An App-Based Digit Symbol Substitution Test for Assessment of Cognitive Deficits in Adults With Major Depressive Disorder: Evaluation Study.

BACKGROUND: Cognitive dysfunction is an impairing core symptom of depression. Among adults with major depressive disorder (MDD) treated with antidepressants, residual cognitive symptoms interfere with patient-reported outcomes. The foregoing characterization of cognitive symptoms provides the rationale for screening and assessing the severity of cognitive symptoms at point of care. However, clinical neurocognitive assessments are time-consuming and difficult, and they require specialist expertise to interpret them. A smartphone-delivered neurocognitive test may offer an effective and accessible tool that can be readily implemented into a measurement-based care framework. OBJECTIVE: We aimed to evaluate the use of a smartphone-delivered app-based version of the established Cognition Kit Digit Symbol Substitution Test (DSST) neurocognitive assessment compared to a traditional paper-and-pencil version. METHODS: Convergent validity and test-retest reliability of the 2 versions were evaluated. Patient satisfaction with the app was also assessed. RESULTS: Assessments made using the app-based Cognition Kit DSST were highly correlated with the standard paper-and-pencil version of the test, both at the baseline visit (r=0.69, df=27; P<.001) and at the end-of-study visit (r=0.82, df=27; P<.001), and they were positively evaluated by 30 patients as being user-friendly, easy to navigate, and preferable over the paper-and-pencil version of the DSST. However, although the app-based Cognition Kit DSST was validated in patients with MDD, it still needs to be evaluated in healthy controls. CONCLUSIONS: App-based DSST may facilitate a more personalized, convenient, and cost-effective method of cognitive assessment, helping to guide measurement-based care and psychotherapeutic and pharmacologic treatment options for patients with MDD. TRIAL REGISTRATION: ClinicalTrials.gov NCT03999567; https://tinyurl.com/2p8pnyv7.

The influence of prescriber and patient gender on the prescription of benzodiazepines: results from the Florida Medicaid Dataset.

BACKGROUND: Benzodiazepine (BZD) prescription rates have increased over the past decade in the United States. Available literature indicates that sociodemographic factors may influence diagnostic patterns and/or prescription behaviour. Herein, the aim of this study is to determine whether the gender of the prescriber and/or patient influences BZD prescription. METHODS: Cross-sectional study using data from the Florida Medicaid Managed Medical Assistance Program from January 1, 2018 to December 31, 2018. Eligible recipients ages 18 to 64, inclusive, enrolled in the Florida Medicaid plan for at least 1 day, and were dually eligible. Recipients either had a serious mental illness (SMI), or non-SMI and anxiety. RESULTS: Total 125 463 cases were identified (i.e., received BZD or non-BZD prescription). Main effect of patient and prescriber gender was significant F(1, 125 459) = 0.105, P = 0 .745, partial η2 < 0.001. Relative risk (RR) of male prescribers prescribing a BZD compared to female prescribers was 1.540, 95% confidence intervals (CI) [1.513, 1.567], whereas the RR of male patients being prescribed a BZD compared to female patients was 1.16, 95% CI [1.14, 1.18]. Main effects of patient and prescriber gender were statistically significant F(1, 125 459) = 188.232, P < 0.001, partial η2 = 0.001 and F(1, 125 459) = 349.704, P < 0.001, partial η2 = 0.013, respectively. CONCLUSIONS: Male prescribers are more likely to prescribe BZDs, and male patients are more likely to receive BZDs. Further studies are required to characterize factors that influence this gender-by-gender interaction.

Ecological momentary assessment of depressive symptoms using the mind.me application: Convergence with the Patient Health Questionnaire-9 (PHQ-9).

Ecological momentary assessment (EMA) for mental disorders, using application-based (app) technology capable of passive and ambient data collection, has been insufficiently evaluated and validated with rigorous, adequately-powered, high-quality studies. Herein, we sought to validate the mind.me application for the assessment of depressive symptoms in adults. Adults (ages 18-65) who self-identified as having clinically significant depressive symptoms [i.e. Patient Health Questionnaire 9 (PHQ-9) ≥ 5] utilized the mind.me app-a mobile phone technology that collects data passively and continuously, and is capable of integrating broad multimodal data [e.g., location variance (e.g. GPS), behavioural (e.g. social network activity), and communication data (e.g. SMS texting, phone calls)]. The primary outcome was predictive accuracy (i.e. convergent validity with depressive symptom measurement, as captured by the PHQ-9). 200 subjects were enrolled in the study (mean age 46 ± 12.71). The average PHQ-9 score was 12.8 ± 6.9. The predictive accuracy of the mind.me app was 0.91 ± 0.06. The sensitivity was 0.98 and the specificity was 0.93. The mind.me app was rated by 200 users as highly usable and informative to their illness. The mind.me app exhibits robust predictive accuracy in detecting depressive symptoms in adults with clinically relevant depressive symptoms. The mind.me app more specifically demonstrates convergence with the PHQ-9.

The utility of smartphone-based, ecological momentary assessment for depressive symptoms.

BACKGROUND: Major Depressive Disorder (MDD) is a common and debilitating mood disorder. Individuals with MDD are often misdiagnosed or diagnosed in an untimely manner, exacerbating existing functional impairments. Ecological momentary assessment (EMA) involves the repeated sampling of an individual's symptoms within their natural environment and has been demonstrated to assist in illness assessment and characterization. Capturing data in this way would set the stage for improved treatment outcomes and serve as a complementary resource in the management and treatment of depressive symptoms. METHODS: Online databases PubMed/MedLine and PsycINFO were searched using PRISMA guidelines and combinations of the following keywords: EMA, depression, smartphone app, diagnosing, symptoms, phone, app, ecological momentary assessment, momentary assessment, data mining, unobtrusive, passive data, GPS, sensor. RESULTS: A total of nineteen original articles were identified using our search parameters and ten articles met the inclusion criteria for full-text review. Among the ten relevant studies, three studies evaluated feasibility, seven evaluated detection, and three evaluated treatment of MDD. LIMITATIONS: Limitations include that the design of all of the studies included in this review are non-randomized. It should be noted that most of the studies included were pilot studies and/or exploratory trials lacking a control group. CONCLUSIONS: Available evidence suggests that the use of passive smartphone-based applications may lead to improved management of depressive symptoms. This review aids the creation of new EMA applications, highlights the potential of EMA usage in clinical settings and drug development, emphasizes the importance for regulation of applications in the mental health field, and provides insight into future directions.

The THINC-it Tool for Cognitive Assessment and Measurement in Major Depressive Disorder: Sensitivity to Change.

BACKGROUND: Herein, we sought to determine the sensitivity to change in cognitive function, as measured by the THINC-it tool, in a sample of adults with major depressive disorder (MDD) receiving standardized antidepressant therapy. METHODS: Adults meeting the DSM-5 criteria for MDD with at least moderate depressive symptom severity [i.e., Montgomery Åsberg Depression Rating Scale (MADRS) total score ≥ 20] were treated with open-label vortioxetine (10-20 mg/day, flexibly-dosed) for 8 weeks. The previously validated THINC-it tool was the primary dependent measure. The THINC-it tool was validated against the paper and pencil version of the Digit Symbol Substitution Test (DSST) and the Trails Making Test B (TMTB). RESULTS: After 8 weeks of treatment, adults with MDD exhibited improvement in cognitive function relative to healthy controls (e.g., processing speed) (p = 0.031). A subdomain measure of working memory (i.e., symbol check; SC) exhibited significant improvement at Weeks 2 and 8 in latency (p = 0.032), SC accuracy (p = 0.046), and objective z-score (p = 0.001) independent of depressive symptoms. A linear regression analysis determined that the THINC-it tool measures of processing speed, as well as executive function were significantly associated with changes observed on the pencil and paper version the Digit Symbol Substitution Test (DSST) (p = 0.002) and in Trails Making Test B (TMTB) (p = 0.003), respectively. CONCLUSION: The THINC-it tool demonstrates sensitivity to change in adults with MDD and is highly correlated with improvements on pencil and paper versions of DSST and TMTB. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier NCT03053362.

Projected increases in suicide in Canada as a consequence of COVID-19.

Macroeconomic indicators, notably unemployment, are significant moderators of suicide. We projected the number of excess suicides in Canada as a consequence of the impact of COVID-19 on unemployment. Annual suicide mortality (2000-2018) and unemployment (2000-2019) data were derived from Statistics Canada. Time-trend regression models were used to evaluate and predict the number of excess suicides in 2020 and 2021 for two possible projection scenarios following the COVID-19 pandemic: 1) an increase in unemployment of 1.6% in 2020, 1.2% in 2021, or 2) an increase in unemployment of 10.7% in 2020, 8.9% in 2021. A percentage point increase in unemployment was associated with a 1.0% increase in suicide between 2000 and 2018. In the first scenario, the rise in unemployment rates resulted in a projected total of 418 excess suicides in 2020-2021 (suicide rate per 100,000: 11.6 in 2020). In the second scenario, the projected suicide rates per 100,000 increased to 14.0 in 2020 and 13.6 in 2021, resulting in 2114 excess suicides in 2020-2021. These results indicate that suicide prevention in the context of COVID-19-related unemployment is a critical priority. Furthermore, timely access to mental healthcare, financial provisions and social/labour support programs, as well as optimal treatment for mental disorders is urgently needed.

What is bipolar disorder? A disease model of dysregulated energy expenditure.

Advances in the understanding and management of bipolar disorder (BD) have been slow to emerge. Despite notable recent developments in neurosciences, our conceptualization of the nature of this mental disorder has not meaningfully progressed. One of the key reasons for this scenario is the continuing lack of a comprehensive disease model. Within the increasing complexity of modern research methods, there is a clear need for an overarching theoretical framework, in which findings are assimilated and predictions are generated. In this review and hypothesis article, we propose such a framework, one in which dysregulated energy expenditure is a primary, sufficient cause for BD. Our proposed model is centered on the disruption of the molecular and cellular network regulating energy production and expenditure, as well its potential secondary adaptations and compensatory mechanisms. We also focus on the putative longitudinal progression of this pathological process, considering its most likely periods for onset, such as critical periods that challenges energy homeostasis (e.g. neurodevelopment, social isolation), and the resulting short and long-term phenotypical manifestations.

Suicide risk reduction in youths with attention-deficit/hyperactivity disorder prescribed methylphenidate: A Taiwan nationwide population-based cohort study.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) youths have increased suicide risk. Nevertheless, the beneficial effects of methylphenidate (MPH) on suicide attempt have received relatively little attention. AIMS: To investigate the MPH usage and the risk of suicide attempt among ADHD youths. METHODS: We identified 84,898 youths less than 18 years old with ADHD diagnosis between 1997 and 2013 from National Health Insurance, and examined whether MPH use affected suicide attempt risk using Cox proportional-hazards models. OUTCOME AND RESULTS: Among ADHD youths, reduction of suicide risk was found in patients prescribed 90-180days of MPH after adjusting for confounding factors (hazard ratio (HR): 0.41, 95% confidence interval (CI): 0.19-0.90) and a greater reduction in those prescribed more than 180days of MPH (HR: 0.28, 95% CI: 0.17-0.48). CONCLUSIONS AND IMPLICATIONS: We observed a 59% suicide attempt risk reduction among ADHD youths prescribed between 90 and 180days and a 72% risk reduction in those prescribed more than 180days of MPH. The protective benefit observed by the group prescribed MPH for longer duration underscores the importance of psychoeducation and compliance enhancement as part of ADHD management. Indication bias is identified as a limitation of this study, and future self-case control study to investigate the association between suicide attempt and ADHD medication is suggested. WHAT THIS PAPER ADDS: This nationwide population-based cohort study showed that among ADHD youths, reduction of suicide risk was observed in patients prescribed MPH for duration 90days and longer, underscoring the importance of appropriate ADHD pharmacotherapy and enhancing drug compliance.

Efficacy of antidepressants on measures of workplace functioning in major depressive disorder: A systematic review.

INTRODUCTION: Work-related disability and productivity loss in Major Depressive Disorder (MDD) are critical determinants of patient quality of life and contribute significantly to the human and economic costs of MDD. Notwithstanding the return to work and pre-morbid levels of functioning as a critical therapeutic objective among individuals with MDD, it is unclear whether antidepressant treatment significantly and reliably improves measures of workplace functioning. Herein, we investigate to what extent antidepressant treatment improves workplace functioning among adults with MDD. METHODS: We conducted a systematic review of randomized, double-blind, placebo-controlled or active comparator clinical trials primarily or secondarily investigating the efficacy of antidepressant agents on subjective ratings of workplace functioning and/or measures of work absence. RESULTS: Thirteen placebo-controlled and four active comparator clinical trials reported on the efficacy of agomelatine, bupropion, desvenlafaxine, duloxetine, fluoxetine, levomilnacipran, paroxetine, sertraline, venlafaxine, or vortioxetine on subjective measures of workplace impairment. Overall, antidepressant treatment improved standardized measures of workplace functioning (e.g., Sheehan Disability Scale-work item). One placebo-controlled trial of agomelatine and one clinical trial comparing the efficacy of vortioxetine to that of venlafaxine had mixed results on measures of work absence. LIMITATIONS: Included interventional trials evaluated work-related disability as a secondary outcome using subjective rating scales. CONCLUSION: Extant data suggest that antidepressant treatment improves workplace outcomes in MDD. The capability of antidepressants in improving measures of workplace functioning should be considered in cost-benefit analyses to better inform cost-modelling studies pertaining to antidepressant therapy.

Assessment of brain functional connectome alternations and correlation with depression and anxiety in major depressive disorders.

Major depressive disorder (MDD) is highly prevalent, recurrent, and associated with functional impairment, morbidity, and mortality. Herein, we aimed to identify disruptions in functional connectomics among subjects with MDD by using resting-state functional magnetic resonance imaging (rs-fMRI). Sixteen subjects with MDD and thirty health controls completed resting-state fMRI scans and clinical assessments (e.g., Hamilton Depression Rating Scale (HAMD) and Hospital Anxiety and Depression Scale (HADS)). We found higher amplitude of low frequency fluctuations (ALFF) bilaterally in the hippocampus and amygdala among MDD subjects when compared to healthy controls. Using graph theoretical analysis, we found decreased clustering coefficient, local efficiency, and transitivity in the MDD patients. Our findings suggest a potential biomarker for differentiating individuals with MDD from individuals without MDD.

The THINC-Integrated Tool (THINC-it) Screening Assessment for Cognitive Dysfunction: Validation in Patients With Major Depressive Disorder.

OBJECTIVE: To validate the THINC-integrated tool (THINC-it)-a freely available, patient-administered, computerized screening tool integrating subjective and objective measures of cognitive function in adults with major depressive disorder (MDD). METHODS: Subjects aged 18 to 65 years (n = 100) with recurrent MDD experiencing a major depressive episode of at least moderate severity were evaluated and compared to age-, sex-, and education-matched healthy controls (n = 100). Between January and June 2016, subjects completed the THINC-it, which includes variants of the Choice Reaction Time Identification Task (IDN), One-Back Test, Digit Symbol Substitution Test, Trail Making Test-Part B, and the Perceived Deficits Questionnaire for Depression-5-item (PDQ-5-D). RESULTS: The THINC-it required approximately 10 to 15 minutes for administration and was capable of detecting cognitive deficits in adults with MDD. A total of 44.4% of adults with MDD exhibited cognitive performance at ≥ 1.0 SD below that of healthy controls on standardized mean scores of the THINC-it. Concurrent validity of the overall tool, based on a calculated composite score, was acceptable (r = 0.539, P < .001). Concurrent validity of the component tests ranged from -0.083 (IDN) to 0.929 (PDQ-5-D). Qualitative survey results indicated that there was a high level of satisfaction and perceived value in administering the THINC-it regarding its impact on the appropriateness and quality of care being received. CONCLUSIONS: The THINC-it is a valid and sensitive tool for detecting cognitive dysfunction in adults with MDD that is free, easy to use, and rapidly administered. The THINC-it should be incorporated into the assessment and measurement of all patients with MDD, particularly among those with enduring functional impairment. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02508493.

Bipolar disorder and the risk of fracture: A nationwide population-based cohort study.

BACKGROUND: The co-primary aims are: 1) to compare the risk of fracture between adults with bipolar disorder and those without bipolar disorder; and 2) to assess whether lithium, anticonvulsants and antipsychotics reduce risk of fracture among individuals with bipolar disorder. METHODS: The analysis herein is a population-based retrospective cohort study, utilizing the National Health Insurance (NHI) medical claims data collected between 1997 and 2013 in Taiwan. We identified 3705 cases with incident diagnoses of bipolar disorder during study period and 37,050 matched controls without bipolar diagnoses. Incident diagnosis of fracture was operationalized as any bone fracture after the diagnosis of bipolar disorder or after the matched index date for controls. RESULTS: Bipolar patients had significantly higher risk of facture when compared to matched controls (17.6% versus 11.7%, respectively p<0.001). The hazard ratio (HR) was 1.33 (95% confidence interval [CI]＝1.23-1.48, p<0.001) after adjusting for covariates. Persons with bipolar disorder and a prior history of psychiatric hospitalization were had higher risk for bone fracture than those without prior history of psychiatric hospitalization when compared to match controls. Higher cumulative dose of antipsychotics or mood stabilizers did not increase the risk of fracture. LIMITATIONS: The diagnoses of bipolar disorder were not confirmed with structured clinical interview. Drug adherence, exact exposure dosage, smoking, lifestyle, nutrition and exercise habits were unable to be assessed in our dataset. CONCLUSIONS: Bipolar disorder is associated with increased risk of fracture, and higher cumulative dose of mood stabilizers and antipsychotics did not further increase the risk of fracture.

Does Pharmacogenomic Testing Improve Clinical Outcomes for Major Depressive Disorder? A Systematic Review of Clinical Trials and Cost-Effectiveness Studies.

OBJECTIVE: Pharmacogenomic testing has become scalable and available to the general public. Pharmacogenomics has shown promise for predicting antidepressant response and tolerability in the treatment of major depressive disorder (MDD). In theory, pharmacogenomics can improve clinical outcomes by guiding antidepressant selection and dosing. The current systematic review examines the extant literature to determine the impact of pharmacogenomic testing on clinical outcomes in MDD and assesses its cost-effectiveness. DATA SOURCES: The MEDLINE/PubMed and Google Scholar databases were systematically searched for relevant articles published prior to October 2015. Search terms included various combinations of the following: major depressive disorder (MDD), depression, mental illness, mood disorder, antidepressant, response, remission, outcome, pharmacogenetic, pharmacogenomics, pharmacodynamics, pharmacokinetic, genetic testing, genome wide association study (GWAS), CYP450, personalized medicine, cost-effectiveness, and pharmacoeconomics. STUDY SELECTION: Of the 66 records identified from the initial search, relevant clinical studies, written in English, assessing the cost-effectiveness and/or efficacy of pharmacogenomic testing for MDD were included. DATA EXTRACTION: Each publication was critically examined for relevant data. RESULTS: Two nonrandomized, open-label, 8-week, prospective studies reported overall greater improvement in depressive symptom severity in the group of MDD subjects receiving psychiatric care guided by results of combinatorial pharmacogenomic testing (GeneSight) when compared to the unguided group. One industry-sponsored, randomized, double-blind, 10-week prospective study reported a trend for improved outcomes for the GeneSight-guided group; however, the trend did not reach statistical significance. Another industry-sponsored, randomized, double-blind, 12-week prospective study reported a 2.5-fold increase in remission rates in the CNSDose-guided group (P < .0001). One naturalistic, unblinded, industry-sponsored study showed clinical improvement when pharmacogenomics testing guided prescribing; however, this study lacked a control group. A single cost-effectiveness study concluded that single gene testing was not cost-effective. Conversely, a separate study reported that combinatorial pharmacogenomic testing is cost-effective. CONCLUSIONS: A limited number of studies have shown promise for the clinical utility of pharmacogenomic testing; however, cost-effectiveness of pharmacogenomics, as well as demonstration of improved health outcomes, is not yet supported with replicated evidence.

Assessment of abnormal brain structures and networks in major depressive disorder using morphometric and connectome analyses.

BACKGROUND: It is hypothesized that the phenomenology of major depressive disorder (MDD) is subserved by disturbances in the structure and function of brain circuits; however, findings of structural abnormalities using MRI have been inconsistent. Generalized q-sampling imaging (GQI) methodology provides an opportunity to assess the functional integrity of white matter tracts in implicated circuits. METHODS: The study population was comprised of 16 outpatients with MDD (mean age 44.81±2.2 years) and 30 age- and gender-matched healthy controls (mean age 45.03±1.88 years). We excluded participants with any other primary mental disorder, substance use disorder, or any neurological illnesses. We used T1-weighted 3D MRI with voxel-based morphometry (VBM) and vertex-wise shape analysis, and GQI with voxel-based statistical analysis (VBA), graph theoretical analysis (GTA) and network-based statistical (NBS) analysis to evaluate brain structure and connectivity abnormalities in MDD compared to healthy controls correlates with clinical measures of depressive symptom severity, Hamilton Depression Rating Scale 17-item (HAMD) and Hospital Anxiety and Depression Scale (HADS). RESULTS: Using VBM and vertex-wise shape analyses, we found significant volumetric decreases in the hippocampus and amygdala among subjects with MDD (p<0.001). Using GQI, we found decreases in diffusion anisotropy in the superior longitudinal fasciculus and increases in diffusion probability distribution in the frontal lobe among subjects with MDD (p<0.01). In GTA and NBS analyses, we found several disruptions in connectivity among subjects with MDD, particularly in the frontal lobes (p<0.05). In addition, structural alterations were correlated with depressive symptom severity (p<0.01). LIMITATIONS: Small sample size; the cross-sectional design did not allow us to observe treatment effects in the MDD participants. CONCLUSIONS: Our results provide further evidence indicating that MDD may be conceptualized as a brain disorder with abnormal circuit structure and connectivity.