Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder.

BACKGROUND: International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics. AIMS: To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity. METHOD: Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results. RESULTS: Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%. CONCLUSIONS: The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

Multimodal digital assessment of depression with actigraphy and app in Hong Kong Chinese.

There is an emerging potential for digital assessment of depression. In this study, Chinese patients with major depressive disorder (MDD) and controls underwent a week of multimodal measurement including actigraphy and app-based measures (D-MOMO) to record rest-activity, facial expression, voice, and mood states. Seven machine-learning models (Random Forest [RF], Logistic regression [LR], Support vector machine [SVM], K-Nearest Neighbors [KNN], Decision tree [DT], Naive Bayes [NB], and Artificial Neural Networks [ANN]) with leave-one-out cross-validation were applied to detect lifetime diagnosis of MDD and non-remission status. Eighty MDD subjects and 76 age- and sex-matched controls completed the actigraphy, while 61 MDD subjects and 47 controls completed the app-based assessment. MDD subjects had lower mobile time (P = 0.006), later sleep midpoint (P = 0.047) and Acrophase (P = 0.024) than controls. For app measurement, MDD subjects had more frequent brow lowering (P = 0.023), less lip corner pulling (P = 0.007), higher pause variability (P = 0.046), more frequent self-reference (P = 0.024) and negative emotion words (P = 0.002), lower articulation rate (P < 0.001) and happiness level (P < 0.001) than controls. With the fusion of all digital modalities, the predictive performance (F1-score) of ANN for a lifetime diagnosis of MDD was 0.81 and 0.70 for non-remission status when combined with the HADS-D item score, respectively. Multimodal digital measurement is a feasible diagnostic tool for depression in Chinese. A combination of multimodal measurement and machine-learning approach has enhanced the performance of digital markers in phenotyping and diagnosis of MDD.

Assessment of biomarker stability and assay performance parameters for medical diagnosis: a case study of diagnosis of major depressive disorder.

Aim: Assessing the stability profiles and assay performance of 24 biomarker assays in 32 biomarker/body fluid combinations identified as relevant for prediction of major depressive disorder. Materials & methods: Combinations were tested for stability and assay performance with ELISA at different storage and freeze-thaw conditions in pooled samples of 40 patients. Results: Stability and assay performance issues were found in almost all cases except three biomarkers in urine and three in serum. Conclusion: This study shows that, to produce reliable measurement data, assessments of stability and assay performance are essential. In development, other quality assurance parameters might be implemented to increase the level of measurement reliability by increasing assay performance control.

Prevalence of suicidal ideation in German psychotherapy outpatients: A large multicenter assessment.

BACKGROUND: Suicidal ideation is a major concern in clinical practice. Yet, little is known about prevalence rates of suicidal ideation in patients undergoing outpatient psychotherapeutic treatment. Therefore, the aim of the current study is to assess the prevalence of suicidal ideation in a large sample of psychotherapy outpatients in Germany. The data analyzed in this study is taken from the KODAP-project on the coordination of data collection and analysis at German university-based research and training outpatient clinics for psychotherapy. METHODS: A total of N = 10,357 adult outpatients (64.4 % female; age: M(SD) = 35.94 (13.54), range: 18-92 years of age) starting cognitive-behavioral therapy at one of 27 outpatient clinics in Germany were included in the current study. Prevalence of suicidal ideation was assessed with the Suicide Item (Item 9) of the Beck-Depression Inventory II. RESULTS: Suicidal ideation was reported by 36.7 % (n = 3795) of the participants. Borderline Personality Disorder, Posttraumatic Stress Disorder, and recurrent Major Depression were the diagnoses most strongly associated with the presence and severity of suicidal ideation. LIMITATION: Suicide ideation was assessed only with the respective item of the Beck Depression Inventory II. CONCLUSION: Suicidal ideation is very common among adult patients who start psychotherapy in Germany. A well-founded knowledge of risk assessment in suicidal patients and suicide-specific treatment options is therefore highly relevant.

Knowledge and Behavior of Primary Care Physicians Regarding Utilization of Standardized Tools in Screening and Assessment of Anxiety, Depression, and Mood Disorders at a Large Integrated Health System.

INTRODUCTION: Standardized screening, objective evaluation, and management of behavioral health conditions are major challenges in primary care. The Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), and Mood Disorder Questionnaire (MDQ) provide standardized screening and symptom management tools for generalized anxiety disorder (GAD), major depressive disorder (MDD), and Mood Disorders (MD), respectively. This study explores family physicians' knowledge, attitudes, and practices regarding the utilization of GAD-7, PHQ-9, and MDQ in outpatient primary care offices. METHODS: The study method was a cross-sectional electronic and paper survey utilizing a self-administered questionnaire that assessed primary care physicians' demographics, knowledge, attitudes, and practices in rural and urban outpatient clinical settings regarding GAD-7, PHQ-9, and MDQ. Statistical software SAS 9.4 was used for descriptive and Chi-Square statistics. RESULTS: Out of 320 total participants,145 responded (45.3%). Responding family physicians demonstrated a high level of familiarity with the GAD-7 (97.9%), PHQ-9 (97.9%), and MDQ (81.3%) assessment tools. However, the reported utilization rates were relatively lower than knowledge, with 62.7%, 73.1%, and 31.9% extremely likely or likely to utilize the GAD-7, PHQ-9, and MDQ as screening and monitoring tools, respectively. Less than a quarter of the total respondents use the objective score for the future management of GAD, with significantly more residents utilizing the score for GAD-7 compared to attendings (P < .05). There was no statistical significance difference between residents and attendings for the objective evaluation of Major Depressive Disorder (P = .26) and Mood Disorders (P = .05). CONCLUSIONS: Despite being knowledgeable of the utility of GAD-7, PHQ-9, and MDQ, the primary care physicians in a large integrated health system in Central Pennsylvania and Northern Maryland report inconsistent utilization in their practice. Further studies are needed to determine the underlying factors contributing to the suboptimal usage of these screening tools and ways to increase it.

Availability of Mental Telehealth Services in the US.

Importance: Telehealth utilization for mental health care remains much higher than it was before the COVID-19 pandemic; however, availability may vary across facilities, geographic areas, and by patients' demographic characteristics and mental health conditions. Objective: To quantify availability, wait times, and service features of telehealth for major depressive disorder, general anxiety disorder, and schizophrenia throughout the US, as well as facility-, client-, and county-level characteristics associated with telehealth availability. Design, Settings, and Participants: Cross-sectional analysis of a secret shopper survey of mental health treatment facilities (MHTFs) throughout all US states except Hawaii from December 2022 and March 2023. A nationally representative sample of 1938 facilities were contacted; 1404 (72%) responded and were included. Data analysis was performed from March to July 2023. Exposure: Health facility, client, and county characteristics. Main Outcome and Measures: Clinic-reported availability of telehealth services, availability of telehealth services (behavioral treatment, medication management, and diagnostic services), and number of days until first telehealth appointment. Multivariable logistic and linear regression analyses were conducted to assess whether facility-, client-, and county-level characteristics were associated with each outcome. Results: Of the 1221 facilities (87%) accepting new patients, 980 (80%) reported offering telehealth. Of these, 97% (937 facilities) reported availability of counseling services; 77% (726 facilities), medication management; and 69% (626 facilities) diagnostic services. Telehealth availability did not differ by clinical condition. Private for-profit (adjusted odds ratio [aOR], 1.75; 95% CI, 1.05-2.92) and private not-for-profit (aOR, 2.20; 95% CI, 1.42-3.39) facilities were more likely to offer telehealth than public facilities. Facilities located in metropolitan counties (compared with nonmetropolitan counties) were more likely to offer medication management services (aOR, 1.83; 95% CI, 1.11-3.00) but were less likely to offer diagnostic services (aOR, 0.67; 95% CI, 0.47-0.95). Median (range) wait time for first telehealth appointment was 14 (4-75) days. No differences were observed in availability of an appointment based on the perceived race, ethnicity, or sex of the prospective patient. Conclusions and Relevance: The findings of this cross-sectional study indicate that there were no differences in the availability of mental telehealth services based on the prospective patient's clinical condition, perceived race or ethnicity, or sex; however, differences were found at the facility-, county-, and state-level. These findings suggest widespread disparities in who has access to which telehealth services throughout the US.

Clinical high risk state of major depressive episodes: Assessment of prodromal phase, its occurrence, duration and symptom patterns by the instrument the DEpression Early Prediction-INventory (DEEP-IN).

BACKGROUND: To decrease the incidence of major depressive episodes, indicated prevention that targets clinical high-risk individuals with first detectable signs that forecast mental disorder is a highly relevant topic of preventive psychiatry. Still little is known about the prodrome of MDE. The aim of the current study was to identify the occurrence of a clinical high-risk state of depression, its duration and symptom constellation. METHODS: Seventy-three patients with a diagnosed affective disorder in partial remission were assessed with our newly developed semi-structured extensive clinical instrument, the DEpression Early Prediction-INventory (DEEP-IN). Within DEEP-IN the course of prodromal symptoms was explored by using a life-chart method. RESULTS: The significant majority of patients (93.2 %) reported a prodromal phase. The mean duration was 7.9 months (SD = 12.5). Within the group with an identified prodromal phase, psychopathological (95.6 %) as well as somatic symptoms (88.2 %) were reported. Somatic symptoms showed a moderate-to-strong effect of sex with higher prevalence in females than in males (97.6 % vs 73.1 %; V = 0.370). LIMITATIONS: This feasibility study had only a small sample size. CONCLUSIONS: The majority of patients with affective disorders reported a clinical prodromal phase with both psychopathological and somatic symptoms that developed months before the onset of the depressive episode. The development of structured instruments for the assessment of depressive risk states is a promising approach for indicated prevention of depression in the future.

Optimal risk and diagnosis assessment strategies in perinatal depression: A machine learning approach from the life-ON study cohort.

This study aimed to assess the concordance of various psychometric scales in detecting Perinatal Depression (PND) risk and diagnosis. A cohort of 432 women was assessed at 10-15th and 23-25th gestational weeks, 33-40 days and 180-195 days after delivery using the Edinburgh Postnatal Depression Scale (EPDS), Visual Analogue Scale (VAS), Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS), and Mini International Neuropsychiatric Interview (MINI). Spearman's rank correlation coefficient was used to assess agreement across instruments, and multivariable classification models were developed to predict the values of a binary scale using the other scales. Moderate agreement was shown between the EPDS and VAS and between the HDRS and MADRS throughout the perinatal period. However, agreement between the EPDS and HDRS decreased postpartum. A well-performing model for the estimation of current depression risk (EPDS > 9) was obtained with the VAS and MADRS, and a less robust one for the estimation of current major depressive episode (MDE) diagnosis (MINI) with the VAS and HDRS. When the EPDS is not feasible, the VAS may be used for rapid and comprehensive postpartum screening with reliability. However, a thorough structured interview or clinical examination remains necessary to diagnose a MDE.

Development of depression assessment tools using humanoid robots -Can tele-operated robots talk with depressive persons like humans?

BACKGROUND: Depression is a common mental disorder and causes significant social loss. Early intervention for depression is important. Nonetheless, depressed patients tend to conceal their symptoms from others based on shame and stigma, thus hesitate to visit psychiatrists especially during early phase. We hypothesize that application of humanoid robots would be a novel solution. Depressed patients may feel more comfortable talking with such robots than humans. METHODS: We recruited 13 patients with major depressive disorder (MDD) and 27 healthy volunteers as controls. Participants took both tele-operated humanoid robot and human interviews to evaluate severity of depression using the Hamilton Depression Rating Scale (HDRS). In addition, participants completed a self-administered questionnaire asking about their impressions of the robot interview. RESULTS: Confidence interval and t-test analysis have revealed that the HDRS scores are equally reliable between robot and human interviews. No significant differences were observed between the two interviews regarding "nervousness about the interview" and "hesitancy to talk about depressed moods and suicidal ideation." Compared to human interviews, robot interviews yielded significantly lower scores on shame-related factors especially among patients with MDD. LIMITATION: Small sample size, and the evaluator is male only. CONCLUSIONS: This is the first report to show the reliability of tele-operated humanoid robot interviews for assessment of depression. Robot interviews are potentially equally reliable as human interviews. Robot interviews are suggested to be more appropriate in assessing shame-related suppressed emotions and hidden thoughts of depressed patients in clinical practice, which may reduce the stigma associated with depression.

Major depressive disorder with suicidal ideation or behavior in Chinese population: A scoping review of current evidence on disease assessment, burden, treatment and risk factors.

BACKGROUND: Identifying and managing major depressive disorder (MDD) patients with suicidal ideation or behavior (MDSI) is critical for reducing the disease burden. This scoping review aims to map the existing evidence related to MDSI in the Chinese population. METHOD: A scoping review was conducted to summarize the published evidence regarding epidemiology or disease burden, evaluation, diagnosis, management, and prognosis of MDSI. The search strategy imposed restriction on English or Chinese publications between 1 January 2011 and 28 February 2022. RESULTS: Of the 14,005 identified records, 133 met the eligibility criteria and were included for analysis. The included studies were characterized as high heterogeneity in evaluation of suicidal ideation or behavior. Compared with MDD patients without suicidal ideation or behavior, MDSI patients were more likely to suffer from psychological and somatic symptoms, social function impairment, and lower quality of life. Younger age, female gender, longer disease course, and comorbid psychological or physical symptoms were consistently found to be risk factors of suicidal ideation or behavior. Relevant research gaps remain regarding comprehensive evaluation of standard clinical diagnosis, disease burden, social-cultural risk factors, and effectiveness of interventions targeting MDSI. Studies with large sample size, representative population are warranted to provide high-quality evidence. CONCLUSIONS: MDD patients with suicidal ideation or behavior should be prioritized in treatment and resource allocation. Heterogeneity exists in the definition and evaluation of MDSI in different studies. To better inform clinical practice, it is imperative to establish a unified standard for evaluation and diagnosis of suicidal ideation or behavior among MDD population.

The prevalence and economic burden of treatment-resistant depression in Thailand.

BACKGROUND: The objectives of this study were to investigate the proportion of treatment-resistant depression (TRD) among patients with diagnosed major depressive disorder (MDD) and undergoing antidepressant treatment, to estimate the economic cost of MDD, TRD, and non-treatment-resistant depression (non-TRD), and to examine the differences between TRD and non-TRD MDD in a Thai public tertiary hospital. METHODS: This was a combined study between retrospective review of medical records and a cross-sectional survey. The sample size was 500 dyads of antidepressant-treated MDD patients and their unpaid caregivers. MDD patients' medical records, the concept of healthcare resource utilization, the Work Productivity and Activity Impairment Questionnaire: depression and mood & mental state versions (WPAI: D, MM), the Class Impairment Questionnaire (CIQ), and the Family Experiences Interview Schedule (FEIS) were applied as the tools of the study. Pearson Chi's square, Fisher's Exact test, and independent T-test were employed for statistical analysis. RESULTS: The proportion of TRD was 19.6% among antidepressant-treated MDD patients in a Thai tertiary public hospital. The results of the study indicated that several factors showed a statistically significant association with TRD criteria. These factors included younger age of MDD patients, a younger age of onset of MDD, lower body mass index (BMI), a history of suicide attempts and self-harm, as well as frequent smoking behavior. The annualized economic cost of TRD was 276,059.97 baht per person ($7,668.33), which was significantly higher than that of cost of non-TRD (173,487.04 baht or $4,819.08). The aggregated economic costs of MDD were 96.8 million baht annually ($2.69 M) if calculated from 500 MDD patients and unpaid caregivers. This contributed to the economic cost of TRD 27.05 million baht (98 respondents) and the economic cost of non-TRD 69.74 million baht (402 respondents). CONCLUSIONS: The economic burden associated with TRD was significantly higher compared to non-TRD among antidepressant-treated MDD patients. Specifically, both direct medical costs and indirect costs were notably elevated in the TRD group.

The clinical, economic, and patient-centric burden of insomnia symptom severity in adults with major depressive disorder in the United States.

INTRODUCTION: Insomnia is prevalent in adults with major depressive disorder (MDD) and is a key diagnostic criterion of MDD; however, little is understood about the burden of insomnia symptom severity in MDD. We evaluated the relationship between insomnia symptom severity and the clinical, economic, and patient-centric burden among community-dwelling individuals with MDD. METHODS: Respondents with diagnosed depression who reported insomnia symptoms in the past 12 months (N = 4402) were identified from the 2019 United States National Health and Wellness Survey. Multivariable analyses assessed the association of Insomnia Severity Index (ISI) with health-related outcomes while controlling for sociodemographic and health characteristics. Further analyses also controlled for depression severity (9-item Patient Health Questionnaire). RESULTS: Mean ISI score was 14.3 ± 5.6. Higher ISI was associated with greater depression severity (r = .51, p < .001). After adjustments, a one-standard deviation (5.6-point) increase in ISI score was significantly associated with higher depression (rate ratio [RR] = 1.36), anxiety (RR = 1.33) and daytime sleepiness (RR = 1.16) levels, more healthcare provider (RR = 1.13) and emergency room visits (RR = 1.31), hospitalizations (RR = 1.21), work productivity and activity impairment (RRs = 1.27 and 1.23, respectively), and poorer mental and physical health-related quality of life (ß = -3.853 and -1.999, respectively) (p < .001). These findings remained statistically significant when controlling for concurrent depression severity. CONCLUSION: In adults with MDD, greater insomnia symptom severity is associated with worse health-related outcomes, which suggests the importance of addressing insomnia symptoms as a clinical target for treating MDD.

Economic impact of reducing treatment gaps in depression.

BACKGROUND: Major depressive disorder (MDD) is highly prevalent across Europe. While evidence-based treatments exist, many people with MDD have their condition undetected and/or untreated. This study aimed to assess the cost-effectiveness of reducing treatment gaps using a modeling approach. METHODS: A decision-tree model covering a 27-month time horizon was used. This followed a care pathway where MDD could be detected or not, and where different forms of treatment could be provided. Expected costs pertaining to Germany, Hungary, Italy, Portugal, Sweden, and the UK were calculated and quality-adjusted life years (QALYs) were estimated. The incremental costs per QALY of reducing detection and treatment gaps were estimated. RESULTS: The expected costs with a detection gap of 69% and treatment gap of 50% were €1236 in Germany, €476 in Hungary, €1413 in Italy, €938 in Portugal, €2093 in Sweden, and €1496 in the UK. The incremental costs per QALY of reducing the detection gap to 50% ranged from €2429 in Hungary to €10,686 in Sweden. The figures for reducing the treatment gap to 25% ranged from €3146 in Hungary to €13,843 in Sweden. CONCLUSIONS: Reducing detection and treatment gaps, and maintaining current patterns of care, is likely to increase healthcare costs in the short term. However, outcomes are improved, and reducing these gaps to 50 and 25%, respectively, appears to be a cost-effective use of resources.

Assessment of Disruptive Life Events for Individuals Diagnosed With Schizophrenia or Bipolar I Disorder Using Data From a Consumer Credit Reporting Agency.

Importance: There is a dearth of population-level data on major disruptive life events (defined here as arrests by a legal authority, address changes, bankruptcy, lien, and judgment filings) for patients with bipolar I disorder (BPI) or schizophrenia, which has limited studies on mental health and treatment outcomes. Objective: To conduct a population-level study on disruptive life events by using publicly available data on disruptive life events, aggregated by a consumer credit reporting agency in conjunction with electronic health record (EHR) data. Design, Setting, and Participants: This study used EHR data from 2 large, integrated health care systems, Kaiser Permanente Southern California and Henry Ford Health. Cohorts of patients diagnosed from 2007 to 2019 with BPI or schizophrenia were matched 1:1 by age at analysis, age at diagnosis (if applicable), sex, race and ethnicity, and Medicaid status to (1) an active comparison group with diagnoses of major depressive disorder (MDD) and (2) a general health (GH) cohort without diagnoses of BPI, schizophrenia, or MDD. Patients with diagnoses of BPI or schizophrenia and their respective comparison cohorts were matched to public records data aggregated by a consumer credit reporting agency (98% match rate). Analysis took place between November 2020 and December 2022. Main Outcomes and Measures: The differences in the occurrence of disruptive life events among patients with BPI or schizophrenia and their comparison groups. Results: Of 46 167 patients, 30 008 (65%) had BPI (mean [SD] age, 42.6 [14.2] years) and 16 159 (35%) had schizophrenia (mean [SD], 41.4 [15.1] years). The majoriy of patients were White (30 167 [65%]). In addition, 18 500 patients with BPI (62%) and 6552 patients with schizophrenia (41%) were female. Patients with BPI were more likely to change addresses than patients in either comparison cohort (with the incidence ratio being as high as 1.25 [95% CI, 1.23-1.28]) when compared with GH cohort. Patients with BPI were also more likely to experience any of the financial disruptive life events with odds ratio ranging from 1.15 [95% CI, 1.07-1.24] to 1.50 [95% CI, 1.42-1.58]). The largest differences in disruptive life events were seen in arrests of patients with either BPI or schizophrenia compared with GH peers (3.27 [95% CI, 2.84-3.78] and 3.04 [95% CI, 2.57-3.59], respectively). Patients with schizophrenia had fewer address changes and were less likely to experience a financial event than their matched comparison cohorts. Conclusions and Relevance: This study demonstrated that data aggregated by a consumer credit reporting agency can support population-level studies on disruptive life events among patients with BPI or schizophrenia.

Perinatal mental health in low-income urban and rural patients: The importance of screening for comorbidities.

OBJECTIVE: To assess the rates and feasibility of assessing comorbid mental health disorders and referral rates in low-income urban and rural perinatal patients. METHODS: In two urban and one rural clinic serving primarily low-income perinatal patients of color, a computerized adaptive diagnostic tool CAT-MH® was implemented to assess major depressive disorder (MDD), general anxiety disorder (GAD), suicidality (SS), substance use disorder (SUD), and post-traumatic stress disorder (PTSD) at the first obstetric visit and/or 8 weeks postpartum. RESULTS: Of a total of 717 screens, 10.7% (n = 77 unique patients) were positive for one or more disorders (6.1% one, 2.5% two, 2.1% three or more). MDD was the most common disorder (9.6%) and was most commonly comorbid with GAD (33% of MDD cases), SUD (23%), or PTSD (23%). For patients with a positive screen, referral to treatment was 35.1% overall, with higher rates in urban (51.6%) versus rural (23.9%) clinics (p = 0.03). CONCLUSION: Mental health comorbidities are common in low-income urban and rural populations, but referral rates are low. Promoting mental health in these populations requires comprehensive screening and treatment approaches for psychiatric comorbidities and dedication to increase the availability of mental health prevention and treatment options.

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

OBJECTIVE: A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. METHOD: Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA-Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior. RESULTS: We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15-0.97; r range: 0.21-0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments. CONCLUSIONS: Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Personality Assessment Inventory suicidality scales: Suicidal Ideation (SUI), Suicide Potential Index (SPI), and S_Chron in an Afghanistan/Iraq-era active and Veteran military sample.

INTRODUCTION: This study validated Personality Assessment Inventory (PAI) Suicidal Ideation (SUI), Suicide Potential Index (SPI), and S_Chron scales against chronic and acute suicide risk factors and symptom validity measures. METHODS: Afghanistan/Iraq-era active-duty and Veteran participants completed a prospective study on neurocognition (N = 403) that included the PAI. The Beck Depression Inventory-II (specifically item 9) administered at two time points assessed acute and chronic suicide risk; the Beck Scale for Suicide Ideation item 20 identified history of suicide attempts. Major depressive disorder (MDD), posttraumatic stress disorder (PTSD), and traumatic brain injury (TBI) were evaluated using structured interviews and questionnaires. RESULTS: All three PAI suicide scales were significantly related to independent indicators of suicidality, with the largest effect for SUI (AUC 0.837-0.849). All three suicide scales were significantly related to MDD (r = 0.36-0.51), PTSD (r = 0.27-0.60), and TBI (r = 0.11-0.30). The three scales were not related to suicide attempt history for those with invalid PAI protocols. CONCLUSIONS: Although all three suicide scales do show significant relationships to other indicators of risk, SUI showed the highest association and greatest resistance to response bias.

The transdiagnostic use of worry and rumination to avoid negative emotional contrasts following negative events: A momentary assessment study.

The contrast avoidance model (CAM) suggests that individuals with generalized anxiety disorder (GAD) are sensitive to a sharp increase in negative and/or decrease in positive affect. They thus worry to increase negative emotion to avoid negative emotional contrasts (NECs). However, no prior naturalistic study has examined reactivity to negative events, or ongoing sensitivity to NECs, or the application of CAM to rumination. We used ecological momentary assessment to examine effects of worry and rumination on negative and positive emotion before and after negative events and intentional use of repetitive thinking to avoid NECs. Individuals with major depressive disorder (MDD) and/or GAD (N = 36) or without psychopathology (N = 27) received 8 prompts/day for 8 days and rated items on negative events, emotions, and repetitive thoughts. Regardless of group, higher worry/rumination before negative events was associated with less increased anxiety and sadness, and less decreased happiness from before to after the events. Participants with MDD/GAD (vs. controls) reported higher ratings on focusing on the negative to avoid NECs and greater vulnerability to NECs when feeling positive. Results support the transdiagnostic ecological validity for CAM extending to rumination and intentional engagement in repetitive thinking to avoid NECs among individuals with MDD/GAD.

Assessment of patient life engagement in major depressive disorder using items from the Inventory of Depressive Symptomatology Self-Report (IDS-SR).

BACKGROUND: Patient-reported outcomes can measure domains that are personally meaningful, such as life engagement, which reflects motivation, pleasure, and well-being. This study explored whether certain items from the Inventory of Depressive Symptomatology Self-Report (IDS-SR) can capture patient life engagement in major depressive disorder (MDD). METHODS: IDS-SR life engagement items were identified by a) a panel of expert psychiatrists (n = 4), b) patient interviews (n = 20), and c) a principal component analysis (PCA) to explore clustering of items. Psychometric analyses were performed on potential subscales, and a minimal clinically important difference (MCID) was estimated by anchor- and distribution-based methods. IDS-SR data were obtained from three randomized controlled trials of adjunctive brexpiprazole in MDD. RESULTS: Expert psychiatrists selected 10 items by consensus from the IDS-SR that might capture patient life engagement (Cronbach's alpha, 0.82; item-total correlations, 0.36-0.58). Patient interviews identified 13 items as moderately to very relevant to life engagement (Cronbach's alpha, 0.85; item-total correlations, 0.35-0.61). The PCA revealed a cluster that included all 10 items selected by psychiatrists and 11 items identified by patients. Expert psychiatrists intentionally distinguished life engagement and core depressive symptoms, although patient insights and the PCA indicated that these aspects of MDD are strongly linked. The 10-item IDS-SR life engagement subscale had an MCID of 3-5 points. CONCLUSIONS: Different approaches consistently identified a subset of 10 IDS-SR items that can measure life engagement in MDD, which may be suitable to group into an IDS-SR life engagement subscale.

Machine learning-decision tree classifiers in psychiatric assessment: An application to the diagnosis of major depressive disorder.

This work illustrates the advantages of using machine learning classifiers in psychiatric assessment. Machine learning-decision trees (ML-DTs) represent a new approach to scoring and interpreting psychodiagnostic test data that allows for increasing assessment accuracy and efficiency. The approach is outlined in an easy yet detailed way, and its application is illustrated on real psychodiagnostic test data. Specifically, cross-sectional data concerning nonclinical and clinical Japanese populations were taken from a panel registered with an internet survey company. Responses to the Patient Health Questionnaire-9 (PHQ-9) underwent receiver operating characteristic (ROC) curve, DSM algorithm, and ML-DT analyses. The results showed greater diagnostic accuracy for ML-DT (0.71-0.75) compared with the DSM algorithm (0.69) and ROC curves (0.70-0.71). Moreover, ML-DT enabled classifying participants as having or not having a diagnosis of depression using, on average, the information from 2.99 out of 9 items (SD = 1.35). The application showed that ML-DTs can provide information of high clinical value to integrate traditional psychometric methods. The resulting assessments are informative, accurate, and efficient.