Sampling bias in an internet treatment trial for depression

Internet psychological interventions are efficacious and may reduce traditional access barriers. No studies have evaluated whether any sampling bias exists in these trials that may limit the translation of the results of these trials into real-world application. We identified 7999 potentially eligible trial participants from a community-based health cohort study and invited them to participate in a randomized controlled trial of an online cognitive behavioural therapy programme for people with depression. We compared those who consented to being assessed for trial inclusion with nonconsenters on demographic, clinical and behavioural indicators captured in the health study. Any potentially biasing factors were then assessed for their association with depression outcome among trial participants to evaluate the existence of sampling bias. Of the 35 health survey variables explored, only 4 were independently associated with higher likelihood of consenting—female sex (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.05–1.19), speaking English at home (OR 1.48, 95% CI 1.15–1.90) higher education (OR 1.67, 95% CI 1.46–1.92) and a prior diagnosis of depression (OR 1.37, 95% CI 1.22–1.55). The multivariate model accounted for limited variance (C-statistic 0.6) in explaining participation. These four factors were not significantly associated with either the primary trial outcome measure or any differential impact by intervention arm. This demonstrates that, among eligible trial participants, few factors were associated with the consent to participate. There was no indication that such self-selection biased the trial results or would limit the generalizability and translation into a public or clinical setting.

[1]  David G Steel,et al.  Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs , 2010, BMC medical research methodology.

[2]  B. Lebowitz,et al.  Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. , 2006, The American journal of psychiatry.

[3]  J. Unützer,et al.  Monitoring Depression Treatment Outcomes With the Patient Health Questionnaire-9 , 2004, Medical care.

[4]  Aziz Sheikh,et al.  Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma , 2009, PLoS medicine.

[5]  A. Goodman,et al.  Who are we missing? Area deprivation and survey participation , 2008, European Journal of Epidemiology.

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

[7]  R. Schoevers,et al.  Predicting the Outcome of Antidepressants and Psychotherapy for Depression: A Qualitative, Systematic Review , 2008, Harvard review of psychiatry.

[8]  Internet-based treatment for older adults with depression and co-morbid cardiovascular disease: protocol for a randomised, double-blind, placebo controlled trial , 2011, BMC psychiatry.

[9]  Ian M. Shochet,et al.  Online Intervention for Student Wellbeing: Universal Online Interventions Might Engage Psychologically Distressed University Students who are Unlikely to Seek Formal Help , 2010 .

[10]  V. Beral,et al.  Cohort Profile: The 45 and Up Study , 2007, International journal of epidemiology.

[11]  T. Kashdan,et al.  Who volunteers for phase I clinical trials? Influences of anxiety, social anxiety and depressive symptoms on self-selection and the reporting of adverse events , 2008, European Journal of Clinical Pharmacology.

[12]  M. Fava,et al.  Sex differences in response to citalopram: a STAR*D report. , 2009, Journal of psychiatric research.

[13]  R. Stewart,et al.  Gender differences in 12-week antidepressant treatment outcomes for a naturalistic secondary care cohort: The CRESCEND study , 2011, Psychiatry Research.

[14]  V. Salomaa,et al.  Non-participation and mortality in different socioeconomic groups: the FINRISK population surveys in 1972–92 , 2007, Journal of Epidemiology and Community Health.

[15]  A. Serretti,et al.  Sociodemographic Features Predict Antidepressant Trajectories of Response in Diverse Antidepressant Pharmacotreatment Environments: A Comparison Between the STAR*D Study and an Independent Trial , 2011, Journal of clinical psychopharmacology.

[16]  F. Zitman,et al.  The generalizability of antidepressant efficacy trials to routine psychiatric out-patient practice , 2010, Psychological Medicine.

[17]  A. Avenell,et al.  Factors influencing the participation of older people in clinical trials — data analysis from the MAVIS trial , 2010, The journal of nutrition, health & aging.

[18]  Bradley N Gaynes,et al.  Can phase III trial results of antidepressant medications be generalized to clinical practice? A STAR*D report. , 2009, The American journal of psychiatry.

[19]  Patrick J O'Connor,et al.  Population reach and recruitment bias in a maintenance RCT in physically active older adults. , 2010, Journal of physical activity & health.

[20]  Frederick T. L. Leong,et al.  Gender and opinions about mental illness as predictors of attitudes toward seeking professional psychological help , 1999 .

[21]  C. Hewitt,et al.  Screening for Depression in Medical Settings with the Patient Health Questionnaire (PHQ): A Diagnostic Meta-Analysis , 2007, Journal of General Internal Medicine.

[22]  G. Andrews,et al.  Interpreting scores on the Kessler Psychological Distress Scale (K10) , 2001, Australian and New Zealand journal of public health.

[23]  C. Beevers,et al.  Effectiveness of a Novel Integrative Online Treatment for Depression (Deprexis): Randomized Controlled Trial , 2009, Journal of medical Internet research.

[24]  P. Cuijpers,et al.  One-year follow-up results of a randomized controlled clinical trial on internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years , 2008, Psychological Medicine.

[25]  Heleen Riper,et al.  Internet-Based Treatment for Adults with Depressive Symptoms: Randomized Controlled Trial , 2008, Journal of medical Internet research.

[26]  S. Michie,et al.  Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy , 2010, Journal of medical Internet research.

[27]  H. Dodge,et al.  Random versus volunteer selection for a community-based study. , 1998, The journals of gerontology. Series A, Biological sciences and medical sciences.

[28]  Per Carlbring,et al.  Experiences of guided Internet-based cognitive-behavioural treatment for depression: A qualitative study , 2011, BMC psychiatry.

[29]  N. Glozier,et al.  Motivators and Motivations to Persist With Online Psychological Interventions: A Qualitative Study of Treatment Completers , 2012, Journal of medical Internet research.

[30]  J Brug,et al.  Effectiveness of an online computer-tailored physical activity intervention in a real-life setting. , 2006, Health education research.

[31]  Ronald D. Rogge,et al.  Recruitment and selection of couples for intervention research: achieving developmental homogeneity at the cost of demographic diversity. , 2006, Journal of consulting and clinical psychology.

[32]  Clinical Excellence,et al.  Common mental health disorders : identification and pathways to care , 2011 .

[33]  S. Hollon,et al.  Predictors of attrition during initial (citalopram) treatment for depression: a STAR*D report. , 2007, The American journal of psychiatry.

[34]  B W Wyse,et al.  Prevalence of depression and its treatment in an elderly population: the Cache County study. , 2000, Archives of general psychiatry.

[35]  Maurizio Fava,et al.  Selecting among second-step antidepressant medication monotherapies: predictive value of clinical, demographic, or first-step treatment features. , 2008, Archives of general psychiatry.

[36]  P. de Jonge,et al.  Prediction of the three-year course of recurrent depression in primary care patients: different risk factors for different outcomes. , 2008, Journal of affective disorders.

[37]  C. Reynolds,et al.  Social inequalities in response to antidepressant treatment in older adults. , 2006, Archives of general psychiatry.

[38]  T. Laatikainen,et al.  Marital status, educational level and household income explain part of the excess mortality of survey non-respondents , 2010, European Journal of Epidemiology.

[39]  Patient predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH Treatment of Depression Collaborative Research Program. , 1991 .

[40]  M. Egger,et al.  Women, older persons, and ethnic minorities: factors associated with their inclusion in randomised trials of statins 1990 to 2001 , 2003, Heart.

[41]  J. Ware SF-36 health survey: Manual and interpretation guide , 2003 .

[42]  H. Christensen,et al.  Online randomized controlled trial of brief and full cognitive behaviour therapy for depression , 2006, Psychological Medicine.

[43]  H. Riper,et al.  Clinical effectiveness of online computerised cognitive–behavioural therapy without support for depression in primary care: randomised trial , 2009, British Journal of Psychiatry.

[44]  Wiebo Brouwer,et al.  Differences between participants and non-participants in an RCT on physical activity and psychological interventions for older persons , 2005, Aging clinical and experimental research.

[45]  J. Brug,et al.  Efficacy and Use of an Internet-delivered Computer-tailored Lifestyle Intervention, Targeting Saturated Fat Intake, Physical Activity and Smoking Cessation: A Randomized Controlled Trial , 2008, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[46]  P. Rautava,et al.  Non-response and related factors in a nation-wide health survey , 2004, European Journal of Epidemiology.

[47]  M. Reger,et al.  A meta-analysis of the effects of internet- and computer-based cognitive-behavioral treatments for anxiety. , 2009, Journal of clinical psychology.

[48]  Frederick T. L. Leong,et al.  Gender and Opinions about Mental Illness as Predictors of Attitudes toward Seeking Professional Psychological Help. , 1999 .

[49]  M. Flores-Ramos,et al.  Different gender response to serotonergic and noradrenergic antidepressants. A comparative study of the efficacy of citalopram and reboxetine. , 2006, Journal of affective disorders.

[50]  M. Shea,et al.  Patient predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH Treatment of Depression Collaborative Research Program. , 1991, The American journal of psychiatry.

[51]  V. Preedy,et al.  Scottish Intercollegiate Guidelines Network , 2010 .

[52]  C. Mackenzie,et al.  Age, gender, and the underutilization of mental health services: The influence of help-seeking attitudes , 2006, Aging & mental health.

[53]  G. Andersson,et al.  Self-Guided Psychological Treatment for Depressive Symptoms: A Meta-Analysis , 2011, PloS one.

[54]  Pim Cuijpers,et al.  Effectiveness of a Web-Based Self-Help Intervention for Symptoms of Depression, Anxiety, and Stress: Randomized Controlled Trial , 2008, Journal of medical Internet research.

[55]  W. Brown,et al.  Sex Differences in Antidepressant Response in Recent Antidepressant Clinical Trials , 2005, Journal of clinical psychopharmacology.

[56]  R. Bhopal,et al.  Self reports in research with non-English speakers , 2003, BMJ : British Medical Journal.

[57]  R. Kessler,et al.  Short screening scales to monitor population prevalences and trends in non-specific psychological distress , 2002, Psychological Medicine.

[58]  S. Øverland,et al.  American Journal of Epidemiology Practice of Epidemiology the Health Status of Nonparticipants in a Population-based Health Study the Hordaland Health Study , 2022 .

[59]  Nikki M. Carroll,et al.  Recruitment to a Randomized Web-Based Nutritional Intervention Trial: Characteristics of Participants Compared to Non-Participants , 2009, Journal of medical Internet research.

[60]  A. Möller-Leimkühler Barriers to help-seeking by men: a review of sociocultural and clinical literature with particular reference to depression. , 2002, Journal of affective disorders.

[61]  A. Arntz,et al.  Improving adherence and effectiveness of computerised cognitive behavioural therapy without support for depression: a qualitative study on patient experiences. , 2011, Journal of Affective Disorders.

[62]  J. Wyatt,et al.  Using the Internet for Surveys and Health Research , 2002, Journal of medical Internet research.

[63]  S. Cotten,et al.  Characteristics of online and offline health information seekers and factors that discriminate between them. , 2004, Social science & medicine.

[64]  D. Veale,et al.  National Collaborating Centre for Mental Health , 2006 .

[65]  Heleen Riper,et al.  Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis , 2006, Psychological Medicine.