The validity of daily patient-reported anxiety measured using smartphones and the association with stress, quality of life and functioning in patients with bipolar disorder

The Minimum Feature Set for Designing Mobile Apps to Support Bipolar Disorder-Affected Patients: Proposal of Essential Functions and Requirements

Research conducted on mobile apps providing mental health services has concluded that patients with mental disorders tend to use such apps to maintain mental health balance technology may help manage and monitor issues like bipolar disorder (BP). This study was conducted in four steps to identify the features of designing a mobile application for BP-affected patients including (1) a literature search, (2) analyzing existing mobile apps to examine their efficiency, (3) interviewing patients affected with BP to discover their needs, and 4) exploring the points of view of experts using a dynamic narrative survey. Literature search and mobile app analysis resulted in 45 features, which were later reduced to 30 after the experts were surveyed about the project. The features included the following: mood monitoring, sleep schedule, energy level evaluation, irritability, speech level, communication, sexual activity, self-confidence level, suicidal thoughts, guilt, concentration level, aggressiveness, anxiety, appetite, smoking or drug abuse, blood pressure, the patient's weight and the side effects of medication, reminders, mood data scales, diagrams or charts of the collected data, referring the collected data to a psychologist, educational information, sending feedbacks to patients using the application, and standard tests for mood assessment. The first phase of analysis should consider an expert and patient view survey, mood and medication tracking, as well as communication with other people in the same situation are the most features to be considered. The present study has identified the necessity of apps intended to manage and monitor bipolar patients to maximize efficiency and minimize relapse and side effects.

Associations between oxidative stress markers and patient-reported smartphone-based symptoms in patients newly diagnosed with bipolar disorder: An exploratory study

Oxidative stress generated nucleoside damage seems to represent key pathophysiological mechanisms of bipolar disorder (BD). Likewise, mood and activity are core features of BD and can be reliably monitored using smartphone-based applications. The aim was to investigate whether oxidative stress generated nucleoside damage could reflect psychopathology in BD using easily available and non-invasive patient-reported smartphone-based symptoms. We included 223 patients newly diagnosed with BD and employed linear mixed-effect regression models to associate baseline measurements of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) and 8-oxo-7,8-dihydroguanosine (8-oxoGuo) levels with patient-reported smartphone measures of mood, activity, anxiety, stress and sleep duration monitored three days prior to and 30 days after the baseline visit in the longitudinal Bipolar Illness Onset Study. In patients newly diagnosed with BD higher 8-oxoGuo levels were inversely associated with the patient-reported activity level (B = 0.953, 95%CI = 0.909;0.99, p = 0.043) and positively associated with patient-reported anxiety (B = 1.104, 95%CI = 1.022;1.161, p=0.012), perceived stress (B = 1.092, 95%CI = 1.009;1.183, p = 0.014) and sleep duration (B = 1.000, 95%CI = 1.000;1.001, p = 0.001), respectively, in analyses, adjusted for sex and age. The associations between 8-oxoGuo levels and anxiety, perceived stress and sleep duration, respectively, withstood adjustment for sex, age, smoking, BMI and alcohol intake. No associations between 8-oxodG levels and patient-reported smartphone-based data were found and mood was not associated with 8-oxoGuo. Oxidative stress was associated with patient-reported smartphone-based data on activity, anxiety, stress and sleep duration pointing towards that oxidative stress generated nucleoside damage may reflect ongoing psychopathology in BD.

Affective lability and social functioning in severe mental disorders

Social functioning is impaired in severe mental disorders despite clinical remission, illustrating the need to identify other mechanisms that hinder psychosocial recovery. Affective lability is elevated and associated with an increased clinical burden in psychosis spectrum disorders. We aimed to investigate putative associations between affective lability and social functioning in 293 participants with severe mental disorders (schizophrenia- and bipolar spectrum), and if such an association was independent of well-established predictors of social impairments. The Affective Lability Scale (ALS-SF) was used to measure affective lability covering the dimensions of anxiety-depression, depression-elation and anger. The interpersonal domain of the Social Functioning Scale (SFS) was used to measure social functioning. Correlation analyses were conducted to investigate associations between affective lability and social functioning, followed by a hierarchical multiple regression and follow-up analyses in diagnostic subgroups. Features related to premorbid and clinical characteristics were entered as independent variables together with the ALS-SF scores. We found that higher scores on all ALS-SF subdimensions were significantly associated with lower social functioning (p < 0.005) in the total sample. For the anxiety-depression dimension of the ALS-SF, this association persisted after controlling for potential confounders such as premorbid social functioning, duration of untreated illness and current symptoms (p = 0.019). Our results indicate that elevated affective lability may have a negative impact on social functioning in severe mental disorders, which warrants further investigation. Clinically, it might be fruitful to target affective lability in severe mental disorders to improve psychosocial outcomes.

Portable technologies for digital phenotyping of bipolar disorder: A systematic review

BACKGROUND

Bias-prone psychiatric interviews remain the mainstay of bipolar disorder (BD) assessment. The development of digital phenotyping promises to improve BD management. We present a systematic review of the evidence about the use of portable digital devices for the identification of BD, BD types and BD mood states and for symptom assessment.

METHODS

We searched Web of Knowledge^SM, Scopus ®, IEEE Xplore, and ACM Digital Library databases (until 5/1/2021) for articles evaluating the use of portable/wearable digital devices, such as smartphone apps, wearable sensors, audio and/or visual recordings, and multimodal tools. The protocol is registered in PROSPERO (CRD42020200086).

RESULTS

We included 62 studies (2325 BD; 724 healthy controls, HC): 27 using smartphone apps, either for recording self-assessments (n = 10) or for passively gathering metadata (n = 7) or both (n = 10); 15 using wearable sensors for physiological parameters; 17 analysing audio and/or video recordings; 3 using multiple technologies. Two thirds of the included studies applied artificial intelligence (AI)-based approaches. They achieved fair to excellent classification performances.

LIMITATIONS

The included studies had small sample sizes and marked heterogeneity. Evidence of overfitting emerged, limiting generalizability. The absence of clear guidelines about reporting classification performances, with no shared standard metrics, makes results hardly interpretable and comparable.

CONCLUSIONS

New technologies offer a noteworthy opportunity to BD digital phenotyping with objectivity and high granularity. AI-based models could deliver important support in clinical decision-making. Further research and cooperation between different stakeholders are needed for addressing methodological, ethical and socio-economic considerations.

Prevalences of comorbid anxiety disorder and daily smartphone-based self-reported anxiety in patients with newly diagnosed bipolar disorder

BACKGROUND

Around 40% of patients with bipolar disorder (BD) additionally have anxiety disorder. The prevalence of anxiety in patients with newly diagnosed BD and their first-degree relatives (UR) has not been investigated.ObjectiveTo investigate (1) the prevalence of a comorbid anxiety diagnosis in patients with newly diagnosed BD and their UR, (2) sociodemographic and clinical differences between patients with and without a comorbid anxiety diagnosis and (3) the association between smartphone-based patient-reported anxiety and observer-based ratings of anxiety and functioning, respectively.

METHODS

We recruited 372 patients with BD and 116 of their UR. Daily smartphone-based data were provided from 125 patients. SCAN was used to assess comorbid anxiety diagnoses.

FINDINGS

In patients with BD, the prevalence of a comorbid anxiety disorder was 11.3% (N=42) and 10.3% and 5.9% in partial and full remission, respectively. In UR, the prevalence was 6.9%. Patients with a comorbid anxiety disorder had longer illness duration (p=0.016) and higher number of affective episodes (p=0.011). Smartphone-based patient-reported anxiety symptoms were associated with ratings of anxiety and impaired functioning (p<0.001).

LIMITATIONS

The SCAN interviews to diagnose comorbid anxiety disorder were carried out regardless of the participants' mood state.Clinical implicationsThe lower prevalence of anxiety in newly diagnosed BD than in later stages of BD indicates that anxiety increases with progression of BD. Comorbid anxiety seems associated with poorer clinical outcomes and functioning and smartphones are clinically useful for monitoring anxiety symptoms.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT02888262).

Effects of psychological and pharmacological interventions on anxiety symptoms in patients with bipolar disorder in full or partial remission: A systematic review

BACKGROUND

Anxiety symptoms are prevalent in bipolar disorder (BD) even during periods of remission and impede treatment efficacy, prognosis and functional capacity. This highlights a pressing clinical need to identify novel effective anxiety treatments. This systematic review aimed to evaluate the evidence within the field.

METHODS

Following PRISMA guidelines, we conducted a systematic search on PubMed, PsycInfo, EMBASE and Cochrane Library for randomised controlled trials (RCTs) targeting anxiety in remitted BD patients.

RESULTS

We identified 10 RCTs investigating the effects of psychological or pharmacological treatments on anxiety in remitted BD patients. Two studies of transdiagnostic personalised cognitive behavioural therapy (CBT) found a treatment-related reduction in anxiety. This evidence was preliminary given small sample size and use of self-report measures in a single-blind trial design, respectively. The remaining six psychological intervention trials provided more preliminary evidence due to several methodological challenges. The two pharmacological studies found anxiolytic effects of add-on olanzapine or methylene blue to lithium treatment, respectively. Nevertheless, this evidence should be interpreted with caution given high drop-out rates and substantial side-effects that may have impeded blinding.

LIMITATIONS

We did not conduct a quantitative meta-analysis.

CONCLUSIONS

There is preliminary evidence for beneficial effects of modified CBT and add-on pharmacotherapy on residual anxiety in BD. Future trials should pre-screen participants for anxiety, define one clinician-rated anxiety measurement as a primary outcome, and employ intention-to-treat analysis to assess treatment effect. This will advance treatment development and enable personalised approaches to address residual anxiety in BD, which has great clinical relevance.

Mood, activity, and sleep measured via daily smartphone-based self-monitoring in young patients with newly diagnosed bipolar disorder, their unaffected relatives and healthy control individuals

Diagnostic evaluations and early interventions of patients with bipolar disorder (BD) rely on clinical evaluations. Smartphones have been proposed to facilitate continuous and fine-grained self-monitoring of symptoms. The present study aimed to (1) validate daily smartphone-based self-monitored mood, activity, and sleep, against validated questionnaires and clinical ratings in young patients with newly diagnosed BD, unaffected relatives (UR), and healthy controls persons (HC); (2) investigate differences in daily smartphone-based self-monitored mood, activity, and sleep in young patients with newly diagnosed BD, UR, and HC; (3) investigate associations between self-monitored mood and self-monitored activity and sleep, respectively, in young patients with newly diagnosed BD. 105 young patients with newly diagnosed BD, 24 UR and 77 HC self-monitored 2 to 1077 days (median [IQR] = 65 [17.5-112.5]). There was a statistically significantly negative association between the mood item on Hamilton Depression Rating Scale (HAMD) and smartphone-based self-monitored mood (B = - 0.76, 95% CI - 0.91; - 0.63, p < 0.001) and between psychomotor item on HAMD and self-monitored activity (B = - 0.44, 95% CI - 0.63; - 0.25, p < 0.001). Smartphone-based self-monitored mood differed between young patients with newly diagnosed BD and HC (p < 0.001), and between UR and HC (p = 0.008) and was positively associated with smartphone-based self-reported activity (p < 0.001) and sleep duration (p < 0.001). The findings support the potential of smartphone-based self-monitoring of mood and activity as part of a biomarker for young patients with BD and UR. Smartphone-based self-monitored mood is better to discriminate between young patients with newly diagnosed BD and HC, and between UR and HC, compared with smartphone-based activity and sleep.Trial registration clinicaltrials.gov NCT0288826.

Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study

BACKGROUND

Smartphone-based ecological momentary assessment (EMA) is a promising methodology for mental health research. The objective of this study is to determine the feasibility of smartphone-based active and passive EMA in psychiatric outpatients and student controls.

METHODS

Two smartphone applications -MEmind and eB²- were developed for behavioral active and passive monitoring. The applications were tested in psychiatric patients with a history of suicidal thoughts and/or behaviors (STB), psychiatric patients without a history of STB, and student controls. Main outcome was feasibility, measured as response to recruitment, retention, and EMA compliance. Secondary outcomes were patterns of smartphone usage.

RESULTS

Response rate was 87.3% in patients with a history of STB, 85.1% in patients without a history of STB, and 75.0% in student controls. 457 participants installed the MEmind app (120 patients with a history of STB and 337 controls) and 1,708 installed the eB² app (139 patients with a history of STB, 1,224 patients with no history of STB and 346 controls). For the MEmind app, participants were followed-up for a median of 49.5, resulting in 22,622 person-days. For the eB² application, participants were followed-up for a median of 48.9 days, resulting in 83,521 person-days. EMA compliance rate was 65.00% in suicidal patients and 75.21% in student controls. At the end of the follow-up, over 60% of participants remained in the study.

LIMITATIONS

Cases and controls were not matched by age and sex. Cases were patients who were receiving adequate psychopharmacological treatment and attending their appointments, which may result in an overstatement of clinical compliance.

CONCLUSIONS

Smartphone-based active and passive monitoring are feasible methods in psychiatric patients in real-world settings. The development of applications with friendly interfaces and directly useful features can help increase engagement without using incentives. The MEmind and eB² applications are promising clinical tools that could contribute to the management of mental disorders. In the near future, these applications could serve as risk monitoring devices in the clinical practice.