Correction: Comparing Online and On-Site Cognitive Behavior Therapy in Major Depressive Disorder: Protocol for a Noninferiority Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/29726.].

Comparing Online and On-Site Cognitive Behavior Therapy in Major Depressive Disorder: Protocol for a Noninferiority Randomized Controlled Trial.

BACKGROUND: The incidence of mental health disorders in Canada is increasing with costs of CAD $51 billion (US $40 billion) per year. Depression is the most prevalent cause of disability while cognitive behavioral therapy (CBT) is the best validated behavioral depression treatment. CBT, when combined with mindfulness meditation (CBT-M), has strong evidence for increased efficacy. While randomized controlled trials (RCTs) have demonstrated online CBT-M efficacy, comparisons with in-office delivery are lacking. OBJECTIVE: The aim of this research is to assess whether online group CBT-M (with standard psychiatric care) is non-inferior in efficacy and more cost-effective than office-based, on-site group CBT-M at post-intervention and 6-months follow-up in major depressive disorder. The study will also assess whether digitally recorded data (ie, online workbooks completed, Fitbit step count, and online text messages) predict depression symptom reduction in online participants. METHODS: This single-center, two-arm, noninferiority RCT employs assessor-blinded and self-report outcomes and economic evaluation. The research site is the Centre for Addiction and Mental Health (Toronto), a research-based psychiatry institution where participants will be identified from service wait lists and through contacts with other Toronto clinics. Inclusion criteria are as follows: (1) aged 18-60 years, any ethnicity; (2) Beck Depression Inventory-II (BDI-II) of mild severity (score ≥14) with no upper severity limit; (3) Mini-International Neuropsychiatric Interview-confirmed, psychiatric major depressive disorder diagnosis; (4) fluent in English. All patients are diagnosed by staff psychiatrists. Exclusion criteria are as follows: (1) receipt of weekly structured psychotherapy; (2) observation of Diagnostic and Statistical Manual of Mental Disorders (5th Edition) criteria for severe alcohol or substance use disorder (in past 3 months), borderline personality disorder, schizophrenia (or other primary psychotic disorder), bipolar disorder, or obsessive-compulsive disorder; (3) clinically significant suicidal ideation (imminent intent or attempted suicide in the past 6 months); and (4) treatment-resistant depression. All participants receive standard psychiatric care, experimental participants receive online group CBT-M, and controls receive standard care in-office group CBT-M. The online group program (in collaboration with NexJ Health, Inc) combines smartphone and computer-accessed workbooks with mental health phone counselling (16 hours in 16 weeks) that coordinates software interactions (eg, secure text messaging and Fitbit-tracked walking). The primary outcome is BDI-II, and secondary outcomes are anxiety (Beck Anxiety Inventory), depression (ie, Quick Inventory of Depressive Symptomatology and 17-item Hamilton Depression Rating Scale), mindfulness (Five-Facet Mindfulness Questionnaire), quality of life (European Quality of Life Five Dimension), and pain (Brief Pain Inventory). RESULTS: Based on prior studies with the BDI-II and 80% power to reject an inferiority hypothesis with a 1-sided type I error rate of 5%, a sample of 78 per group is adequate to detect small-to-medium-effect sizes. CONCLUSIONS: This study assesses online CBT-M efficacy and noninferiority in relation to in-person CBT, and the cost-effectiveness of both interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04825535; https://www.clinicaltrials.gov/ct2/show/NCT04825535. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29726.

Participant experiences in a smartphone-based health coaching intervention for type 2 diabetes: A qualitative inquiry.

INTRODUCTION: We investigated the experience of individuals diagnosed with type 2 diabetes mellitus (T2DM) who participated in an intervention in which the key elements were the provision of a smartphone and self-monitoring software. The interviews focused on use of a smartphone and the effects on motivation for health behavior change. METHODS: This was a qualitative evaluation of participants in a larger T2DM self-management randomized controlled trial (RCT) conducted at the Black Creek Community Health Centre (BCCHC) in Toronto, Canada (ClinicalTrials.gov Identifier: NCT02036892). The study is based on semi-structured interviews (n = 11) that were audio taped and analyzed with a thematic analytic approach. The RCT compared the effectiveness of six months of smartphone-based self-monitoring and health coaching with a control group who received health coaching without internet or smartphone-based assistance. RESULTS: Qualitative data analyses resulted in derivation of four major themes that describe participant experience: (a) 'smartphone and software', describes smartphone use in relation to health behavior change; (b) 'health coach' describes how client/health coach relationships were assisted by smartphone use; (c) 'overall experience' describes perceptions of the overall intervention; and (d) 'frustrations in managing chronic conditions' describes difficulties with the complexities of T2DM management from a patient perspective. DISCUSSION: Findings suggest that interventions with T2DM assisted by smartphone software and health coaches actively engage individuals in improved hemoglobin A1c (HbA1c) control.

Data Mining of a Remote Behavioral Tracking System for Type 2 Diabetes Patients: A Prospective Cohort Study.

BACKGROUND: Complications from type 2 diabetes mellitus can be prevented when patients perform health behaviors such as vigorous exercise and glucose-regulated diet. The use of smartphones for tracking such behaviors has demonstrated success in type 2 diabetes management while generating repositories of analyzable digital data, which, when better understood, may help improve care. Data mining methods were used in this study to better understand self-monitoring patterns using smartphone tracking software. OBJECTIVE: Associations were evaluated between the smartphone monitoring of health behaviors and HbA1c reductions in a patient subsample with type 2 diabetes who demonstrated clinically significant benefits after participation in a randomized controlled trial. METHODS: A priori association-rule algorithms, implemented in the C language, were applied to app-discretized use data involving three primary health behavior trackers (exercise, diet, and glucose monitoring) from 29 participants who achieved clinically significant HbA1c reductions. Use was evaluated in relation to improved HbA1c outcomes. RESULTS: Analyses indicated that nearly a third (9/29, 31%) of participants used a single tracker, half (14/29, 48%) used two primary trackers, and the remainder (6/29, 21%) of the participants used three primary trackers. Decreases in HbA1c were observed across all groups (0.97-1.95%), but clinically significant reductions were more likely with use of one or two trackers rather than use of three trackers (OR 0.18, P=.04). CONCLUSIONS: Data mining techniques can reveal relevant coherent behavior patterns useful in guiding future intervention structure. It appears that focusing on using one or two trackers, in a symbolic function, was more effective (in this sample) than regular use of all three trackers.

Health Coaching Reduces HbA1c in Type 2 Diabetic Patients From a Lower-Socioeconomic Status Community: A Randomized Controlled Trial.

BACKGROUND: Adoptions of health behaviors are crucial for maintaining good health after type 2 diabetes mellitus (T2DM) diagnoses. However, adherence to glucoregulating behaviors like regular exercise and balanced diet can be challenging, especially for people living in lower-socioeconomic status (SES) communities. Providing cost-effective interventions that improve self-management is important for improving quality of life and the sustainability of health care systems. OBJECTIVE: To evaluate a health coach intervention with and without the use of mobile phones to support health behavior change in patients with type 2 diabetes. METHODS: In this noninferiority, pragmatic randomized controlled trial (RCT), patients from two primary care health centers in Toronto, Canada, with type 2 diabetes and a glycated hemoglobin/hemoglobin A1c (HbA1c) level of ≥7.3% (56.3 mmol/mol) were randomized to receive 6 months of health coaching with or without mobile phone monitoring support. We hypothesized that both approaches would result in significant HbA1c reductions, although health coaching with mobile phone monitoring would result in significantly larger effects. Participants were evaluated at baseline, 3 months, and 6 months. The primary outcome was the change in HbA1c from baseline to 6 months (difference between and within groups). Other outcomes included weight, waist circumference, body mass index (BMI), satisfaction with life, depression and anxiety (Hospital Anxiety and Depression Scale [HADS]), positive and negative affect (Positive and Negative Affect Schedule [PANAS]), and quality of life (Short Form Health Survey-12 [SF-12]). RESULTS: A total of 138 patients were randomized and 7 were excluded for a substudy; of the remaining 131, 67 were allocated to the intervention group and 64 to the control group. Primary outcome data were available for 97 participants (74.0%). While both groups reduced their HbA1c levels, there were no significant between-group differences in change of HbA1c at 6 months using intention-to-treat (last observation carried forward [LOCF]) (P=.48) or per-protocol (P=.83) principles. However, the intervention group did achieve an accelerated HbA1c reduction, leading to a significant between-group difference at 3 months (P=.03). This difference was reduced at the 6-month follow-up as the control group continued to improve, achieving a reduction of 0.81% (8.9 mmol/mol) (P=.001) compared with a reduction of 0.84% (9.2 mmol/mol)(P=.001) in the intervention group. Intervention group participants also had significant decreases in weight (P=.006) and waist circumference (P=.01) while controls did not. Both groups reported improvements in mood, satisfaction with life, and quality of life. CONCLUSIONS: Health coaching with and without access to mobile technology appeared to improve glucoregulation and mental health in a lower-SES, T2DM population. The accelerated improvement in the mobile phone group suggests the connectivity provided may more quickly improve adoption and adherence to health behaviors within a clinical diabetes management program. Overall, health coaching in primary care appears to lead to significant benefits for patients from lower-SES communities with poorly controlled type 2 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT02036892; http://clinicaltrials.gov/ct2/show/NCT02036892 (Archived by WebCite at http://www.webcitation.org/6b3cJYJOD).

Smartphone-enabled health coach intervention for people with diabetes from a modest socioeconomic strata community: single-arm longitudinal feasibility study.

BACKGROUND: Lower socioeconomic strata (SES) populations have higher chronic disease risks. Smartphone-based interventions can support adoption of health behaviors that may, in turn, reduce the risks of type 2 diabetes-related complications, overcoming the obstacles that some patients may have with regular clinical contact (eg, shiftwork, travel difficulties, miscommunication). OBJECTIVE: The intent of the study was to develop and test a smartphone-assisted intervention that improves behavioral management of type 2 diabetes in an ethnically diverse, lower SES population within an urban community health setting. METHODS: This single-arm pilot study assessed a smartphone application developed with investigator assistance and delivered by health coaches. Participants were recruited from the Black Creek Community Health Centre in Toronto and had minimal prior experience with smartphones. RESULTS: A total of 21 subjects consented and 19 participants completed the 6-month trial; 12 had baseline glycosylated hemoglobin (HbA1c) levels >7.0% and these subjects demonstrated a mean reduction of 0.43% (SD 0.63) (P<.05) with minimal changes in medication. CONCLUSIONS: This project supported the feasibility of smartphone-based health coaching for individuals from lower SES with minimal prior smartphone experience.