The Use of Text Messaging as an Adjunct to Internet-Based Cognitive Behavioral Therapy for Major Depressive Disorder in Youth: Secondary Analysis.

BACKGROUND: As an established treatment for major depressive disorder (MDD), cognitive behavioral therapy (CBT) is now implemented and assessed in internet-based formats that, when combined with smartphone apps, enable secure text messaging. As an adjunct to such internet-based CBT (ICBT) approaches, text messaging has been associated with increased adherence and therapeutic alliance. OBJECTIVE: This study analyzed data from the intervention arm of a randomized control trial evaluating 24-week ICBT for MDD (intervention arm) against standard-care psychiatry (waitlist control). The aim of this secondary analysis was to assess MDD symptom improvement in relation to the frequency and content of text messages sent by ICBT participants to Navigator-Coaches during randomized control trial participation. Higher text frequency in general and in 3 conceptual categories (appreciating alliance, alliance building disclosures, and agreement confirmation) was hypothesized to predict larger MDD symptom improvement. METHODS: Participants were young adults (18-30 years) from the Centre for Addiction and Mental Health. The frequencies of categorized texts from 20 ICBT completers were analyzed with respect to MDD symptom improvement using linear regression models. Texts were coded by 2 independent coders and categorized using content analysis. MDD symptoms were measured using the Beck Depression Inventory-II (BDI-II). RESULTS: Participants sent an average of 136 text messages. Analyses indicated that BDI-II improvement was negatively associated with text messaging frequency in general (ß=-0.029, 95% CI -0.11 to 0.048) and in each of the 3 categories: appreciating alliance (ß=-0.096, 95% CI -0.80 to 0.61), alliance building disclosures (ß=-0.098, 95% CI -0.28 to 0.084), and agreement confirmation (ß=-0.076, 95% CI -0.40 to 0.25). Altogether, the effect of text messaging on BDI-II improvement was uniformly negative across statistical models. More text messaging appeared associated with less MDD symptom improvement. CONCLUSIONS: The hypothesized positive associations between conceptually categorized text messages and MDD symptom improvement were not supported in this study. Instead, more text messaging appeared to indicate less treatment benefit. Future studies with larger samples are needed to discern the optimal use of text messaging in ICBT approaches using adjunctive modes of communication. TRIAL REGISTRATION: Clinical Trials.gov NCT03406052; https://www.clinicaltrials.gov/ct2/show/NCT03406052.

A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.

Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic or hypomanic episodes, and depressive episodes. While motor abnormalities are commonly seen during depressive or manic episodes, not much attention has been paid to postural abnormalities during periods of euthymia and their association with illness burden. We collected 24-hour posture data in 32 euthymic participants diagnosed with BD using a shirt-based wearable. We extracted a set of nine time-domain features, and performed unsupervised participant clustering. We investigated the association between posture variables and 12 clinical characteristics of illness burden. Based on their postural dynamics during the daytime, evening, or nighttime, participants clustered in three clusters. Higher illness burden was associated with lower postural variability, in particular during daytime. Participants who exhibited a mostly upright sitting/standing posture during the night with frequent nighttime postural transitions had the highest number of lifetime depressive episodes. Euthymic participants with BD exhibit postural abnormalities that are associated with illness burden, especially with the number of depressive episodes. Our results contribute to understanding the role of illness burden on posture changes and sleep consolidation in periods of euthymia.

Prescribed psychostimulants and other pro-cognitive medications in bipolar disorder: A systematic review and meta-analysis of recurrence of manic symptoms.

OBJECTIVES: Clinicians are often hesitant to prescribe psychostimulants in bipolar disorder (BD) due to concerns of inducing (hypo)mania, despite limited published evidence on associations between prescribed psychostimulant use and recurrence of mood episodes in BD. The current systematic review and meta-analysis evaluated the emergence of (hypo)manic symptoms in patients with BD receiving prescribed psychostimulants or other pro-cognitive medications in euthymic or depressive states. METHODS: A systematic search was performed of MEDLINE, Embase, and PsychINFO from inception to April 5, 2023 and search of Clinicaltrials.gov and Clinicaltrialsregister.eu for unpublished data. References of included studies were hand-searched. Randomized trials and prospective longitudinal studies that evaluated psychostimulants and non-stimulant medications recommended for the treatment of ADHD by the Canadian ADHD practice guidelines were included. The review was reported in line with PRISMA guidelines and was preregistered on PROSPERO (CRD42022358588). RESULTS: After screening 414 unique records, we included 27 studies, of which five reported data that was quantitatively synthesized (n = 1653). The use of psychostimulants in BD was not associated with increased scores on the Young Mania Rating Scale in patients who were in a euthymic or depressed state (SMD IV -0.17; 95% CI, -0.40 to 0.06) compared to placebo. There was a high degree of study-level heterogeneity (I2 = 80%). A qualitative synthesis of studies revealed a limited risk of medication-induced manic symptoms. CONCLUSIONS: Our review provides preliminary evidence to suggest psychostimulants and non-stimulant ADHD medications have a limited risk of precipitating (hypo)mania symptoms. More extensive studies evaluating the safety and efficacy of these medications are warranted.

Challenges in defining treatment-resistant mania in adults: A systematic review.

OBJECTIVES: To review the definitions of treatment-resistant mania (TRM) in the literature and propose criteria for an operationalized definition. METHODS: A systematic search of five databases (MEDLINE, EMBASE, PsychInfo, Cochrane Central, and CINAHL) and data extraction of eligible articles. RESULTS: In total, 47 articles addressing the concept of TRM were included, comprising 16 case reports, 11 case series, 3 randomized clinical trials, 8 open-label clinical trials, 1 experimental study, 7 narrative reviews, and 1 systematic review. While reviews discussed several challenges in defining TRM, definitions varied substantially based on different criteria for severity of mania, duration of mania, and use of specific therapeutic agents with minimal dosages and duration of treatment. Only a handful of the reviewed articles operationalized these criteria. CONCLUSION: While the concept of TRM has been discussed in the literature for over three decades, we could not find an agreed-upon operationalized definition based on specific criteria. We propose and discuss a possible definition that could be used by clinicians to guide their practice and by researchers to assess the prevalence of TRM and develop and test interventions targeting TRM.

The Role of Daily Steps in the Treatment of Major Depressive Disorder: Secondary Analysis of a Randomized Controlled Trial of a 6-Month Internet-Based, Mindfulness-Based Cognitive Behavioral Therapy Intervention for Youth.

BACKGROUND: Current evidence supports physical activity (PA) as an adjunctive treatment for major depressive disorder (MDD). Few studies, however, have examined the relationship between objectively measured PA and MDD treatment outcomes using prospective data. OBJECTIVE: This study is a secondary analysis of data from a 24-week internet-based, mindfulness-based cognitive behavioral therapy program for MDD. The purpose of this analysis was twofold: (1) to examine average daily step counts in relation to MDD symptom improvement, and whether pain moderated this relationship; and (2) to examine whether changes in step activity (ie, step trajectories) during treatment were associated with baseline symptoms and symptom improvement. METHODS: Patients from the Centre for Addiction and Mental Health were part of a randomized controlled trial evaluating the effects of internet-based, mindfulness-based cognitive behavioral therapy for young adults (aged 18-30 years old) with MDD. Data from 20 participants who had completed the intervention were analyzed. PA, in the form of objectively measured steps, was measured using the Fitbit-HR Charge 2 (Fitbit Inc), and self-reported depression severity was measured with the Beck Depression Inventory-II (BDI-II). Linear regression analysis was used to test PA's relationship with depression improvement and the moderating effect of pain severity and pain interference. Growth curve and multivariable regression models were used to test longitudinal associations. RESULTS: Participants walked an average of 8269 steps per day, and each additional +1000-step difference between participants was significantly associated with a 2.66-point greater improvement (reduction) in BDI-II, controlling for anxiety, pain interference, and adherence to Fitbit monitoring (P=.02). Pain severity appeared to moderate (reduce) the positive effect of average daily steps on BDI-II improvement (P=.03). Higher baseline depression and anxiety symptoms predicted less positive step trajectories throughout treatment (Ps≤.001), and more positive step trajectories early in the trial predicted greater MDD improvement at the end of the trial (Ps<.04). However, step trajectories across the full duration of the trial did not significantly predict MDD improvement (Ps=.40). CONCLUSIONS: This study used objective measurements to demonstrate positive associations between PA and depression improvement in the context of cognitive behavioral treatment. Pain appeared to moderate this relationship, and baseline symptoms of anxiety and depression predicted PA trajectories. The findings inform future interventions for major depression. Future research with larger samples should consider additional moderators of PA-related treatment success and the extent to which outcomes are related to PA change in multimodal interventions. TRIAL REGISTRATION: Clinical Trials.gov NCT03406052; https://www.clinicaltrials.gov/ct2/show/NCT03406052. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/11591.

Predictors of adherence to electronic self-monitoring in patients with bipolar disorder: a contactless study using Growth Mixture Models.

BACKGROUND: Several studies have reported on the feasibility of electronic (e-)monitoring using computers or smartphones in patients with mental disorders, including bipolar disorder (BD). While studies on e-monitoring have examined the role of demographic factors, such as age, gender, or socioeconomic status and use of health apps, to our knowledge, no study has examined clinical characteristics that might impact adherence with e-monitoring in patients with BD. We analyzed adherence to e-monitoring in patients with BD who participated in an ongoing e-monitoring study and evaluated whether demographic and clinical factors would predict adherence. METHODS: Eighty-seven participants with BD in different phases of the illness were included. Patterns of adherence for wearable use, daily and weekly self-rating scales over 15 months were analyzed to identify adherence trajectories using growth mixture models (GMM). Multinomial logistic regression models were fitted to compute the effects of predictors on GMM classes. RESULTS: Overall adherence rates were 79.5% for the wearable; 78.5% for weekly self-ratings; and 74.6% for daily self-ratings. GMM identified three latent class subgroups: participants with (i) perfect; (ii) good; and (iii) poor adherence. On average, 34.4% of participants showed "perfect" adherence; 37.1% showed "good" adherence; and 28.2% showed poor adherence to all three measures. Women, participants with a history of suicide attempt, and those with a history of inpatient admission were more likely to belong to the group with perfect adherence. CONCLUSIONS: Participants with higher illness burden (e.g., history of admission to hospital, history of suicide attempts) have higher adherence rates to e-monitoring. They might see e-monitoring as a tool for better documenting symptom change and better managing their illness, thus motivating their engagement.

Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study.

BACKGROUND: Predictive models for mental disorders or behaviors (e.g., suicide) have been successfully developed at the level of populations, yet current demographic and clinical variables are neither sensitive nor specific enough for making individual clinical predictions. Forecasting episodes of illness is particularly relevant in bipolar disorder (BD), a mood disorder with high recurrence, disability, and suicide rates. Thus, to understand the dynamic changes involved in episode generation in BD, we propose to extract and interpret individual illness trajectories and patterns suggestive of relapse using passive sensing, nonlinear techniques, and deep anomaly detection. Here we describe the study we have designed to test this hypothesis and the rationale for its design. METHOD: This is a protocol for a contactless cohort study in 200 adult BD patients. Participants will be followed for up to 2 years during which they will be monitored continuously using passive sensing, a wearable that collects multimodal physiological (heart rate variability) and objective (sleep, activity) data. Participants will complete (i) a comprehensive baseline assessment; (ii) weekly assessments; (iii) daily assessments using electronic rating scales. Data will be analyzed using nonlinear techniques and deep anomaly detection to forecast episodes of illness. DISCUSSION: This proposed contactless, large cohort study aims to obtain and combine high-dimensional, multimodal physiological, objective, and subjective data. Our work, by conceptualizing mood as a dynamic property of biological systems, will demonstrate the feasibility of incorporating individual variability in a model informing clinical trajectories and predicting relapse in BD.

Depression and Impulsivity Self-Assessment Tools to Identify Dopamine Agonist Side Effects in Patients With Pituitary Adenomas.

Background: Dopamine agonists (DA) are the first line therapy for prolactinoma and symptomatic hyperprolactinemia; use as an adjuvant treatment for acromegaly and Cushing's disease is rare. Some patients develop de novo psychiatric symptoms or have exacerbation of pre-existing conditions during DA therapy. A practical, clinically sensitive depression and impulse control disorders (ICD; particularly hypersexuality and gambling disorders) detection tool is important for identifying at risk patients. The Barratt Impulsivity Scale (BIS-11) and the 9-item Patient Health Questionnaire (PHQ-9) are sensitive in identifying impulsivity and depression. Objective: Detail use of the BIS-11 and PHQ-9 as screening tools for depression and ICD in patients with pituitary disease at a high-volume academic pituitary center. Methods: DA-treated and naïve patients with pituitary disease were included. Patients with a known history of depression or psychiatric disorder were excluded. PHQ-9 standardized interpretation criteria were utilized to classify depression severity. For BIS-11, threshold was established based on previous studies. Statistical analysis was with SPSS version 25. Results: Seventy-six DA-treated and 27 naïve patients were included. Moderate and moderately severe depression were more prevalent in DA-treated patients; severe depression only found in DA-treated patients. A normal BIS-11 score was noted in 76.69%; higher scores (not significant) were noted in DA-treated patients. There was a positive correlation between higher BIS-11 and PHQ-9 scores; higher in DA-treated patients (r = 0.52, p < 0.001) than DA-naïve patients. Patients with BIS-11 scores ≥60 were younger and received lower cumulative DA doses compared to patients with BIS scores <60. There was no association between male sex and BIS-11 ≥60 and male sex did not increase the odds of increased scores (OR = 0.66, CI95% 0.25-1.76, p = 0.41). No significant difference was found for macroadenoma, prolactin levels, testosterone levels, hypogonadism, testosterone replacement in men, and increased impulsivity or depression scores. Conclusion: Use of PHQ-9 and BIS-11 is practical for routine screening of depression and ICD during outpatient pituitary clinic visits for patients with pituitary disease both naïve to treatment and during DA therapy. We recommend close follow-up after initiation of DA therapy for younger patients, regardless of dose.