Cross-sectional study of psychiatric disorders in patients with chronic musculoskeletal pain and individuals without pain.

BACKGROUND: Musculoskeletal chronic pain is a leading cause of global disability and laboral incapacity. However, there is a lack of population-based studies that investigate the relationship between chronic pain and mental disorders with a control group, particularly among low- and middle-income countries. Chronic pain is a serious public health problem in terms of human suffering, and in terms of socioeconomic implications. Frequent association with different mental disorders increases disability, decreases quality of life, and makes diagnosis and treatment challenging. The present study aimed to evaluate the presence of mental disorders in patients with chronic musculoskeletal pain and compare with a control group without pain. METHODS: We selected 100 patients in a regular follow-up at the Musculoskeletal Pain Outpatient Clinic of the University Hospital and compared them with 100 painless individuals from the control group from June 2016 to June 2018. The instruments used were the Mini International Neuropsychiatric Interview (MINI-PLUS) and a structured questionnaire to collect sociodemographic data. Statistical analysis used t-test, chi-square, Fisher's exact test, Mann-Whitney, Kolmogorov-Smirnov tests, and multiple logistic regression. RESULTS: In the sample evaluated, the majority of patients were women (83%), of brown color (54%), with lower-level education (51%), lower salary range (73%) and high absenteeism rate at work (60,7%). Patients with chronic pain had more psychiatric disorders (88% vs. 48% in the control group; p < 0.001). The most frequent diagnoses were anxiety disorders with panic attacks (44%), generalized anxiety (36%), mixed anxiety and depression disorder (33%), social phobia (30%), agoraphobia (29%), suicide risk (28%), and major depression (27%). CONCLUSION: Positive correlations of mental disorders and chronic musculoskeletal pain have been documented. This suggests that psychiatric components must be taken into account in the management of chronic pain syndromes. The use of Mini Plus as a diagnostic tool for psychiatric disorders can contribute to optimizing the diagnosis and treatment of patients with chronic pain and encourage the creation of policies with strategies and criteria for quick access to Multi-professional Services.

Digital biomarkers in depression: A systematic review and call for standardization and harmonization of feature engineering.

BACKGROUND: General physicians misclassify depression in more than half of the cases. Researchers have explored the feasibility of leveraging passively collected data points, also called digital biomarkers, to provide more granular understanding of depression phenotypes as well as a more objective assessment of disease. METHOD: This paper provides a systematic review following the PRISMA guidelines (Page et al., 2021) to understand which digital biomarkers might be relevant for passive screening of depression. Pubmed and PsycInfo were systematically searched for studies published from 2019 to early 2024, resulting in 161 records assessed for eligibility. Excluded were intervention studies, studies focusing on a different disease or those with a lack of passive data collection. 74 studies remained for a quality assessment, after which 27 studies were included. RESULTS: The review shows that depressed participants' real-life behavior such as reduced communication with others can be tracked by passive data. Machine learning models for the classification of depression have shown accuracies up to 0.98, surpassing the quality of many standardized assessment methods. LIMITATIONS: Inconsistency of outcome reporting of current studies does not allow for drawing statistical conclusions regarding effectiveness of individual included features. The Covid-19 pandemic might have impacted the ongoing studies between 2020 and 2022. CONCLUSION: While digital biomarkers allow real-life tracking of participant's behavior and symptoms, further work is required to align the feature engineering of digital biomarkers. With shown high accuracies of assessments, connecting digital biomarkers with clinical practice can be a promising method of detecting symptoms of depression automatically.

The assessment of transdiagnostic dimensions of emotional disorders: Validation of the Multidimensional Emotional Disorders Inventory (MEDI) in adolescents with subthreshold anxiety and depression.

BACKGROUND: The transdiagnostic approach to psychopathology has emerged as an alternative to traditional taxonomic approaches. The Multidimensional Emotional Disorders Inventory (MEDI) is a specifically designed self-report to measure the transdiagnostic dimensions proposed by Brown and Barlow (2009). This study aims to analyse the psychometric properties of the MEDI scores in adolescents with subthreshold anxiety and depression. METHOD: The sample consisted of a total of 476 students. The mean age was 13.77 years (SD = 1.43) (range 10 to 18 years), 73.9 % were females. Several questionnaires assessing positive affect, negative affect, mental health difficulties, and quality of life were used. RESULTS: The original 9-factor structure of the MEDI was confirmed with good fit indices. Satisfactory levels of internal consistency were observed in most of the MEDI scores using McDonald's Omega, ranging from 0.58 to 0.87. The MEDI dimensions were associated with psychopathology, positive affect, negative affect, and quality of life. LIMITATIONS: Reliance on self-reported data, a cross-sectional design limiting temporal assessment, and a 73.9 % female gender imbalance. CONCLUSION: The MEDI scores showed adequate psychometric properties among adolescents with subclinical emotional symptoms. The results found might have potential clinical implications for conceptualization, assessment, intervention, and prevention of emotional disorders at both clinical and research levels.

Burden of undiagnosed depression among older adults in India: a population based study.

BACKGROUND: The study explored the levels and associated factors of undiagnosed depression among community-dwelling older Indian adults. It also identified the socio-demographic predictors of undiagnosed depression among the study population at national and state levels. METHODS: The study employed data from the Longitudinal Ageing Study in India wave-I, 2017-18. Based on the data on depression from interviewee's self-reporting and measurement on Composite International Diagnostic Interview- Short Form (CIDI-SF) and Centre for Epidemiological Studies- Depression scale (CES-D) scales, we estimated undiagnosed depression among older adults (age 60+). We estimated multivariable binary logistic regressions to examine the socio-demographic and health-related predictors of undiagnosed depression among older adults. FINDINGS: 8% (95% CI: 7.8-8.4) of the total older adults had undiagnosed depression on CIDI-SF scale and 5% (95% CI: 4.8-5.3) on the combined CIDI-SF and CES-D. Undiagnosed depression was higher among those who were widowed, worked in the past and currently not working, scheduled castes, higher educated and the richest. Lack of health insurance coverage, presence of any other physical or mental impairment, family history of Alzheimer's/Parkinson's disease/ psychotic disorder, lower self-rated health and poor life satisfaction were significant predictors of undiagnosed depression on both CIDI-SF and combined scales. CONCLUSION: To improve the health of older adults in India, targeted policy efforts integrating mental health screening, awareness campaigns and decentralization of mental healthcare to primary level is needed. Further research could explore the causal factors behind different levels of undiagnosed depression.

The Swedish version of the Motivation and Pleasure Scale self-report (MAP-SR): psychometric properties in patients with schizophrenia or depression.

PURPOSE: Negative symptoms are commonly regarded as a symptom dimension belonging to schizophrenia spectrum disorders but are also present in depression. The recently developed Clinical Assessment Interview for Negative Symptoms (CAINS) has shown to be reliable and valid. A corresponding self-report questionnaire has also been developed, named the Motivation and Pleasure Scale - Self Report (MAP-SR). The purpose was to evaluate the psychometric properties of the Swedish version of the MAP-SR in patients with either schizophrenia or depression. MATERIALS AND METHODS: The MAP-SR was translated to Swedish. Participants were 33 patients with schizophrenia spectrum disorders and 52 patients with a depressive disorder and they completed the MAP-SR, the CAINS and other measures assessing adjacent psychopathology, functioning and cognition. RESULTS: The internal consistency for the MAP-SR was adequate in both groups (schizophrenia spectrum α = .93, depressive disorder α = .82). Furthermore, the MAP-SR had a large correlation to the motivation and pleasure subscale of the CAINS in patients with schizophrenia disorders (r = -0.75, p < .001), however among patients with depression this correlation was medium-to-large (r = -0.48, p < 0.001). CONCLUSIONS: Findings suggest that the Swedish version of the MAP-SR shows promise as a useful measure of motivation and pleasure, especially in patients with schizophrenia spectrum disorders. Furthermore, results also suggest that the MAP-SR does not assess negative symptoms specifically, but that there is an overlap between depressive and negative symptoms.

[A Continuous Literature Review for Mental Health Surveillance during the Covid-19 Pandemic in Germany - Method, Selected Results and Lessons Learned]. / Kontinuierliches Literaturreview zur Surveillance der psychischen Gesundheit in Deutschland während der COVID-19-Pandemie ­ Methode, ausgewählte Ergebnisse und Lessons Learned.

In order to provide an up-to-date overview on changes in population's mental health during the COVID-19 pandemic, a continuous literature review was conducted. Building on a rapid review, systematic and hand searches were conducted monthly until December 31, 2022. Studies were assessed for observation periods, risk of bias and outcomes. Trends in depressive symptoms in adults were summarized by vote counting. 102 publications were included from 62 studies in the adult population. Studies declined over the course of the pandemic. Overall, 37% of the studies and 56% of the publications can assess trends in the population reliably. Among evidence for changes in depressive symptoms deteriorations predominated at last. The heterogeneity of results published by the end of 2022 limits evidence syntheses. Evidence of deterioration requires further surveillance. A continuous review can indicate evidence gaps at an early stage.

[Intended utilization of health care services in cases of mental illnesses with varying urgency]. / Intendierte Inanspruchnahme von Versorgungsangeboten bei psychischen Erkrankungen mit unterschiedlicher Dringlichkeit.

OBJECTIVE: To investigate variations in intended utilization in cases of an acute psychotic episode, an alcohol related or depressive disorder depending on different case characteristics. METHODS: A telephone survey with case vignettes was conducted (N=1,200). Vignettes varied in terms of urgency of symptoms, daytime, sex of the afflicted person and age/mental disorder. The respondents were asked to indicate whom they would contact first in the described case. RESULTS: Outpatient physicians were named most frequently as the first point of contact (61.1%) while only 6.5% of the respondents named emergency medicine including the medical on call service (8.1% in high urgency cases, i. e. emergencies that did not tolerate any delay). Intended utilization varied by urgency and age/mental illness. CONCLUSION: More Information about the need to seek medical help immediately in cases of mental illnesses with high urgency should be provided.

Action recommendations review in community-based therapy and depression and anxiety outcomes: a machine learning approach.

BACKGROUND: While the positive impact of homework completion on symptom alleviation is well-established, the pivotal role of therapists in reviewing these assignments has been under-investigated. This study examined therapists' practice of assigning and reviewing action recommendations in therapy sessions, and how it correlates with patients' depression and anxiety outcomes. METHODS: We analyzed 2,444 therapy sessions from community-based behavioral health programs. Machine learning models and natural language processing techniques were deployed to discern action recommendations and their subsequent reviews. The extent of the review was quantified by measuring the proportion of session dialogues reviewing action recommendations, a metric we refer to as "review percentage". Using Generalized Estimating Equations modeling, we evaluated the correlation between this metric and changes in clients' depression and anxiety scores. RESULTS: Our models achieved 76% precision in capturing action recommendations and 71.1% in reviewing them. Using these models, we found that therapists typically provided clients with one to eight action recommendations per session to engage in outside therapy. However, only half of the sessions included a review of previously assigned action recommendations. We identified a significant interaction between the initial depression score and the review percentage (p = 0.045). When adjusting for this relationship, the review percentage was positively and significantly associated with a reduction in depression score (p = 0.032). This suggests that more frequent review of action recommendations in therapy relates to greater improvement in depression symptoms. Further analyses highlighted this association for mild depression (p = 0.024), but not for anxiety or moderate to severe depression. CONCLUSIONS: An observed positive association exists between therapists' review of previous sessions' action recommendations and improved treatment outcomes among clients with mild depression, highlighting the possible advantages of consistently revisiting therapeutic homework in real-world therapy settings. Results underscore the importance of developing effective strategies to help therapists maintain continuity between therapy sessions, potentially enhancing the impact of therapy.

The relationship between the Hopkins symptom checklist-10 and diagnoses of anxiety and depression among inpatients with substance use disorders.

INTRODUCTION: The Hopkins Symptom Checklist-10 (HSCL-10) is a self-report inventory of anxiety and depression symptoms that may assist clinicians in screening for clinical conditions among patients with substance use disorder (SUD). We examined the HSCL-10 as a screening tool for anxiety and depressive disorders within a general population of SUD inpatients. METHODS: We used data from a cohort study of 611 SUD inpatients. Receiver operating characteristic (ROC) analyses were conducted, with and without covariates, to evaluate the potential of the HSCL-10 as a screening tool. This was explored using any anxiety disorder, especially posttraumatic stress disorder (PTSD), and any mood disorder, especially major depressive disorders, as the outcome criteria. Candidate covariates included gender, age, education, polydrug use and treatment center.Results: The HSCL-10 had a moderate ability to identify caseness (i.e. having or not having a clinical diagnosis) according to each outcome criterion, with the area under the ROC curve (AUC) varying from 0.64 to 0.66. Adding relevant covariates markedly enhanced the instrument's ability to identify those who met the criteria for any anxiety disorder (AUC = 0.77), especially PTSD (AUC = 0.82). CONCLUSION: In a real-world clinical setting, the HSCL-10 has fair-to-good clinical utility for identifying SUD inpatients who have comorbid clinical symptoms of anxiety disorders or PTSD, when combined with common background variables. The HSCL-10, a brief self-report screening tool, may serve as an efficient proxy for comprehensive interviews used in research and for clinical anxiety symptom screening among patients with SUD.

Adipocytokines levels as potential biomarkers for discriminating patients with a diagnosis of depressive disorder from healthy controls.

BACKGROUND: Depressive disorder is a complex mental health condition in which the etiopathogenesis involves several factors. Suitable biomarkers for the development of depression have not yet been established. Alterations in cytokines are assumed to be involved in the pathophysiology of depressive disorder. Adipokines (also known as adipocytokines) are important factors that not only regulate the energy balance but also regulate the inflammatory and immune responses. This study investigated the serum levels of adiponectin, leptin, resistin, chemerin, and fetuin A and the possible role of these adipokines in depressive disorder. METHODS: We recruited a total of 73 patients diagnosed with recurrent depressive disorder (rDD) and 54 age- and sex-matched healthy controls (HCs). Serum adipocytokines were determined using ELISA kits (R&D, USA). The serum levels of the investigated molecules between depressive patients and HCs were compared, and diagnostic values were evaluated using the receiver operating characteristic (ROC) curve method for discriminating depressive patients from HCs. Correlations between the molecules and clinical variables were also evaluated. RESULTS: Patients with rDD had lower levels of serum adiponectin and chemerin and higher levels of serum leptin, resistin and fetuin A (p < 0.05) vs. controls. Moreover, ROC curve analysis showed that the area under the curve (AUC) values of above set of adipocytkines were >0.7, with a sensitivity and specificity over 80% in discriminating patients with rDD from HCs. CONCLUSIONS: These results suggest that circulating adipocytokies may hold promise as biomarkers for the diagnosis of rDD.

Do depressive and anxiety symptoms influence the construct validity of Multiple Sclerosis Walking Scale-12 scores?

PURPOSE/OBJECTIVE: Walking dysfunction, depression, and anxiety are prevalent, burdensome, and interrelated outcomes in persons with multiple sclerosis (MS). The 12-item Multiple Sclerosis Walking Scale (MSWS-12) is a common patient-reported outcome (PRO) of walking dysfunction in research and practice involving MS, but the construct validity of its scores might be influenced by symptoms of depression and anxiety. This study examined if symptoms of depression and anxiety influenced the construct validity of MSWS-12 scores. RESEARCH METHOD/DESIGN: The sample included 189 participants with MS who completed the MSWS-12, Hospital Anxiety and Depression Scale (HADS-Depression subscale [HADS-D] and HADS-Anxiety subscale [HADS-A]), 6-minute walk (6MW), and timed 25-foot walk (T25FW). We conducted bivariate correlation analysis to examine the associations between MSWS-12 scores and both the 6MW and T25FW, while controlling for HADS-D and HADS-A scores. RESULTS: MSWS-12 scores were significantly correlated with the 6MW (r = -.752), T25FW (r = .694), HADS-D (r = .405), and HADS-A (r = .235). The correlations between MSWS-12 and 6MW (pr = -.725) and T25FW (pr = .685) did not change when controlling for HADS-D and HADS-A scores. The correlations between MSWS-12 and 6MW (r = -.708 and r = -.726) and T25FW (r = .687 and r = .748) were strong in subsamples with elevated HADS-D and HADS-A scores. CONCLUSIONS/IMPLICATIONS: Our results strengthen the validity evidence for MSWS-12 scores as a PRO of walking dysfunction in MS, including among those with symptoms of depression and anxiety. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Response inhibition related neural oscillatory patterns show reliable early identification of bipolar from unipolar depression in a Go/No-Go task.

BACKGROUND: Response inhibition is a key neurocognitive factor contributing to impulsivity in mood disorders. Here, we explored the common and differential alterations of neural circuits associated with response inhibition in bipolar disorder (BD) and unipolar disorder (UD) and whether the oscillatory signatures can be used as early biomarkers in BD. METHODS: 39 patients with BD, 36 patients with UD, 29 patients initially diagnosed with UD who later underwent diagnostic conversion to BD, and 36 healthy controls performed a Go/No-Go task during MEG scanning. We carried out time-frequency and connectivity analysis on MEG data. Further, we performed machine learning using oscillatory features as input to identify bipolar from unipolar depression at the early clinical stage. RESULTS: Compared to healthy controls, patients had reduced rIFG-to-pre-SMA connectivity and delayed activity of rIFG. Among patients, lower beta power and higher peak frequency were observed in BD patients than in UD patients. These changes enabled accurate classification between BD and UD with an accuracy of approximately 80 %. CONCLUSIONS: The inefficiency of the prefrontal control network is a shared mechanism in mood disorders, while the abnormal activity of rIFG is more specific to BD. Neuronal responses during response inhibition could serve as a diagnostic biomarker for BD in early stage.

Association of Rosacea with Depressive and Anxiety Symptoms: A General Population Study.

BACKGROUND: The association between rosacea and psychiatric comorbidity has been reported previously. However, there is a lack of general population studies about this subject area. OBJECTIVES: The aim of this study was to the association between rosacea with depressive and anxiety symptoms at the population level. METHODS: A clinical whole-body examination was performed by dermatologists for 1,932 subjects belonging to the Northern Finland Birth Cohort 1966 Study during the 46-year follow-up survey. The presence of depressive and anxiety symptoms was gathered by using validated Hopkins Symptom Checklist-25 (HSCL-25) included in the self-administered questionnaires. Binary logistic regression analysis was used to identify associations between rosacea and psychological symptoms. RESULTS: Rosacea was found in dermatological evaluation in 15.1% of the study subjects (n = 292). In logistic regression analyses, after adjusting for confounding factors, those with rosacea had 1.6-fold (OR 1.55, 95% CI: 1.02-2.32) risk for psychiatric symptoms according to HSCL-25 when compared with controls. In separate analyses of the HSCL-25 depression subscale, the risk was increased, especially for depressive symptoms (OR 1.56, 95% CI: 1.10-2.18). CONCLUSIONS: Patients with rosacea seem to have increased risk for depressive and anxiety symptoms in general population. Physicians treating patients with rosacea should pay more attention to the psychosocial health of patients.

Depressive Disorder Remote Detection through Touchscreen Typing Behaviour.

Depressive Disorder (DD) is a leading cause of disability worldwide. Passive tools for screening the symptoms of DD are essential in monitoring and limiting the spread of the disease. From an alternative perspective, individuals' kinetic expression and activities, including smartphone interaction, reflect their mental status. Such widely available data in everyday life form a promising source of information on keystroke dynamics and their characteristics. This work explores how keystroke dynamics derived from touchscreen typing patterns have revealed the diagnosis of mental disorders, particularly depressive disorders. Different deep learning approaches were established to detect patients' depressive tendencies denoted by the self-reported Patient Health Questionnaire-9 (PHQ-9) score based on keystroke digital biomarkers. In particular, Convolutional Neural Networks (CNN), Long-Short-Term-Memory (LSTM), and CNN-LSTM models were examined and compared. The keystroke sequences are captured unobtrusively during routine interaction with touchscreen smartphones in a non-clinical setting. This study used 23,264 typing sessions provided by 10 DD patients and 14 healthy controls (HC). The proposed approach was investigated under two keystroke feature combinations and validated utilizing a leave-one-subject-out (LOSO) cross-validation scheme. The best-performing LSTM-with-hold-time (LSTM-HT) model achieved an Area Under Curve (AUC) of 0.86 with the correlated probabilities for subjects' status [95% confidence interval (CI):0.66-1.00, sensitivity/specificity (SE/SP) of 0.8/0.93].Clinical relevance- The findings of this research have the potential to contribute to improving digital tools for objectively screening mental disorders in the wild. Moreover, they would potentially provide the users and their attending psychiatrists with information regarding the evolution of their mental health.

[Depressive disorders in adolescents in outpatient psychiatric practice]. / Depressivnye rasstroistva u podrostkov v ambulatornoi psikhiatricheskoi praktike.

OBJECTIVE: To clarify the clinical features of depressive states in adolescent boys and girls (taking into account age and sex) seeking help from primary care specialists in outpatient psychiatric care. MATERIAL AND METHODS: The study included 158 patients (89 boys and 69 girls), aged 15-17, with depressive pathology of various genesis, observed in the adolescent office of one of the Moscow psychoneurological dispensary in 2015-2020. The main research methods were clinical-psychopathological, clinical-follow-up, statistical. RESULTS: An analysis of the data demonstrated that adolescent depression can be observed within different diagnostic categories. Most often they were noted in patients with affective disorders (43%, n=68), emerging personality disorders (29%, n=46), schizotypal disorder (13%, n=21). The nosological affiliation of depression and its severity were associated with sex. In young men, depressive states were more often detected in the structure of emerging personality disorder (59.6%) and schizotypal disorder (15.7%), depressive states within affective disorders were detected in 22.5% of cases. In girls, most of the depressive episodes (69.6%) developed in the structure of affective disorders, less often in personality disorders (20.3%), and schizotypal disorder (10.1%). Depressive episodes in girls were predominantly of moderate severity, in boys the most common were mild depressions. CONCLUSION: Adolescent depressions are a nosologically heterogeneous group of affective disorders, differing in clinical phenomenology and prognosis. They are noted within the pathology of the affective spectrum, affective phases and psychogenic reactions acting in the dynamics of emerging personality disorders, within the framework of psychopathological diathesis, schizotypal disorder. The influence of sex on the development of depressive disorders is determined by the nosological framework of the condition.

[Recent approaches to the diagnosis and therapy of monopolar depression]. / Sovremennye podkhody k diagnostike i terapii monopolyarnoi depressii.

Unipolar depression is one of the most significant biomedical problems, which is associated with its high prevalence, a pronounced negative impact on the level of work capacity of the population, worsening of the course of most somatic and neurological diseases, and suicide risk. This review presents current data on approaches to the diagnosis of monopolar depression, both classical (clinical and psychometric) and using modern technologies. The existing approaches to the therapy of monopolar depression - psychopharmacologic, psychotherapeutic, and non-drug biological approaches - are discussed. The advantages of the selective serotonin reuptake inhibitor sertraline are presented, and its use as a first-line drug is justified.