Lifestyle in bipolar disorder: A cross-sectional study.

BACKGROUND: Modifiable lifestyle behaviors are important factors for improving mental health, yet there has been a lack of research studying lifestyle as a multidimensional construct in bipolar disorder (BD). The aim of this cross-sectional study was to compare the lifestyle patterns of individuals with BD in a current mood episode with healthy controls (HCs) using the Short Multidimensional Inventory Lifestyle Evaluation (SMILE). MATERIALS AND METHODS: The sample consisted of 46 individuals with BD currently experiencing a depressive or manic episode and 50 HC, assessed using the MINI International Neuropsychiatric Interview, Montgomery-Åsberg Depression Rating Scale (MADRS), and the Young Mania Rating Scale (YMRS). The SMILE scale assesses lifestyle across seven domains: diet and nutrition, substance abuse, physical activity, stress management, restorative sleep, social support, and environmental exposures. Between-groups comparisons were performed based on the presence of a psychiatric diagnosis and the type of BD episode. RESULTS: We found significant differences in the total SMILE score (r=0.75, p<0.001) and in scores from each domain of the scale between BD and HC (p<0.05), where individuals with BD in a depressive or manic episode with or without mixed features reported worse lifestyle across all domains. Differences between individuals with BD in different mood episodes across domains on the SMILE scale were non-significant. CONCLUSION: Findings from this study highlight the presence of unhealthy lifestyle patterns in people with BD regardless of the polarity of their mood episode. Implementation of multidimensional lifestyle assessments is an essential step toward detecting the clustering of unhealthy lifestyle patterns in BD.

Lifestyle interventions for bipolar disorders: A systematic review and meta-analysis.

This review and meta-analysis aimed to describe the existing literature on interventions for bipolar disorder (BD) targeting the 6 pillars of Lifestyle Psychiatry: diet, physical activity (PA), substance use (SU), sleep, stress management, and social relationships (SR). Randomized Controlled Trials that examined the efficacy of lifestyle interventions targeting improvement in depressive/(hypo)manic symptom severity, lifestyle patterns, functioning, quality of life, and/or circadian rhythms were included. The systematic review included 18 studies, while the meta-analysis included studies targeting the same lifestyle domains and outcomes. Sleep (n = 10), PA (n = 9), and diet (n = 8) were the most targeted domains, while SU, SM and SR were least targeted (n = 4 each). Combined diet and PA interventions led to significant improvements in depressive symptoms (SMD: -0.46; 95%CI: -0.88, -0.04; p = 0.03), and functioning (SMD: -0.47; 95%CI: -0.89, -0.05; p = 0.03). Sleep interventions also led to significant improvements in depressive symptoms (SMD: -0.80; 95%CI: -1.21, -0.39; p < 0.01). Future research should focus on developing more multidimensional lifestyle interventions for a potentially greater impact on clinical and functional outcomes of BD.

Lifestyle Behaviors, Depression, and Anxiety Among Individuals Living in Canada During the COVID-19 Pandemic.

The aim of our study was to investigate the association between lifestyle behaviors and symptoms of depression and anxiety during the COVID-19 pandemic in Canada. A web survey was conducted between July 3-August 3, 2020, across Canada. The main outcomes considered were a positive screening for depression, as evaluated by the PHQ-2 and positive screening for anxiety, as evaluated by the GAD-7. Lifestyle behaviors were assessed using the Short Multidimensional Lifestyle Inventory Evaluation-Confinement (SMILE-C), an instrument adapted for lifestyle behaviors during the COVID-19 pandemic. The total sample size included 404 participants, of which 24.3% had a positive screen for depression, 20.5% for anxiety, and 15.5% for both. We found significant differences in SMILE-C scores between individuals with a positive and individuals with a negative screen for depression (P < .001). Likewise, there were significant differences in SMILE-C scores between individuals with a positive and individuals with a negative screen for anxiety (P < .001). We found an association between unhealthy lifestyle behaviors and symptoms of depression and anxiety during the COVID-19 lockdown in Canada. The findings highlight the importance of lifestyle medicine (LM) education and targeted lifestyle interventions to promote healthy behaviors and help reduce the burden of mental disorders.

Cognitive impairment in bipolar disorder in comparison to mild cognitive impairment and dementia: a systematic review.

OBJECTIVE: To conduct a systematic review to describe cognitive abilities in bipolar disorder (BD) in comparison to cognitive abilities in mild cognitive impairment (MCI) and dementia. METHODS: A literature search was performed with no year or language restrictions. The search yielded 1,461 articles, with 1,261 remaining after removal of duplicates, five of which were suitable for the systematic review: two for the comparison between BD and MCI and three comparing BD and dementia. RESULTS: Analyses from our systematic review showed that euthymic individuals with BD present impairments in cognitive domains such as attention and executive functioning, motor skills, conceptual thinking, and visuo-spatial abilities that are equally severe as or more severe than the impairments observed in individuals with MCI. In contrast, studies comparing BD and dementia indicated that Alzheimer's disease (AD) dementia and behavioral variant frontotemporal dementia (bvFTD) both showed greater cognitive deficits than BD during euthymia, whereas BD during a mood episode demonstrated higher cognitive impairments than bvFTD. CONCLUSION: Findings from our systematic review suggest that cognitive impairments in euthymic BD fall into a range between the impairments seen in MCI and those seen in dementia. More studies are needed to analyze these comparisons, while also focusing on comparing different clinical stages of BD with MCI and dementia to analyze the progression of the clinical course and cognitive dysfunction in BD.

Lifestyle predictors of depression and anxiety during COVID-19: a machine learning approach.

INTRODUCTION: Recent research has suggested an increase in the global prevalence of psychiatric symptoms during the COVID-19 pandemic. This study aimed to assess whether lifestyle behaviors can predict the presence of depression and anxiety in the Brazilian general population, using a model developed in Spain. METHODS: A web survey was conducted during April-May 2020, which included the Short Multidimensional Inventory Lifestyle Evaluation (SMILE) scale, assessing lifestyle behaviors during the COVID-19 pandemic. Depression and anxiety were examined using the PHQ-2 and the GAD-7, respectively. Elastic net, random forest, and gradient tree boosting were used to develop predictive models. Each technique used a subset of the Spanish sample to train the models, which were then tested internally (vs. the remainder of the Spanish sample) and externally (vs. the full Brazilian sample), evaluating their effectiveness. RESULTS: The study sample included 22,562 individuals (19,069 from Brazil, and 3,493 from Spain). The models developed performed similarly and were equally effective in predicting depression and anxiety in both tests, with internal test AUC-ROC values of 0.85 (depression) and 0.86 (anxiety), and external test AUC-ROC values of 0.85 (depression) and 0.84 (anxiety). Meaning of life was the strongest predictor of depression, while sleep quality was the strongest predictor of anxiety during the COVID-19 epidemic. CONCLUSIONS: Specific lifestyle behaviors during the early COVID-19 epidemic successfully predicted the presence of depression and anxiety in a large Brazilian sample using machine learning models developed on a Spanish sample. Targeted interventions focused on promoting healthier lifestyles are encouraged.

Dropout in brief psychotherapy for major depressive disorder: Randomized clinical trial.

The aim of this paper is to analyse the factors associated with the dropout from brief psychotherapy for adults with major depressive disorder (MDD) treated at a mental health outpatient clinic. This is a randomized clinical trial with two models of psychotherapy: cognitive behavioural therapy (CBT) and supportive expressive dynamic psychotherapy (SEDP). MDD and anxiety disorders were evaluated through the Mini International Neuropsychiatric Interview-Plus. The personality disorders were evaluated by the Millon Clinical Multiaxial Inventory-III. The severity of depressive symptoms was measured using the Beck Depression Inventory-II and resilience through Resilience Scale. Of the 215 participants, 41.9% abandoned psychotherapy (n = 90), and, of these, 54.4% (n = 49) abandoned after the fourth session. The proportion of psychotherapy dropout was higher among those with nonwhite skin colour, belonging to economic classes C and D, who had children and whose depressive symptoms were moderate. Presence of obsessive-compulsive personality trait was protective against dropout. The damage caused by this abrupt interruption is evident for all those involved in the psychotherapeutic process, so the clinician should pay attention to the predictors found in this study in order to develop strategies that promote therapeutic adherence.

Cognitive impairment in bipolar disorder in comparison to mild cognitive impairment and dementia: a systematic review

Abstract Objective To conduct a systematic review to describe cognitive abilities in bipolar disorder (BD) in comparison to cognitive abilities in mild cognitive impairment (MCI) and dementia. Methods A literature search was performed with no year or language restrictions. The search yielded 1,461 articles, with 1,261 remaining after removal of duplicates, five of which were suitable for the systematic review: two for the comparison between BD and MCI and three comparing BD and dementia. Results Analyses from our systematic review showed that euthymic individuals with BD present impairments in cognitive domains such as attention and executive functioning, motor skills, conceptual thinking, and visuo-spatial abilities that are equally severe as or more severe than the impairments observed in individuals with MCI. In contrast, studies comparing BD and dementia indicated that Alzheimer's disease (AD) dementia and behavioral variant frontotemporal dementia (bvFTD) both showed greater cognitive deficits than BD during euthymia, whereas BD during a mood episode demonstrated higher cognitive impairments than bvFTD. Conclusion Findings from our systematic review suggest that cognitive impairments in euthymic BD fall into a range between the impairments seen in MCI and those seen in dementia. More studies are needed to analyze these comparisons, while also focusing on comparing different clinical stages of BD with MCI and dementia to analyze the progression of the clinical course and cognitive dysfunction in BD.PROSPERO registration ID: CRD42020150412

Lifestyle predictors of depression and anxiety during COVID-19: a machine learning approach

Abstract Introduction Recent research has suggested an increase in the global prevalence of psychiatric symptoms during the COVID-19 pandemic. This study aimed to assess whether lifestyle behaviors can predict the presence of depression and anxiety in the Brazilian general population, using a model developed in Spain. Methods A web survey was conducted during April-May 2020, which included the Short Multidimensional Inventory Lifestyle Evaluation (SMILE) scale, assessing lifestyle behaviors during the COVID-19 pandemic. Depression and anxiety were examined using the PHQ-2 and the GAD-7, respectively. Elastic net, random forest, and gradient tree boosting were used to develop predictive models. Each technique used a subset of the Spanish sample to train the models, which were then tested internally (vs. the remainder of the Spanish sample) and externally (vs. the full Brazilian sample), evaluating their effectiveness. Results The study sample included 22,562 individuals (19,069 from Brazil, and 3,493 from Spain). The models developed performed similarly and were equally effective in predicting depression and anxiety in both tests, with internal test AUC-ROC values of 0.85 (depression) and 0.86 (anxiety), and external test AUC-ROC values of 0.85 (depression) and 0.84 (anxiety). Meaning of life was the strongest predictor of depression, while sleep quality was the strongest predictor of anxiety during the COVID-19 epidemic. Conclusions Specific lifestyle behaviors during the early COVID-19 epidemic successfully predicted the presence of depression and anxiety in a large Brazilian sample using machine learning models developed on a Spanish sample. Targeted interventions focused on promoting healthier lifestyles are encouraged.

Risk factors for new-onset bipolar disorder in a community cohort: A five-year follow up study.

The aim of this study was to assess the risk factors for new-onset Bipolar Disorder (BD) in a community sample of young adults. This is a prospective cohort study including a population-based sample of young adults aged between 18-24 years. The baseline took place from 2007 to 2009, and 1560 subjects were included. Five years after, 1244 individuals were re-evaluated (79.7% retention). Substance abuse/dependence was assessed using the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), and mental disorders were assessed using the Mini International Neuropsychiatric Interview 5.0 (MINI) at both waves. The cumulative incidence of BD in five years was 4.6%. There was no significant association between sociodemographic factors and BD incidence. Tobacco, cannabis, cocaine/crack, other substances abuse/dependence increased the relative risk for BD. Depressive, anxiety, post-traumatic stress disorders, and the suicide risk increased the relative risk to BD. Depressive episode was the strongest risk factor for BD, followed by other mental disorders and substance abuse/dependence in a probabilistic community sample of young adults. Preventive actions in mental health directed at the non-clinical population are needed for early detection and better management of BD.

Cognitive complaints in individuals recently diagnosed with bipolar disorder: A cross-sectional study.

AIM: To assess the differences in subjective cognitive dysfunction between major depressive disorder (MDD) and recently diagnosed Bipolar Disorder (BD) across euthymia and mood episodes. METHODS: This is a cross-sectional study corresponding to the second wave of a longitudinal study. The first wave consisted of subjects aged between 18 and 60 diagnosed with MDD. In the follow up after three years (second wave), conversion from MDD to BD diagnosis was assessed by qualified psychologists using the Mini International Neuropsychiatric Interview (MINI-Plus). Subjects were categorized in four diagnostic groups: euthymic MDD, MDD in a current mood episode, euthymic BD, and BD in a current mood episode. All subjects completed the Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA), an instrument specifically designed for detecting subjective cognitive deficits in BD. RESULTS: The total sample (n = 468) included 410 subjects with MDD and 58 individuals recently diagnosed with BD. We subdivided the 2 groups based on their current mood state, and found a significant difference in COBRA total scores between euthymic BD individuals (median 17.00 [IQR: 8.75 - 20.75]) and euthymic MDD subjects (median 8.00 [IRQ: 5.00 - 14.00], p = 0.002), showing higher subjective cognitive dysfunction in individuals recently diagnosed with BD. The differences remained significant after adjusting for the presence of lifetime psychotic symptoms. We found no differences between MDD and BD during an acute mood episode. LIMITATION: The small sample size of individuals with BD. CONCLUSION: The findings suggest a higher presence of subjective cognitive complaints among individuals recently diagnosed with BD in comparison to individuals with MDD during euthymia.

Sleep alterations in individuals recently diagnosed with bipolar disorder across different mood stages.

OBJECTIVES: To assess the differences in sleep impairments in major depressive disorder (MDD) and individuals recently diagnosed with bipolar disorder (BD) across different mood stages. METHODS: This is a cross-sectional study corresponding to the second wave of a prospective clinical cohort of a sample of outpatients. The first wave included subjects diagnosed with MDD aged 18 to 60 years. Averaging 3 years after the first phase (second wave), conversion from MDD to BD diagnosis was assessed using the Mini International Neuropsychiatric Interview. The total sample was divided into four groups: euthymic MDD, MDD in a current episode, euthymic BD, and BD in a current mood episode. The sleep alterations were assessed using the Pittsburgh Sleep Quality Index. RESULTS: The sample included 468 subjects (261 euthymic MDD, 149 MDD currently depressed, 16 euthymic BD, and 42 BDs currently in a (hypo)manic or depressive episode). Euthymic BD differed from euthymic MDD only in the domains of sleep efficiency and sleep disturbances, showing lower sleep efficiency (PR 4.91 [95%CI 1.94 - 12.42]) and higher sleep disturbances (PR 3.38 [95%CI 1.32 - 8.67]) in subjects recently diagnosed with BD during euthymia. These differences remained significant after adjusting for the potential confounding factors. CONCLUSIONS: The findings point out the relevance of regular sleep assessments in individuals recently diagnosed with BD, since the differences in sleep quality observed could provide insights regarding prognosis, treatment, and the extent to which these individuals display significant subsyndromal symptomatology, even in the absence of a mood episode.

What Are We Measuring When We Evaluate Digital Interventions for Improving Lifestyle? A Scoping Meta-Review.

Background: Lifestyle Medicine (LM) aims to address six main behavioral domains: diet/nutrition, substance use (SU), physical activity (PA), social relationships, stress management, and sleep. Digital Health Interventions (DHIs) have been used to improve these domains. However, there is no consensus on how to measure lifestyle and its intermediate outcomes aside from measuring each behavior separately. We aimed to describe (1) the most frequent lifestyle domains addressed by DHIs, (2) the most frequent outcomes used to measure lifestyle changes, and (3) the most frequent DHI delivery methods. Methods: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR) Extension for Scoping Reviews. A literature search was conducted using MEDLINE, Cochrane Library, EMBASE, and Web of Science for publications since 2010. We included systematic reviews and meta-analyses of clinical trials using DHI to promote health, behavioral, or lifestyle change. Results: Overall, 954 records were identified, and 72 systematic reviews were included. Of those, 35 conducted meta-analyses, 58 addressed diet/nutrition, and 60 focused on PA. Only one systematic review evaluated all six lifestyle domains simultaneously; 1 systematic review evaluated five lifestyle domains; 5 systematic reviews evaluated 4 lifestyle domains; 14 systematic reviews evaluated 3 lifestyle domains; and the remaining 52 systematic reviews evaluated only one or two domains. The most frequently evaluated domains were diet/nutrition and PA. The most frequent DHI delivery methods were smartphone apps and websites. Discussion: The concept of lifestyle is still unclear and fragmented, making it hard to evaluate the complex interconnections of unhealthy behaviors, and their impact on health. Clarifying this concept, refining its operationalization, and defining the reporting guidelines should be considered as the current research priorities. DHIs have the potential to improve lifestyle at primary, secondary, and tertiary levels of prevention-but most of them are targeting clinical populations. Although important advances have been made to evaluate DHIs, some of their characteristics, such as the rate at which they become obsolete, will require innovative research designs to evaluate long-term outcomes in health.