Is a SIMPLe smartphone application capable of improving biological rhythms in bipolar disorder?

Environmental pollution and extreme weather conditions: insights into the effect on mental health

Environmental pollution exposures, including air, soil, water, light, and noise pollution, are critical issues that may implicate adverse mental health outcomes. Extreme weather conditions, such as hurricanes, floods, wildfires, and droughts, may also cause long-term severe concerns. However, the knowledge about possible psychiatric disorders associated with these exposures is currently not well disseminated. In this review, we aim to summarize the current knowledge on the impact of environmental pollution and extreme weather conditions on mental health, focusing on anxiety spectrum disorders, autism spectrum disorders, schizophrenia, and depression. In air pollution studies, increased concentrations of PM2.5, NO2, and SO2 were the most strongly associated with the exacerbation of anxiety, schizophrenia, and depression symptoms. We provide an overview of the suggested underlying pathomechanisms involved. We highlight that the pathogenesis of environmental pollution-related diseases is multifactorial, including increased oxidative stress, systematic inflammation, disruption of the blood-brain barrier, and epigenetic dysregulation. Light pollution and noise pollution were correlated with an increased risk of neurodegenerative disorders, particularly Alzheimer's disease. Moreover, the impact of soil and water pollution is discussed. Such compounds as crude oil, heavy metals, natural gas, agro-chemicals (pesticides, herbicides, and fertilizers), polycyclic or polynuclear aromatic hydrocarbons (PAH), solvents, lead (Pb), and asbestos were associated with detrimental impact on mental health. Extreme weather conditions were linked to depression and anxiety spectrum disorders, namely PTSD. Several policy recommendations and awareness campaigns should be implemented, advocating for the advancement of high-quality urbanization, the mitigation of environmental pollution, and, consequently, the enhancement of residents' mental health.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force

BACKGROUND

The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established.

OBJECTIVES

To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators.

METHODS

We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668).

RESULTS

The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators.

CONCLUSION

We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

Real-world Implementation of a Smartphone-Based Psychoeducation Program for Bipolar Disorder: Observational Ecological Study

BACKGROUND

SIMPLe is an internet-delivered self-management mobile app for bipolar disorder (BD) designed to combine technology with evidence-based interventions and facilitate access to psychoeducational content. The SIMPLe app was launched to the real world to make it available worldwide within the context of BD treatment.

OBJECTIVE

The main aims of this study are as follows: to describe app use, engagement, and retention rates based on server data; to identify patterns of user retention over the first 6-month follow-up of use; and to explore potential factors contributing to discontinuation of app use.

METHODS

This was an observational ecological study in which we pooled available data from a real-world implementation of the SIMPLe app. Participation was open on the project website, and the data-collection sources were a web-based questionnaire on clinical data and treatment history administered at inclusion and at 6 months, subjective data gathered through continuous app use, and the use patterns captured by the app server. Characteristics and engagement of regular users, occasional users, and no users were compared using 2-tailed t tests or analysis of variance or their nonparametric equivalent. Survival analysis and risk functions were applied to regular users' data to examine and compare use and user retention. In addition, a user evaluation analysis was performed based on satisfaction, perceived usefulness, and reasons to discontinue app use.

RESULTS

We included 503 participants with data collected between 2016 and 2018, of whom 77.5% (n=390) used the app. Among the app users, 44.4% (173/390) completed the follow-up assessment, and data from these participants were used in our analyses. Engagement declined gradually over the first 6 months of use. The probability of retention of the regular users after 1 month of app use was 67.4% (263/390; 95% CI 62.7%-72.4%). Age (P=.002), time passed since illness onset (P<.001), and years since diagnosis of BD (P=.048) correlate with retention duration. In addition, participants who had been diagnosed with BD for longer used the app on more days (mean 97.73, SD 69.15 days; P=.002) than those who had had a more recent onset (mean 66.49, SD 66.18 days; P=.002) or those who had been diagnosed more recently (mean 73.45, SD 66 days; P=.01).

CONCLUSIONS

The user retention rate of the app decreased rapidly after each month until reaching only one-third of the users at 6 months. There exists a strong association between age and app engagement of individuals with BD. Other variables such as years lived with BD, diagnosis of an anxiety disorder, and taking antipsychotics seem relevant as well. Understanding these associations can help in the definition of the most suitable user profiles for predicting trends of engagement, optimization of app prescription, and management.

The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review

BACKGROUND

The number of self-monitoring apps for bipolar disorder (BD) is increasing. The involvement of users in human-computer interaction (HCI) research has a long history and is becoming a core concern for designers working in this space. The application of models of involvement, such as user-centered design, is becoming standardized to optimize the reach, adoption, and sustained use of this type of technology.

OBJECTIVE

This paper aims to examine the current ways in which users are involved in the design and evaluation of self-monitoring apps for BD by investigating 3 specific questions: are users involved in the design and evaluation of technology? If so, how does this happen? And what are the best practice ingredients regarding the design of mental health technology?

METHODS

We reviewed the available literature on self-tracking technology for BD and make an overall assessment of the level of user involvement in design. The findings were reviewed by an expert panel, including an individual with lived experience of BD, to form best practice ingredients for the design of mental health technology. This combines the existing practices of patient and public involvement and HCI to evolve from the generic guidelines of user-centered design and to those that are tailored toward mental health technology.

RESULTS

For the first question, it was found that out of the 11 novel smartphone apps included in this review, 4 (36%) self-monitoring apps were classified as having no mention of user involvement in design, 1 (9%) self-monitoring app was classified as having low user involvement, 4 (36%) self-monitoring apps were classified as having medium user involvement, and 2 (18%) self-monitoring apps were classified as having high user involvement. For the second question, it was found that despite the presence of extant approaches for the involvement of the user in the process of design and evaluation, there is large variability in whether the user is involved, how they are involved, and to what extent there is a reported emphasis on the voice of the user, which is the ultimate aim of such design approaches. For the third question, it is recommended that users are involved in all stages of design with the ultimate goal of empowering and creating empathy for the user.

CONCLUSIONS

Users should be involved early in the design process, and this should not just be limited to the design itself, but also to associated research ensuring end-to-end involvement. Communities in health care-based design and HCI design need to work together to increase awareness of the different methods available and to encourage the use and mixing of the methods as well as establish better mechanisms to reach the target user group. Future research using systematic literature search methods should explore this further.

Behavioural and Self-Reported Data Collected from Smartphones in the Assessment of Depressive and Manic Symptoms for Bipolar Disorder Patients: Prospective Observational Study

BACKGROUND

Smartphones allow for real-time monitoring of patients' behavioural activities in a naturalistic setting. These data are suggested as markers of mental state in bipolar disorder (BD).

OBJECTIVE

We assess the relations between data collected from smartphones and the clinically rated depressive and manic symptoms together with the corresponding affective states in BD.

METHODS

BDmon - a dedicated mobile app was developed and installed on the patients' smartphones to automatically collect statistics about phone calls and text messages, as well as self-assessment of sleep and patient's mood. The final sample for the numerical analyses consisted of 51 eligible patients who participated in at least two psychiatric assessments and used the BDmon app (mean participation time: 208 days ± SD of 132 days). In total, 196 psychiatric assessments were performed using the Hamilton Depression Rating Scale (HDRS) and Young Mania Rating Scale (YMRS). Generalized linear mixed-effects models were applied to quantify the strength of the relation between the daily statistics about behavioural data collected automatically from smartphones and the affective symptoms and mood states in BD.

RESULTS

Objective behavioural data collected from smartphones and their relation to BD states were as follows: (1) depressed patients tended to make phone calls less frequently than in euthymia (β=-0.064, P=.01); (2) the number of incoming answered calls was lower in depression as compared to euthymia (β=-0.15, P=.01) and, at the same time, missed incoming calls were more frequent and increased as depressive symptoms intensified (β=4.431, P<.001; β=4.861, P<.001, respectively); (3) the fraction of outgoing calls was higher in manic states (β=2.73, P=.03); (4) the fraction of missed calls was higher in manic/mixed states as compared to euthymia (β=3.53, P=.01) and positively correlated to the severity of symptoms (β=2.991, P=.02); (5) variability of duration of outgoing calls was higher in manic/mixed states (β=1.22·10-3, P=.045) and positively correlated to the severity of symptoms (β=1.72·10-3, P=.02); (6) the number and length of sent text messages was higher in manic/mixed states as compared to euthymia (β=0.031, P=.01; β=0.015, P=.01, respectively) and positively correlated to the severity of manic symptoms (β=0.116, P<.001; β=0.022, P<.001). We also observed that self-assessment of mood was lower in depressive (β=-1.452, P<.001). and higher in manic states (β=0.509, P<.001).

CONCLUSIONS

Smartphone-based behavioural parameters are valid markers in assessing the severity of affective symptoms and discriminating between mood states. This opens a way toward early detection of worsening of the mental state and thereby increases the patient's chance of improving the course of the illness.

Using apps for bipolar disorder - An online survey of healthcare provider perspectives and practices

BACKGROUND

Smartphone apps have recognized potential for improving access to evidence-based care in the treatment of bipolar disorder (BD). Healthcare providers are well-positioned to play a role in guiding patients to access safe, evidence-supported, and trustworthy apps. However, little is known about whether and how clinicians use apps with people with BD: understanding practices and attitudes of healthcare providers is essential to support the implementation of mHealth interventions in a real-world context.

METHODS

A web-based survey was used to explore clinicians' attitudes towards, and use of apps when working with people with BD. Descriptive statistics were used to summarize quantitative findings. Free text responses were investigated using qualitative content analysis.

RESULTS

Eighty healthcare providers completed the survey. Approximately half of the respondents reported discussing or recommending apps in clinical practice with BD populations. Recommended apps were most commonly related to mood, sleep, and exercise. Barriers to discussing apps included a lack of healthcare provider knowledge/confidence, concerns about patients' ability to access apps, and beliefs that patients lacked interest in apps.

CONCLUSION

Although research suggests that people with BD are interested in using apps, uptake of such technology among clinicians is more limited. A lack of clinician knowledge regarding apps, combined with concerns about the digital divide and patient interest, may account for this relatively limited integration of apps into the management of BD. These findings emphasise the importance of considering the information needs of healthcare providers when planning dissemination strategies for app-based interventions for BD.

Living With Bipolar Disorder in the Time of Covid-19: Biorhythms During the Severe Lockdown in Cagliari, Italy, and the Moderate Lockdown in Tunis, Tunisia

Background: Restrictions during Covid-19 pandemic lockdown, in which rhythms of life have been compromised, can influence the course of bipolar disorder (BD). This study follows patients with bipolar disorder living in two geographically close cities (Cagliari and Tunis), but with different lockdown conditions: less severe in Tunis. Methods: Two cohorts were evaluated during lockdown (April 2020, t0) and 2 months later with lockdown lifted for a month (t1). Individuals were: over 18 years old without gender exclusion, BD I or II, in care for at least 1 year, received a clinical interview in the month before the start of the lockdown, stable clinically before the lockdown. The assessment was conducted by telephone by a psychiatrist or psychologist with good knowledge of patients. Diagnoses were made according to DSM-5 criteria. Depressive symptoms were collected through the Hamilton Rating Scale for Depression; cut-off 14 indicative of depressive episode. Circadian rhythms were measured using the BRIAN scale. Results: Forty individuals in Cagliari (70%female, age 48.57 ± 11.64) and 30 in Tunis (53.3% Female, age 41.8 ± 13.22) were recruited. In Cagliari at t0 45% had depressive episodes against none in Tunis, a similar difference appeared at t1. At t0 and t1 the Cagliari sample had more dysfunctional scores in the overall BRIAN scale and in the areas of sleep, activities and social rhythms; no differences were found in nutrition, both samples had predominantly nocturnal rhythm. In Cagliari at t0 and t1, the depressive sub-group showed more dysfunctional scores in the BRIAN areas sleep, activity, and nutrition. However, the differences in biological rhythms resulted, through ANCOVA analysis, independent of the co-presence of depressive symptoms. Discussion: A rigid lockdown could expose people with BD to depressive relapse through dysregulation of biological rhythms. The return to more functional rhythms did not appear 1 month after lockdown. The rekindling of the pandemic and the restoration of new restrictive measures will prevent, at least in the short term, the beneficial effect of a return to normality of the two cohorts. This was a limited exploratory study; future studies with larger samples and longer observational time are needed to verify the hypothesis.

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global functioning or the suicidality of patients, these aspects have so far not sufficiently been considered within the context of mobile-based disease management approaches. As a multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, we describe the theoretical and technological basis of our emotion-sensitive approach and do not present empirical data or a proof of concept. To our knowledge, the new assistance system incorporates the first mobile-based approach to analyze emotional expressions of patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models.

Smartphone Apps for the Treatment of Mental Disorders: Systematic Review

BACKGROUND

Smartphone apps are an increasingly popular means for delivering psychological interventions to patients suffering from a mental disorder. In line with this popularity, there is a need to analyze and summarize the state of the art, both from a psychological and technical perspective.

OBJECTIVE

This study aimed to systematically review the literature on the use of smartphones for psychological interventions. Our systematic review has the following objectives: (1) analyze the coverage of mental disorders in research articles per year; (2) study the types of assessment in research articles per mental disorder per year; (3) map the use of advanced technical features, such as sensors, and novel software features, such as personalization and social media, per mental disorder; (4) provide an overview of smartphone apps per mental disorder; and (5) provide an overview of the key characteristics of empirical assessments with rigorous designs (ie, randomized controlled trials [RCTs]).

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed. We performed searches in Scopus, Web of Science, American Psychological Association PsycNET, and Medical Literature Analysis and Retrieval System Online, covering a period of 6 years (2013-2018). We included papers that described the use of smartphone apps to deliver psychological interventions for known mental disorders. We formed multidisciplinary teams, comprising experts in psychology and computer science, to select and classify articles based on psychological and technical features.

RESULTS

We found 158 articles that met the inclusion criteria. We observed an increasing interest in smartphone-based interventions over time. Most research targeted disorders with high prevalence, that is, depressive (31/158,19.6%) and anxiety disorders (18/158, 11.4%). Of the total, 72.7% (115/158) of the papers focused on six mental disorders: depression, anxiety, trauma and stressor-related, substance-related and addiction, schizophrenia spectrum, and other psychotic disorders, or a combination of disorders. More than half of known mental disorders were not or very scarcely (<3%) represented. An increasing number of studies were dedicated to assessing clinical effects, but RCTs were still a minority (25/158, 15.8%). From a technical viewpoint, interventions were leveraging the improved modalities (screen and sound) and interactivity of smartphones but only sparingly leveraged their truly novel capabilities, such as sensors, alternative delivery paradigms, and analytical methods.

CONCLUSIONS

There is a need for designing interventions for the full breadth of mental disorders, rather than primarily focusing on most prevalent disorders. We further contend that an increasingly systematic focus, that is, involving RCTs, is needed to improve the robustness and trustworthiness of assessments. Regarding technical aspects, we argue that further exploration and innovative use of the novel capabilities of smartphones are needed to fully realize their potential for the treatment of mental health disorders.

Sleep and sleep treatments in bipolar disorder

Sleep and circadian disturbances in bipolar disorder are common and persistent within and between illness episodes. Insomnia, hypersomnia, reduced need for sleep, sleep schedule variability and circadian rhythm disorders are frequently observed. In this article, recent research is reviewed suggesting that the presence of sleep disturbance is associated with functional impairment, interacts with other physical and environmental systems (e.g. physical activity, light exposure), and may attenuate response to treatment. Established and emerging treatments for various sleep disturbances are reviewed, with emphasis on applications for light therapy and adapted cognitive behavioral therapy. There remains a critical need to understand the co-occurrence of various sleep disturbances, develop, and refine treatment approaches (especially for hypersomnia/long sleep duration) and adapt wearable and smartphone technologies to aid assessment and intervention.

Factor structure and measurement invariance of the problematic mobile phone use questionnaire-short version across gender in Chinese adolescents and young adults

BACKGROUND

Problematic mobile phone use (PMPU) has become a public health issue in China, particularly in adolescents and young adults. The Problematic Mobile Phone Use Questionnaire-Short Version (PMPUQ-SV) is a validated instrument that measures multiple aspects of PMPU. The current study aimed to test the psychometric characteristics of a Chinese adaption of the PMPUQ-SV and examine its measurement invariance across gender.

METHODS

A total of 2086 participants were recruited form nine schools (six undergraduate colleges and three vocational colleges) through an online platform. Measures included socio-demographic variables, patterns of mobile phone use, the Chinese version of the PMPUQ-SV (C-PMPUQ-SV), the Chinese version of the Smartphone Addiction Proneness Scale (C-SAPS), and the Depression Anxiety Stress Scales (DASS-21).

RESULTS

Exploratory and confirmatory factor analyses conducted in two independent subsamples confirmed that the postulated dimensions fit the data well. Four items, judged as either outdated or not adapted to the Chinese context, performed poorly and were removed, resulting in a shorter 11-item scale. Convergent validity was established through correlations between emotional symptoms and the C-PMPUQ-SV and addictive smartphone use. Additional measurement invariance analyses showed that the scale performed largely similarly in male and female participants.

CONCLUSIONS

The present study demonstrated that the C-PMPUQ-SV is an adequate instrument to study various types of PMPU in Chinese adolescents and young adults. The updated 11-item scale shortens the evaluation time and is adapted to assess contemporary smartphone use.

Personalized and precision medicine as informants for treatment management of bipolar disorder

DSM-5 diagnostic categories, defined by a set of psychopathological symptoms are heterogeneous conditions that may include different biological entities, with distinct etiopathogenesis, different courses and requiring different treatment management. For bipolar disorder the major evidences for this lack of validity are the long paths before a proper diagnosis, the inconsistence of treatment guidelines, the long phases of pharmacological adjustment and the low average of long-term treatment response rates. Personalized medicine for mental disorders aims to couple established clinical-pathological indexes with new molecular profiling to create diagnostic, prognostic and therapeutic strategies precisely tailored to each patient. Regarding bipolar disorder, the clinical history and presentation are still the most reliable markers in stratifying patients and guiding therapeutic management, despite the research goes to great lengths to develop new neuropsychological or biological markers that can reliably predict individual therapy effectiveness. We provide an overview of the advancements in personalized medicine in bipolar disorder, with particular attention to how psychopathology, age at onset, comorbidity, course and staging, genetic and epigenetic, imaging and biomarkers can influence treatment management and provide an integration to the conventional treatment guidelines. This approach may offer a new and rational path for the development of treatments for targeted subgroups of patients with bipolar disorder.

Psychosocial Interventions for Bipolar II Disorder

Bipolar II disorder causes significant suffering among patients and their families, some of which may be alleviated by psychotherapy alone or as an adjunct to pharmacotherapy. Psychotherapies may be more effective if modified to meet the specific needs of patients with bipolar II disorder.

Improving Functioning, Quality of Life, and Well-being in Patients With Bipolar Disorder

People with bipolar disorder frequently experience persistent residual symptoms, problems in psychosocial functioning, cognitive impairment, and poor quality of life. In the last decade, the treatment target in clinical and research settings has focused not only on clinical remission, but also on functional recovery and, more lately, in personal recovery, taking into account patients' well-being and quality of life. Hence, the trend in psychiatry and psychology is to treat bipolar disorder in an integrative and holistic manner. This literature review offers an overview regarding psychosocial functioning in bipolar disorder. First, a brief summary is provided regarding the definition of psychosocial functioning and the tools to measure it. Then, the most reported variables influencing the functional outcome in patients with bipolar disorder are listed. Thereafter, we include a section discussing therapies with proven efficacy at enhancing functional outcomes. Other possible therapies that could be useful to prevent functional decline and improve functioning are presented in another section. Finally, in the last part of this review, different interventions directed to improve patients' well-being, quality of life, and personal recovery are briefly described.

OpenSIMPLe: A real-world implementation feasibility study of a smartphone-based psychoeducation programme for bipolar disorder

BACKGROUND

Few evidence-based mental health apps are widely available to patients and, conversely, many of the available apps have not been appropriately evaluated. Given that the ultimate goal is to scale-up and open internet-based platforms (IBP), it is crucial to appropriately evaluate their real-world feasibility beforehand. We aimed to evaluate the implementation feasibility of a smartphone-based psychoeducational programme for bipolar disorder, exploring its long-term retention, usability, perceived helpfulness and satisfaction, alongside its impact on secondary health outcomes.

METHODS

Participants were recruited via the project website after completing an online screening questionnaire. They were requested to complete web-based questionnaires before using the app and after 6 months of use which included sociodemographic, illness and treatment variables, the world health organisation-five well-being index (WHO-5) and the short form health survey (SF-36). The follow-up questionnaires also contained satisfaction and usefulness questions.

RESULTS

201 participants took part in the study. According to their retention, 66.2% of the participants were classified as noncompleters and 33.8% as completers. The only predictor significantly associated with higher odds of retention was older age (OR = 1.021, p < 0.001). 62% of the users reported they were satisfied with the programme with a higher percentage among completers. Who-5 baseline and follow-up scores showed a significant improvement as well as 6 out of 8 domains of the SF-36.

LIMITATIONS

Screening and outcome measures were administered using exclusively self-reported online methods.

CONCLUSION

The 6-month attrition rate of the programme was high. Positive outcomes regarding satisfaction were found predominantly among completers. The optimal dosage and retention of IBP mental health programmes remain challenging issues that need further research.

Coping with the New Era: Noise and Light Pollution, Hperactivity and Steroid Hormones. Towards an Evolutionary View of Bipolar Disorders

Human population is increasing in immense cities with millions of inhabitants, in which life is expected to run 24 hours a day for seven days a week (24/7). Noise and light pollution are the most reported consequences, with a profound impact on sleep patterns and circadian biorhythms. Disruption of sleep and biorhythms has severe consequences on many metabolic pathways. Suppression of melatonin incretion at night and the subsequent effect on DNA methylation may increase the risk of prostate and breast cancer. A negative impact of light pollution on neurosteroids may also affect mood. People who carry the genetic risk of bipolar disorder may be at greater risk of full-blown bipolar disorder because of the impact of noise and light pollution on sleep patterns and circadian biorhythms. However, living in cities may also offers opportunities and might be selective for people with hyperthymic temperament, who may find themselves advantaged by increased energy prompted by increased stimulation produced by life in big cities. This might result in the spreading of the genetic risk of bipolar disorder in the coming decades. In this perspective the burden of poor quality of life, increased disability adjusted life years and premature mortality due to the increases of mood disorders is the negative side of a phenomenon that in its globality also shows adaptive aspects. The new lifestyle also influences those who adapt and show behaviors, reactions and responses that might resemble the disorder, but are on the adaptive side.

Toward Precision Psychiatry in Bipolar Disorder: Staging 2.0

Personalized treatment is defined as choosing the "right treatment for the right person at the right time." Although psychiatry has not yet reached this level of precision, we are on the way thanks to recent technological developments that may aid to detect plausible molecular and genetic markers. At the moment there are some models that are contributing to precision psychiatry through the concept of staging. While staging was initially presented as a way to categorize patients according to clinical presentation, course, and illness severity, current staging models integrate multiple levels of information that can help to define each patient's characteristics, severity, and prognosis in a more precise and individualized way. Moreover, staging might serve as the foundation to create a clinical decision-making algorithm on the basis of the patient's stage. In this review we will summarize the evolution of the bipolar disorder staging model in relation to the new discoveries on the neurobiology of bipolar disorder. Furthermore, we will discuss how the latest and future progress in psychiatry might transform current staging models into precision staging models.