Symptom Reduction and Engagement in a Cognitive-Behavioral Mobile Phone App: A Study of User Profiling to Determine Prognostic Indicators

[1]  W. Lutz,et al.  Movement-based patient-therapist attunement in psychological therapy and its association with early change , 2022, Digital health.

[2]  W. Lutz,et al.  Measurement-Based and Data-Informed Psychological Therapy. , 2021, Annual review of clinical psychology.

[3]  J. Brewer,et al.  Analyzing the Impact of Mobile App Engagement on Mental Health Outcomes: Secondary Analysis of the Unwinding Anxiety Program , 2021, Journal of medical Internet research.

[4]  N. Kazantzis,et al.  Editorial: Contemporary Issues in Defining the Mechanisms of Cognitive Behavior Therapy , 2021, Frontiers in Psychiatry.

[5]  S. Schueller,et al.  User Experience, Engagement, and Popularity in Mental Health Apps: Secondary Analysis of App Analytics and Expert App Reviews , 2021, JMIR human factors.

[6]  Seunghyun Kim,et al.  Where Is the Age of Digitalization Heading? The Meaning, Characteristics, and Implications of Contemporary Digital Transformation , 2021, Sustainability.

[7]  D. Dorstyn,et al.  Mental health apps for adolescents and young adults: A systematic review of randomised controlled trials , 2021 .

[8]  Simon B. Goldberg,et al.  Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials , 2021, PLOS digital health.

[9]  N. Kazantzis,et al.  A Comprehensive Model of Homework in Cognitive Behavior Therapy , 2021, Cognitive Therapy and Research.

[10]  W. Lutz,et al.  Prospective evaluation of a clinical decision support system in psychological therapy. , 2021, Journal of consulting and clinical psychology.

[11]  Elisa Infanti,et al.  Mobile Apps That Promote Emotion Regulation, Positive Mental Health, and Well-being in the General Population: Systematic Review and Meta-analysis , 2021, JMIR mental health.

[12]  A. Catarino,et al.  Depression subtypes and their response to cognitive behavioral therapy: A latent transition analysis , 2021, Depression and anxiety.

[13]  F. Gunning,et al.  Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement , 2021, npj Digital Medicine.

[14]  S. Hofmann,et al.  Engagement with smartphone-delivered behavioural activation interventions: a study of the MoodMission smartphone application , 2020, Behavioural and Cognitive Psychotherapy.

[15]  P. Bastani,et al.  The effects of mobile apps on stress, anxiety, and depression: overview of systematic reviews , 2020, International Journal of Technology Assessment in Health Care.

[16]  B. Muthén,et al.  Latent transition analysis with random intercepts (RI-LTA). , 2020, Psychological methods.

[17]  Christine D. Wilson-Mendenhall,et al.  Testing the Efficacy of a Multicomponent, Self-Guided, Smartphone-Based Meditation App: Three-Armed Randomized Controlled Trial , 2020, JMIR mental health.

[18]  N. Humphrey,et al.  Latent Class Analysis of Mental Health in Middle Childhood: Evidence for the Dual-Factor Model , 2020, School Mental Health.

[19]  A. Blackwell,et al.  Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling , 2020, Psychological Medicine.

[20]  W. Lutz,et al.  Patterns of change and their relationship to outcome and follow-up in group and individual psychotherapy for depression. , 2020, Journal of consulting and clinical psychology.

[21]  C. Ruggero,et al.  eHealth to redress psychotherapy access barriers both new and old: A review of reviews and meta-analyses. , 2020 .

[22]  J. Torous,et al.  Smartphone apps for the treatment of mental health conditions: status and considerations. , 2020, Current opinion in psychology.

[23]  R. Orji,et al.  Insights from user reviews to improve mental health apps , 2020, Health Informatics J..

[24]  Y. Byrow,et al.  Perceptions of mental health and perceived barriers to mental health help-seeking amongst refugees: A systematic review. , 2019, Clinical psychology review.

[25]  Wolfgang Lutz,et al.  Towards integrating personalized feedback research into clinical practice: Development of the Trier Treatment Navigator (TTN). , 2019, Behaviour research and therapy.

[26]  Amit Baumel,et al.  Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis , 2019, Journal of medical Internet research.

[27]  N. Rickard,et al.  Engagement with a cognitive behavioural therapy mobile phone app predicts changes in mental health and wellbeing: MoodMission , 2019, Australian Psychologist.

[28]  John F. Hunter,et al.  Use of Digital Mental Health for Marginalized and Underserved Populations , 2019, Current Treatment Options in Psychiatry.

[29]  M. Larimer,et al.  Transitions in drinking behaviors across the college years: A latent transition analysis. , 2019, Addictive behaviors.

[30]  John Torous,et al.  User Engagement in Mental Health Apps: A Review of Measurement, Reporting, and Validity. , 2019, Psychiatric services.

[31]  M. Furlong,et al.  A latent transition analysis of the longitudinal stability of dual-factor mental health in adolescence. , 2019, Journal of school psychology.

[32]  W. Assendelft,et al.  eHealth Apps Replacing or Complementing Health Care Contacts: Scoping Review on Adverse Effects , 2019, Journal of medical Internet research.

[33]  N. Rickard,et al.  Development and Pilot Evaluation of Smartphone-Delivered Cognitive Behavior Therapy Strategies for Mood- and Anxiety-Related Problems: MoodMission , 2018, Cognitive and Behavioral Practice.

[34]  David Bakker,et al.  A randomized controlled trial of three smartphone apps for enhancing public mental health. , 2018, Behaviour research and therapy.

[35]  S. Hollon,et al.  Demographic and clinical predictors of response to internet-enabled cognitive–behavioural therapy for depression and anxiety , 2018, BJPsych open.

[36]  M. Paulus,et al.  Predicting Barriers to Treatment for Depression in a U.S. National Sample: A Cross-Sectional, Proof-of-Concept Study. , 2018, Psychiatric services.

[37]  John Torous,et al.  Clinical review of user engagement with mental health smartphone apps: evidence, theory and improvements , 2018, Evidence Based Journals.

[38]  D. Clark Realizing the Mass Public Benefit of Evidence-Based Psychological Therapies: The IAPT Program. , 2018, Annual review of clinical psychology.

[39]  David Bakker,et al.  Engagement in mobile phone app for self-monitoring of emotional wellbeing predicts changes in mental health: MoodPrism. , 2018, Journal of affective disorders.

[40]  Alexander Mertens,et al.  Prevalence of Health App Use Among Older Adults in Germany: National Survey , 2018, JMIR mHealth and uHealth.

[41]  D. Silove,et al.  Twelve-month trajectories of depressive and anxiety symptoms and associations with traumatic exposure and ongoing adversities: a latent trajectory analysis of a community cohort exposed to severe conflict in Sri Lanka , 2017, Translational Psychiatry.

[42]  Martin Hautzinger,et al.  Defining and Predicting Patterns of Early Response in a Web-Based Intervention for Depression , 2017, Journal of medical Internet research.

[43]  John Torous,et al.  Needed Innovation in Digital Health and Smartphone Applications for Mental Health: Transparency and Trust. , 2017, JAMA psychiatry.

[44]  J. Sundquist,et al.  Longitudinal trends in self-reported anxiety. Effects of age and birth cohort during 25 years , 2017, BMC Psychiatry.

[45]  Gerhard Andersson,et al.  Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms: A Meta-analysis of Individual Participant Data , 2017, JAMA psychiatry.

[46]  K. Johansson,et al.  Differences in motivation and adherence to a prescribed assignment after face-to-face and online psychoeducation: an experimental study , 2017, BMC psychology.

[47]  David C. Atkins,et al.  The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial , 2016, Journal of medical Internet research.

[48]  A. Astell,et al.  Cognitive Behavior Therapy for Anxious and Depressed Youth: Improving Homework Adherence Through Mobile Technology , 2016, JMIR research protocols.

[49]  A. Memon,et al.  Perceived barriers to accessing mental health services among black and minority ethnic (BME) communities: a qualitative study in Southeast England , 2016, The Lancet.

[50]  G. Andersson,et al.  Does Internet-based guided-self-help for depression cause harm? An individual participant data meta-analysis on deterioration rates and its moderators in randomized controlled trials , 2016, Psychological Medicine.

[51]  Craig Whittington,et al.  Quantity and Quality of Homework Compliance: A Meta-Analysis of Relations With Outcome in Cognitive Behavior Therapy. , 2016, Behavior therapy.

[52]  David W. Bates,et al.  Usability of Commercially Available Mobile Applications for Diverse Patients , 2016, Journal of General Internal Medicine.

[53]  N. Rickard,et al.  Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments , 2016, JMIR mental health.

[54]  Ricardo Araya,et al.  Computerised cognitive behaviour therapy (cCBT) as treatment for depression in primary care (REEACT trial): large scale pragmatic randomised controlled trial , 2016, BMJ : British Medical Journal.

[55]  Richard B. Fletcher,et al.  Pessimism and Homework in CBT for Depression. , 2015, Journal of clinical psychology.

[56]  S. Landau,et al.  Anxiety and anxious-depression in Parkinson's disease over a 4-year period: a latent transition analysis , 2015, Psychological Medicine.

[57]  H. Uchida,et al.  Language Barriers and Access to Psychiatric Care: A Systematic Review. , 2015, Psychiatric services.

[58]  S. Gilbody,et al.  Early changes, attrition, and dose-response in low intensity psychological interventions. , 2014, The British journal of clinical psychology.

[59]  James F. Boswell,et al.  Patterns of early change and their relationship to outcome and early treatment termination in patients with panic disorder. , 2014, Journal of consulting and clinical psychology.

[60]  Valerie Møller,et al.  How Does Subjective Well-Being Evolve with Age? A Literature Review , 2013, SSRN Electronic Journal.

[61]  Alice T. Sawyer,et al.  The Efficacy of Cognitive Behavioral Therapy: A Review of Meta-analyses , 2012, Cognitive Therapy and Research.

[62]  Lena Sanci,et al.  Self-monitoring Using Mobile Phones in the Early Stages of Adolescent Depression: Randomized Controlled Trial , 2012, Journal of medical Internet research.

[63]  Derek Richards,et al.  Computer-based psychological treatments for depression: a systematic review and meta-analysis. , 2012, Clinical psychology review.

[64]  B. A. Tanner,et al.  Validity of Global Physical and Emotional SUDS , 2012, Applied psychophysiology and biofeedback.

[65]  John A Updegraff,et al.  Mindfulness and its relationship to emotional regulation. , 2012, Emotion.

[66]  Peter Bühlmann,et al.  MissForest - non-parametric missing value imputation for mixed-type data , 2011, Bioinform..

[67]  Leanne M. Casey,et al.  Dropout from Internet-based treatment for psychological disorders. , 2010, The British journal of clinical psychology.

[68]  Craig Whittington,et al.  Meta‐Analysis of Homework Effects in Cognitive and Behavioral Therapy: A Replication and Extension , 2010 .

[69]  B. Olatunji,et al.  Emotion Regulation and the Anxiety Disorders: An Integrative Review , 2010, Journal of psychopathology and behavioral assessment.

[70]  Thomas L. Patterson,et al.  The Relationship Between Homework Compliance and Therapy Outcomes: An Updated Meta-Analysis , 2010, Cognitive Therapy and Research.

[71]  Megan E. Patrick,et al.  Latent Transition Analysis: Benefits of a Latent Variable Approach to Modeling Transitions in Substance Use , 2010, Journal of drug issues.

[72]  B. Löwe,et al.  A brief measure for assessing generalized anxiety disorder: the GAD-7. , 2006, Archives of internal medicine.

[73]  Frank P. Deane,et al.  Using Homework Assignments in Cognitive Behavior Therapy , 2005 .

[74]  Helena C Kraemer,et al.  Centring in regression analyses: a strategy to prevent errors in statistical inference , 2004, International journal of methods in psychiatric research.

[75]  L. A. Goodman Applied Latent Class Analysis: Latent Class Analysis: The Empirical Study of Latent Types, Latent Variables, and Latent Structures , 2002 .

[76]  F. Deane,et al.  Concluding causation from correlation: comment on Burns and Spangler (2000). , 2001, Journal of consulting and clinical psychology.

[77]  R. Spitzer,et al.  The PHQ-9 , 2001, Journal of General Internal Medicine.

[78]  S. Heidrich Self-Discrepancy Across the Life Span , 1999 .

[79]  H Orn,et al.  Help-Seeking for Psychiatric Disorders , 1997, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[80]  Congcong WEN,et al.  Random intercept latent transition analysis (RI-LTA): Separating the between-subject variation from the within-subject variation , 2021, Advances in Psychological Science.

[81]  James R. Andretta,et al.  The impact of stress latent class membership and transitions on statutory service and alcohol use in adolescents across 33 months. , 2019, Journal of adolescence.

[82]  Jodi M. Gonzalez,et al.  How the relationship of attitudes toward mental health treatment and service use differs by age, gender, ethnicity/race and education , 2009, Social Psychiatry and Psychiatric Epidemiology.