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Behavior Therapy Jul 2024Prior research suggests that the effects of specific cognitive-behavioral therapy (CBT) modules on symptom outcomes can be estimated. We conducted a study utilizing...
Prior research suggests that the effects of specific cognitive-behavioral therapy (CBT) modules on symptom outcomes can be estimated. We conducted a study utilizing idiographic and nomothetic methods to clarify which CBT modules are most effective for youth depression, and for whom they are most effective. Thirty-five youths received modular CBT for depression. Interrupted time series models estimated whether the introduction of each module was associated with changes in internalizing symptoms, whereby significant symptom reduction would suggest a therapeutic response to the module. Regression models were used to explore whether participant characteristics predicted subgroups of youths based on their estimated response to certain types (e.g., cognitive) of modules, and whether group membership was associated with posttreatment outcomes. Thirty youths (86%) had at least one module associated with a significant change in internalizing symptoms from premodule delivery to postmodule delivery. The specific modules associated with these changes varied across youths. Behavioral activation was most frequently associated with symptom decreases (34% of youths). No participant characteristics predicted estimated response to module type, and group membership was not significantly associated with posttreatment outcomes. Youths display highly heterogeneous responses to treatment modules, indicating multiple pathways to symptom improvement for depressed youths.
Topics: Humans; Cognitive Behavioral Therapy; Female; Male; Adolescent; Treatment Outcome; Child; Depression; Depressive Disorder
PubMed: 38937058
DOI: 10.1016/j.beth.2024.01.004 -
Behavior Therapy Jul 2024This study explored clinical and sociodemographic moderators of treatment response to "Be a Mom", an internet-based cognitive behavioral therapy (iCBT) intervention,... (Randomized Controlled Trial)
Randomized Controlled Trial
For Whom and for How Long Does the "Be a Mom" Intervention Work? A Secondary Analysis of Data From a Randomized Controlled Trial Exploring the Mid-Term Efficacy and Moderators of Treatment Response.
This study explored clinical and sociodemographic moderators of treatment response to "Be a Mom", an internet-based cognitive behavioral therapy (iCBT) intervention, from baseline to postintervention, in women at high risk for postpartum depression (PPD). The study also assessed the stability of women's treatment gains from baseline to 4-months postintervention (follow-up). This open-label randomized controlled trial (RCT) involved a sample of 1,053 postpartum Portuguese women identified as being at high risk for PPD (i.e., having a score of 5.5 or higher on the Postpartum Depression Predictors Inventory-Revised); participants were allocated to "Be a Mom" intervention group or a waiting-list control group, and completed self-report measures at baseline, postintervention, and a 4-month follow-up (554 women completed follow-up assessments). Depressive and anxiety symptoms were measured using the Edinburgh Postnatal Depression Scale and the anxiety subscale of the Hospital Anxiety and Depression Scale, and flourishing/positive mental health was assessed with the Mental Health Continuum. Regression models and linear mixed models were used to examine moderators of treatment and the mid-term efficacy of the "Be a Mom" intervention, respectively. The results revealed that treatment completion, higher depression scores at baseline, and higher income levels were linked to greater symptom reduction and positive mental health enhancement. Moreover, the efficacy of the "Be a Mom" intervention was supported at the 4-month follow-up. The "Be a Mom" intervention appears to be an effective iCBT tool for reducing psychological distress and enhancing positive mental health in women at risk for PPD, with therapeutic improvements maintained over a 4-month period.
Topics: Humans; Female; Adult; Cognitive Behavioral Therapy; Depression, Postpartum; Treatment Outcome; Anxiety; Mothers; Internet-Based Intervention; Portugal
PubMed: 38937049
DOI: 10.1016/j.beth.2023.11.001 -
The British Journal of General Practice... Jul 2024
Topics: Humans; Primary Health Care; Prognosis; Severity of Illness Index; Depression; Antidepressive Agents; Depressive Disorder
PubMed: 38936876
DOI: 10.3399/bjgp24X738537 -
The British Journal of General Practice... Jul 2024
Topics: Humans; Primary Health Care; Secondary Care; Mental Health Services; Mental Disorders; United Kingdom; Health Services Accessibility; Health Services Needs and Demand; Healthcare Disparities
PubMed: 38936873
DOI: 10.3399/bjgp24X738513 -
Journal of Affective Disorders Jun 2024This short communication explores the interrelationships between depressed mood and sleep disturbances in one-year postpartum period.
BACKGROUND
This short communication explores the interrelationships between depressed mood and sleep disturbances in one-year postpartum period.
METHODS
Utilizing data from the Interaction of Gene and Environment of Depression during PostPartum Cohort (IGEDEPP) involving 3310 French postpartum women, we employed a cross-lagged panel model (CLPM) to analyze the relationships between these two symptoms, across three time points (immediate postpartum [<1 week after delivery], early postpartum [<2 months after delivery], and late postpartum [2 months to 1 years after delivery]).
RESULTS
Depressed mood significantly influences sleep disturbances in late postpartum (β = 0.096, z-value = 7.4; p < 0.001) but not in early postpartum (p-value = 0.9). We found no cross-lagged influence of sleep disturbances on depressed mood in early (p = 0.066) or in late postpartum (p = 0.060). Moreover, depressed mood and sleep disturbances in immediate postpartum are predictive of similar symptoms in the two other postpartum periods (between each of the three periods, p = 0.006 and p < 0.001 for depressed mood, and p = 0.039 and p < 0.001 for sleep disturbances), thus demonstrating the stability of these symptoms over time.
LIMITATIONS
Although conducted with a prospectively assessed cohort, this study faces limitations due to potential methodological biases.
CONCLUSIONS
This study is a pioneering analysis of mutual causal interactions between depressed mood and sleep disturbances in the postpartum period, highlighting the need for vigilant monitoring, early detection, prevention of worsen outcomes and intervention on these symptoms.
PubMed: 38936702
DOI: 10.1016/j.jad.2024.06.089 -
European Neuropsychopharmacology : the... Jun 2024An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of...
Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance.
An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of treatment-resistant depression (TRD) represents a major goal of precision psychiatry, which is hampered by the clinical and biological heterogeneity. To uncover biologically-driven subtypes of MDD, we applied an unsupervised data-driven framework to stratify 102 MDD patients on their neuroimaging signature, including extracted measures of cortical thickness, grey matter volumes, and white matter fractional anisotropy. Our novel analytical pipeline integrated different machine learning algorithms to harmonize data, perform data dimensionality reduction, and provide a stability-based relative clustering validation. The obtained clusters were characterized for immune-inflammatory peripheral biomarkers, TRD, history of childhood trauma and depressive symptoms. Our results indicated two different clusters of patients, differentiable with 67 % of accuracy: one cluster (n = 59) was associated with a higher proportion of TRD, and higher scores of energy-related depressive symptoms, history of childhood abuse and emotional neglect; this cluster showed a widespread reduction in cortical thickness (d = 0.43-1.80) and volumes (d = 0.45-1.05), along with fractional anisotropy in the fronto-occipital fasciculus, stria terminalis, and corpus callosum (d = 0.46-0.52); the second cluster (n = 43) was associated with cognitive and affective depressive symptoms, thicker cortices and wider volumes. Multivariate analyses revealed distinct brain-inflammation relationships between the two clusters, with increase in pro-inflammatory markers being associated with decreased cortical thickness and volumes. Our stratification of MDD patients based on structural neuroimaging identified clinically-relevant subgroups of MDD with specific symptomatic and immune-inflammatory profiles, which can contribute to the development of tailored personalized interventions for MDD.
PubMed: 38936143
DOI: 10.1016/j.euroneuro.2024.05.015 -
JMIR MHealth and UHealth Jun 2024Rising rates of psychological distress (symptoms of depression, anxiety, and stress) among adults in the United States necessitate effective mental wellness...
BACKGROUND
Rising rates of psychological distress (symptoms of depression, anxiety, and stress) among adults in the United States necessitate effective mental wellness interventions. Despite the prevalence of smartphone app-based programs, research on their efficacy is limited, with only 14% showing clinically validated evidence. Our study evaluates Noom Mood, a commercially available smartphone-based app that uses cognitive behavioral therapy and mindfulness-based programming. In this study, we address gaps in the existing literature by examining postintervention outcomes and the broader impact on mental wellness.
OBJECTIVE
Noom Mood is a smartphone-based mental wellness program designed to be used by the general population. This prospective study evaluates the efficacy and postintervention outcomes of Noom Mood. We aim to address the rising psychological distress among adults in the United States.
METHODS
A 1-arm study design was used, with participants having access to the Noom Mood program for 16 weeks (N=273). Surveys were conducted at baseline, week 4, week 8, week 12, week 16, and week 32 (16 weeks' postprogram follow-up). This study assessed a range of mental health outcomes, including anxiety symptoms, depressive symptoms, perceived stress, well-being, quality of life, coping, emotion regulation, sleep, and workplace productivity (absenteeism or presenteeism).
RESULTS
The mean age of participants was 40.5 (SD 11.7) years. Statistically significant improvements in anxiety symptoms, depressive symptoms, and perceived stress were observed by week 4 and maintained through the 16-week intervention and the 32-week follow-up. The largest changes were observed in the first 4 weeks (29% lower, 25% lower, and 15% lower for anxiety symptoms, depressive symptoms, and perceived stress, respectively), and only small improvements were observed afterward. Reductions in clinically relevant anxiety (7-item generalized anxiety disorder scale) and depression (8-item Patient Health Questionnaire depression scale) criteria were also maintained from program initiation through the 16-week intervention and the 32-week follow-up. Work productivity also showed statistically significant results, with participants gaining 2.57 productive work days from baseline at 16 weeks, and remaining relatively stable (2.23 productive work days gained) at follow-up (32 weeks). Additionally, effects across all coping, sleep disturbance (23% lower at 32 weeks), and emotion dysregulation variables exhibited positive and significant trends at all time points (15% higher, 23% lower, and 25% higher respectively at 32 weeks).
CONCLUSIONS
This study contributes insights into the promising positive impact of Noom Mood on mental health and well-being outcomes, extending beyond the intervention phase. Though more rigorous studies are necessary to understand the mechanism of action at play, this exploratory study addresses critical gaps in the literature, highlighting the potential of smartphone-based mental wellness programs to lessen barriers to mental health support and improve diverse dimensions of well-being. Future research should explore the scalability, feasibility, and long-term adherence of such interventions across diverse populations.
Topics: Humans; Prospective Studies; Male; Female; Adult; Middle Aged; Surveys and Questionnaires; Mobile Applications; Health Promotion; Cognitive Behavioral Therapy; Program Evaluation; United States; Mindfulness; Quality of Life
PubMed: 38935946
DOI: 10.2196/54634 -
Journal of Clinical Psychopharmacology
Topics: Humans; Bipolar Disorder; Female; Pregnancy; Pregnancy Complications; Antimanic Agents; Antipsychotic Agents; Adult
PubMed: 38935569
DOI: 10.1097/JCP.0000000000001887 -
Annals of Intensive Care Jun 2024EEG reactivity is a predictor for neurological outcome in comatose patients after cardiac arrest (CA); however, its application is limited by variability in stimulus...
BACKGROUND
EEG reactivity is a predictor for neurological outcome in comatose patients after cardiac arrest (CA); however, its application is limited by variability in stimulus types and visual assessment. We aimed to evaluate the prognostic value of the quantitative analysis of EEG reactivity induced by standardized electrical stimulation and for early prognostication in this population.
METHODS
This prospective observational study recruited post-CA comatose patients in Xuanwu Hospital, Capital Medical University (Beijing, China) between January 2016 and June 2023. EEG reactivity to electrical or traditional pain stimulation was randomly performed via visual and quantitative analysis. Neurological outcome within 6 months was dichotomized as good (Cerebral Performance Categories, CPC 1-2) or poor (CPC 3-5).
RESULTS
Fifty-eight post-CA comatose patients were admitted, and 52 patients were included in the final analysis, of which 19 (36.5%) had good outcomes. EEG reactivity induced with the electrical stimulation had superior performance to the traditional pain stimulation for good outcome prediction (quantitative analysis: AUC 0.932 vs. 0.849, p = 0.048). When using the electrical stimulation, the AUC of EEG reactivity to predict good outcome by visual analysis was 0.838, increasing to 0.932 by quantitative analysis (p = 0.039). Comparing to the traditional pain stimulation by visual analysis, the AUC of EEG reactivity for good prognostication by the electrical stimulation with quantitative analysis was significantly improved (0.932 vs. 0.770, p = 0.004).
CONCLUSIONS
EEG reactivity induced by the standardized electrical stimulation in combination with quantitative analysis is a promising formula for post-CA comatose patients, with increased predictive accuracy.
PubMed: 38935167
DOI: 10.1186/s13613-024-01339-6 -
Laeknabladid Jul 2024Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a hereditary small vessel disease of the brain characterized by... (Review)
Review
Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a hereditary small vessel disease of the brain characterized by progressive white matter lesions, subcortical infarcts, and cognitive decline. This autosomal dominant disorder is caused by mutations in the NOTCH3 gene located on chromosome 19, resulting in the accumulation of granular osmiophilic material within the walls of small arteries and arterioles. Clinically, CADASIL typically manifests in mid-adulthood with recurrent ischemic events, migraine with aura, mood disturbances, and cognitive impairment. Neuroimaging plays a crucial role in the diagnosis of CADASIL, with characteristic findings including white matter hyperintensities particularly in the anterior temporal lobe and external capsule.
Topics: Humans; CADASIL; Receptor, Notch3; Genetic Predisposition to Disease; Phenotype; Mutation; Predictive Value of Tests; Risk Factors; Prognosis; Heredity; Magnetic Resonance Imaging; Cognition; Brain
PubMed: 38934718
DOI: 10.17992/lbl.2024.0708.801