Patient characteristics associated with retrospectively self-reported treatment outcomes following psychological therapy for anxiety or depressive disorders - a cohort of GLAD study participants

[1]  R. DeRubeis,et al.  The contribution of depressive ‘disorder characteristics’ to determinations of prognosis for adults with depression: an individual patient data meta-analysis , 2021, Psychological Medicine.

[2]  D. Kounali,et al.  How much change is enough? Evidence from a longitudinal study on depression in UK primary care , 2020, Psychological Medicine.

[3]  G. Breen,et al.  An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression. , 2020, The American journal of psychiatry.

[4]  A. Palmer,et al.  Emerging phenotyping strategies will advance our understanding of psychiatric genetics , 2020, Nature Neuroscience.

[5]  J. Potash,et al.  Minimal phenotyping yields genome-wide association signals of low specificity for major depression , 2020, Nature Genetics.

[6]  P. Cuijpers,et al.  The effects of fifteen evidence-supported therapies for adult depression: A meta-analytic review , 2020, Psychotherapy research : journal of the Society for Psychotherapy Research.

[7]  R. DeRubeis,et al.  Indicators of Prognosis Independent of Treatment for Adults with Depression in Primary Care, Going Beyond Baseline Symptom-Severity: A Systematic Review and Individual Patient Data Meta-Analysis , 2020 .

[8]  E. Vassos,et al.  The Genetic Links to Anxiety and Depression (GLAD) Study: Online recruitment into the largest recontactable study of depression and anxiety , 2019, Behaviour research and therapy.

[9]  N. Freemantle,et al.  Pharmacological treatments for generalised anxiety disorder: a systematic review and network meta-analysis , 2019, The Lancet.

[10]  Haniye Sadat Sajadi,et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 , 2018, The Lancet.

[11]  Y. Theodorakis,et al.  Aerobic exercise for adult patients with major depressive disorder in mental health services: A systematic review and meta‐analysis , 2018, Depression and anxiety.

[12]  S. Hollon,et al.  Risk factors for relapse and recurrence of depression in adults and how they operate: A four-phase systematic review and meta-synthesis , 2018, Clinical psychology review.

[13]  R. Marioni,et al.  Edinburgh Research Explorer Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways , 2022 .

[14]  J. Ioannidis,et al.  Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis , 2018, The Lancet.

[15]  D. McMillan,et al.  Case Complexity as a Guide for Psychological Treatment Selection , 2017, Journal of consulting and clinical psychology.

[16]  Gregory M. Garrison,et al.  Personality Disorders in Primary Care: Impact on Depression Outcomes Within Collaborative Care , 2017, Journal of primary care & community health.

[17]  David M. Evans,et al.  Collider scope: when selection bias can substantially influence observed associations , 2016, bioRxiv.

[18]  M. Crawford,et al.  Development and Psychometric Properties of the Standardized Assessment of Severity of Personality Disorder (SASPD). , 2017, Journal of personality disorders.

[19]  Glyn Lewis,et al.  Why are there discrepancies between depressed patients’ Global Rating of Change and scores on the Patient Health Questionnaire depression module? A qualitative study of primary care in England , 2017, BMJ Open.

[20]  N. Lindefors,et al.  Predicting Outcome in Internet-Based Cognitive Behaviour Therapy for Major Depression: A Large Cohort Study of Adult Patients in Routine Psychiatric Care , 2016, PloS one.

[21]  S. Pilling,et al.  Predicting treatment outcome in psychological treatment services by identifying latent profiles of patients. , 2016, Journal of affective disorders.

[22]  M. Hotopf,et al.  Clinical characteristics of patients assessed within an Improving Access to Psychological Therapies (IAPT) service: results from a naturalistic cohort study (Predicting Outcome Following Psychological Therapy; PROMPT) , 2016, BMC Psychiatry.

[23]  R. Kessler,et al.  Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder , 2016, Epidemiology and Psychiatric Sciences.

[24]  C. Sudlow,et al.  Challenges of linking to routine healthcare records in UK Biobank , 2015, Trials.

[25]  P. Moran,et al.  The impact of comorbid personality difficulties on response to IAPT treatment for depression and anxiety. , 2015, Behaviour research and therapy.

[26]  T. Peters,et al.  Minimal clinically important difference on the Beck Depression Inventory - II according to the patient's perspective , 2015, Psychological Medicine.

[27]  G. Myhr,et al.  Predicting who benefits most from cognitive-behavioral therapy for anxiety and depression. , 2014, Journal of clinical psychology.

[28]  R. DeRubeis,et al.  Effect of cognitive therapy with antidepressant medications vs antidepressants alone on the rate of recovery in major depressive disorder: a randomized clinical trial. , 2014, JAMA psychiatry.

[29]  T. Johnson,et al.  Influence of personality on the outcome of treatment in depression: systematic review and meta-analysis. , 2014, Journal of personality disorders.

[30]  S. Wisniewski,et al.  Clinical and Functional Outcomes of Patients Who Experience Partial Response to Citalopram: Secondary Analysis of STAR*D , 2014, Journal of psychiatric practice.

[31]  Zachary D. Cohen,et al.  The Personalized Advantage Index: Translating Research on Prediction into Individualized Treatment Recommendations. A Demonstration , 2014, PloS one.

[32]  L. Kriston,et al.  Risk factors for chronic depression--a systematic review. , 2011, Journal of affective disorders.

[33]  Gregory E Simon,et al.  Personalized medicine for depression: can we match patients with treatments? , 2010, The American journal of psychiatry.

[34]  A. Caspi,et al.  How common are common mental disorders? Evidence that lifetime prevalence rates are doubled by prospective versus retrospective ascertainment , 2009, Psychological Medicine.

[35]  R. DeRubeis,et al.  Prediction of response to medication and cognitive therapy in the treatment of moderate to severe depression. , 2009, Journal of consulting and clinical psychology.

[36]  M. Ferreira,et al.  Clinimetric Testing of Three Self-report Outcome Measures for Low Back Pain Patients in Brazil: Which One Is the Best? , 2008, Spine.

[37]  T. Johnson,et al.  Personality disorder and the outcome of depression: Meta-analysis of published studies , 2006, British Journal of Psychiatry.

[38]  D. Nyholt A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. , 2004, American journal of human genetics.

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

[40]  J. Cheverud,et al.  A simple correction for multiple comparisons in interval mapping genome scans , 2001, Heredity.

[41]  D A Bloch,et al.  Capturing the patient's view of change as a clinical outcome measure. , 1999, JAMA.

[42]  R. Kessler,et al.  The World Health Organization Composite International Diagnostic Interview short‐form (CIDI‐SF) , 1998 .

[43]  R. Brant Assessing proportionality in the proportional odds model for ordinal logistic regression. , 1990, Biometrics.

[44]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[45]  R. Spitzer,et al.  The PHQ-9: validity of a brief depression severity measure. , 2001, Journal of general internal medicine.