Christina Gonzalez-Torres

1. Postpartum Depression (PPD), or peripartum-onset depression [1] is a common complication of childbearing that affects approximately 17% of women and can have potentially serious consequences for...

Background: Bipolar disorder (BD) carries a suicide risk 20 times higher than the general population, with up to 60% of patients attempting suicide. Current interventions have failed to reduce its incidence; static factors have shown limited predictive utility. Emerging evidence suggests dynamic monitoring approaches may offer complementary value. This study examined whether quantifiable differences in mood regulation patterns exist across the suicidality continuum among patients diagnosed with BD. Method: We analyzed daily self‐reported mood, anxiety, and energy levels from 164 participants recruited from two Canadian academic hospitals (April 2021–August 2024). Participants were stratified into six groups based on suicide attempt history, current polarity, and active suicidality status. Using time‐series analysis, we computed autocorrelation and cross‐correlation functions to examine temporal relationships within and between variables across 1–7 day lags. Data comprised 64,351 valid observations over 461.5 ± 236.6 days of follow‐up. Results: Participants with the highest suicide risk (previous attempt, in a current depressive episode with active suicidality) demonstrated significantly higher day‐to‐day autocorrelation compared to the lowest‐risk participants (no prior attempts and currently euthymic) for mood (0.53 vs. 0.29, p = 0.01), energy (0.52 vs. 0.23, p = 0.02), and anxiety series (0.55 vs. 0.32, p = 0.04). Cross‐correlation analysis revealed mood‐energy decoupling during active suicidality; as well as a stronger negative mood‐anxiety correlation in those with a prior attempt, even during euthymia. Conclusion: Higher autocorrelation patterns are indicative of a pathologically stable mood regulation in high‐risk individuals, potentially serving as dynamic biomarkers for suicide risk stratification and targeted intervention development. Our findings demonstrate that a more aggressive approach to treating comorbid anxiety may be essential for reducing the risk of future attempts. They also challenge traditional conceptualizations equating euthymia with the absence of suicide risk, suggesting neurobiological vulnerability despite symptomatic remission.

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 (β=–0.029, 95% CI –0.11 to 0.048) and in each of the 3 categories: appreciating alliance (β=–0.096, 95% CI –0.80 to 0.61), alliance building disclosures (β=–0.098, 95% CI –0.28 to 0.084), and agreement confirmation (β=–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

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.

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

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). 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

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 (β=–0.029, 95% CI –0.11 to 0.048) and in each of the 3 categories: appreciating alliance (β=–0.096, 95% CI –0.80 to 0.61), alliance building disclosures (β=–0.098, 95% CI –0.28 to 0.084), and agreement confirmation (β=–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. CLINICALTRIAL Clinical Trials.gov NCT03406052; https://www.clinicaltrials.gov/ct2/show/NCT03406052