=0.32, P=.01). Thematic analysis found 11 themes, including issues of user experience, ease of use and interactivity, privacy concerns, customization, and integration with daily life. Participants particularly valued certain aspects of mental health apps, which appear to be overlooked by professional reviewers. These included functions such as the ability to track and measure mental health and providing general mental health education. The cost of apps was among the most important factors for participants. Although this is already considered by professionals, this information is not always easily accessible. Conclusions As reviews on app stores and by professionals differ from those by people with lived experiences of mental health problems, these alone are not sufficient to provide people with mental health problems with the information they desire when choosing a mental health app. App rating measures must include the perspectives of mental health service users to ensure ratings represent their priorities. Additional work should be done to incorporate the features most important to mental health service users into mental health apps.
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Affiliation(s)
- Georgie Hudson
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Division of Psychology and Language Sciences, University College London, London, United Kingdom
| | - Esther Negbenose
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Martha Neary
- Department of Psychological Science, University of California, Irvine, CA, United States
| | - Sonja M Jansli
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Stephen M Schueller
- Department of Psychological Science, University of California, Irvine, CA, United States
- Department of Informatics, University of California, Irvine, CA, United States
| | - Til Wykes
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Sagar Jilka
- Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Warwick Medical School, University of Warwick, Coventry, United Kingdom
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Matcham F, Carr E, White KM, Leightley D, Lamers F, Siddi S, Annas P, de Girolamo G, Haro JM, Horsfall M, Ivan A, Lavelle G, Li Q, Lombardini F, Mohr DC, Narayan VA, Penninx BWHJ, Oetzmann C, Coromina M, Simblett SK, Weyer J, Wykes T, Zorbas S, Brasen JC, Myin-Germeys I, Conde P, Dobson RJB, Folarin AA, Ranjan Y, Rashid Z, Cummins N, Dineley J, Vairavan S, Hotopf M. Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder. J Affect Disord 2022; 310:106-115. [PMID: 35525507 DOI: 10.1016/j.jad.2022.05.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/28/2022] [Accepted: 05/02/2022] [Indexed: 01/10/2023]
Abstract
BACKGROUND Remote sensing for the measurement and management of long-term conditions such as Major Depressive Disorder (MDD) is becoming more prevalent. User-engagement is essential to yield any benefits. We tested three hypotheses examining associations between clinical characteristics, perceptions of remote sensing, and objective user engagement metrics. METHODS The Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) study is a multicentre longitudinal observational cohort study in people with recurrent MDD. Participants wore a FitBit and completed app-based assessments every two weeks for a median of 18 months. Multivariable random effects regression models pooling data across timepoints were used to examine associations between variables. RESULTS A total of 547 participants (87.8% of the total sample) were included in the current analysis. Higher levels of anxiety were associated with lower levels of perceived technology ease of use; increased functional disability was associated with small differences in perceptions of technology usefulness and usability. Participants who reported higher system ease of use, usefulness, and acceptability subsequently completed more app-based questionnaires and tended to wear their FitBit activity tracker for longer. All effect sizes were small and unlikely to be of practical significance. LIMITATIONS Symptoms of depression, anxiety, functional disability, and perceptions of system usability are measured at the same time. These therefore represent cross-sectional associations rather than predictions of future perceptions. CONCLUSIONS These findings suggest that perceived usability and actual use of remote measurement technologies in people with MDD are robust across differences in severity of depression, anxiety, and functional impairment.
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Affiliation(s)
- F Matcham
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - E Carr
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - K M White
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - D Leightley
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - F Lamers
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - S Siddi
- Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain
| | - P Annas
- H. Lundbeck A/S, Valby, Denmark
| | - G de Girolamo
- IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - J M Haro
- Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain
| | - M Horsfall
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - A Ivan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - G Lavelle
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Q Li
- Janssen Research and Development, LLC, Titusville, NJ, USA
| | - F Lombardini
- Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain
| | - D C Mohr
- Center for Behavioral Intervention Technologies, Department of Preventative Medicine, Northwestern University, Chicago, IL, USA
| | - V A Narayan
- Janssen Research and Development, LLC, Titusville, NJ, USA
| | - B W H J Penninx
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - C Oetzmann
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - M Coromina
- Parc Sanitari Joan de Déu, Barcelona, Spain
| | - S K Simblett
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - J Weyer
- RADAR-CNS Patient Advisory Board
| | - T Wykes
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, London, UK
| | - S Zorbas
- RADAR-CNS Patient Advisory Board
| | | | - I Myin-Germeys
- Department for Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium
| | - P Conde
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - R J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - A A Folarin
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Y Ranjan
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Z Rashid
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - N Cummins
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - J Dineley
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; EIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany
| | - S Vairavan
- Janssen Research and Development, LLC, Titusville, NJ, USA
| | - M Hotopf
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, London, UK
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Rondina R, van Mierlo T, Fournier R. Testing Behavioral Nudges and Prompts in Digital Courses for Self-Guided Treatment of Depression and Anxiety, Protocol for 3-Arm Randomized Controlled Trial (Preprint). JMIR Res Protoc 2022; 11:e37231. [PMID: 35969446 PMCID: PMC9425166 DOI: 10.2196/37231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 05/26/2022] [Accepted: 06/30/2022] [Indexed: 11/13/2022] Open
Abstract
Background Despite showing strong evidence of positive outcomes, a common problem in the field of digital health is poor engagement and adherence. Non–health care, for-profit digital ventures, such as Facebook, LinkedIn, and Twitter, conduct behavioral experiments to increase user engagement. To our knowledge, digital health organizations have not published similar types of experiments in ad libitum environments, and there are limited published data indicating whether nudges and prompts can be leveraged to increase engagement with digital health interventions. Objective The main objective of our 3-arm randomized controlled trial is to test whether registered members in two well-established digital health courses for anxiety and depression will engage with four different types of nudges and prompts, and whether engaging with nudges and prompts increases engagement within the courses. Methods New members who register for the self-guided anxiety and depression courses on the Evolution Health platform will be randomized into 1 of 3 arms. The first control arm will feature a member home page without any behavioral nudges or prompts. The second arm will feature a member home page with a Tip-of-the-Day section containing directive content. Arm 3 will feature a member home page with a Tip-of-the-Day section containing social proof and present bias content. The third arm will also feature a to-do item checklist. Results The experiment was designed in August 2021 and was launched in November 2021. Initially, we will measure engagement with the tips and the to-do checklist by calculating the frequency of use by age and gender. If members do engage, we will then, according to age and gender, examine whether nudges and prompts result in higher course completion rates and whether specific types of prompts and nudges are more popular than others. Conclusions Our 3-arm randomized controlled trial will be the first to compare four distinct types of behavioral prompts and nudges in two self-guided digital health courses that were designed to treat mental health issues. We expect the results to generate insights into which types of behavioral prompts and nudges work best in the population. If they are shown to increase engagement, the insights will then be used to apply prompts and nudges to the platform’s addiction-focused courses. Based on the results of the experiment, the insights will be applied to using artificial intelligence to train the platform to recognize different usage patterns and provide specific engagement recommendations to stratified users. International Registered Report Identifier (IRRID) DERR1-10.2196/37231
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Affiliation(s)
- Renante Rondina
- Rotman School of Mangement, University of Toronto, Toronto, ON, Canada
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