A narrative review of the Beck Depression Inventory (BDI) and implications for its use in an alcohol-dependent population

Correlation between physical exercise levels, depressive symptoms, and sleep quality in college students: Evidence from electroencephalography

BACKGROUND

In recent years, depression has increasingly become a major global public health issue. Among its common physical symptoms, sleep disturbances are prevalent in individuals with depression and are considered a risk factor for the progression of the disorder. Poor sleep quality may be a significant contributor to depression among college students. However, the EEG indicators that are commonly associated with depressive symptoms and sleep quality, as well as the effects of physical exercise on these EEG indicators, remain unclear.

PURPOSE

This study aims to explore the relationship between physical activity levels, depressive symptoms, and sleep quality among college students, based on resting-state electroencephalography (EEG) data in a cross-sectional study.

METHODS

A total of 342 college students were recruited to assess physical activity levels, depressive symptoms, sleep quality, and EEG data. Pearson correlation coefficients were used to evaluate the relationships among these variables, and the PROCESS macro (Model 4) for SPSS was applied to examine the mediating role of sleep quality in the relationship between physical activity levels and depressive symptoms, with mediation effects tested using the bootstrap method.

RESULTS

A significant difference was observed in the Pittsburgh Sleep Quality Index (PSQI) total scores between students with and without depressive symptoms (T = 9.746, P < 0.001). Students with depressive symptoms showed poorer sleep quality across various dimensions, including sleep duration, sleep onset latency, sleep disturbances, and daytime dysfunction. Depression symptom were positively correlated with Sleep Quality (r = 0.547, P < 0.001), indicating that higher depression symptoms are associated with poorer sleep quality. Correlations between depressive symptoms and EEG power values revealed significant associations with theta and beta2 frequencies in multiple brain regions (P < 0.05). Physical exercise showed a significant negative correlation with Sleep Quality scores (r = -0.158, P = 0.004), and with sleep duration (r = -0.141, P = 0.011) and daytime dysfunction (r = -0.142, P = 0.010). Additionally, physical exercise was negatively correlated with theta band power at F8 (P < 0.05). Mediation analysis demonstrated that physical exercise has a direct effect on depressive symptoms (β = -0.123, 95 % CI = -0.287 to -0.069) and an indirect effect through improved sleep quality (β = -0.074, 95 % CI = -0.089 to -0.016), accounting for 60.16 % and 40.65 % of the total effect, respectively.

CONCLUSION

These findings provide a theoretical basis for developing precise exercise intervention programs to improve depressive symptoms and sleep quality among college students. The results indicate that moderate physical activity can help alleviate depressive symptoms and improve sleep quality, thereby enhancing the overall health of college students.

Prazosin and cyproheptadine in combination in the treatment of alcohol use disorder: A randomized, double-blind, placebo-controlled trial

BACKGROUND AND AIMS

Pre-clinical studies suggest that the simultaneous blockade of the α1b and 5HT2A receptors may be effective in reducing alcohol consumption. This study aimed to assess the efficacy and safety of prazosin (α1b blocker) and cyproheptadine (5HT2A blocker) combination in decreasing total alcohol consumption (TAC) in alcohol use disorder (AUD).

DESIGN, SETTING AND PARTICIPANTS

This was a double-blind, parallel group, placebo-controlled, Phase 2, randomized clinical trial conducted in 32 addiction treatment centres in France. A total of 108 men and 46 women with severe AUD took part.

INTERVENTION

Participants were randomly assigned to one of the following 3-month treatments: (1) low-dose group (LDG) receiving 8 mg cyproheptadine and 5 mg prazosin extended-release (ER) formulation daily; (2) high-dose group (HDG) receiving 12 mg cyproheptadine and 10 mg prazosin ER daily; and (3) placebo group (PG) receiving placebo of cyproheptadine and prazosin ER. A total of 154 patients were randomized: 54 in the PG, 54 in the LDG and 46 in the HDG.

MEASUREMENTS

The primary outcome was TAC change from baseline to month 3.

FINDINGS

A significant main treatment effect in the change in TAC was found in the intent-to-treat population (P = 0.039). The HDG and LDG showed a benefit in the change in TAC from baseline to month 3 compared with PG: -23.6 g/day, P = 0.016, Cohen's d = -0.44; -18.4 g/day, P = 0.048 (Bonferroni correction P < 0.025), Cohen's d = -0.36. In a subgroup of very high-risk drinking-level participants (> 100 g/day of pure alcohol for men and > 60 g/day for women), the difference between the HDG and the PG in the primary outcome was -29.8 g/day (P = 0.031, Cohen's d = -0.51). The high and low doses were well-tolerated with a similar safety profile.

CONCLUSIONS

A randomized controlled trial of treatment of severe alcohol use disorder with a cyproheptadine-prazosin combination for 3 months reduced drinking by more than 23 g per day compared with placebo. A higher dose combination was associated with a larger magnitude of drinking reduction than a lower dose combination while showing similar safety profile.

Automatic diagnosis of depression based on attention mechanism and feature pyramid model

Currently, most diagnoses of depression are evaluated by medical professionals, with the results of these evaluations influenced by the subjective judgment of physicians. Physiological studies have shown that depressed patients display facial movements, head posture, and gaze direction disorders. To accurately diagnose the degree of depression of patients, this paper proposes a comprehensive framework, Cross-Channel Attentional Depression Detection Network, which can automatically diagnose the degree of depression of patients by inputting information from the facial images of depressed patients. Specifically, the comprehensive framework is composed of three main modules: (1) Face key point detection and cropping for video images based on Multi-Task Convolutional Neural Network. (2) The improved Feature Pyramid Networks model can fuse shallow features and deep features in video images and reduce the loss of miniscule features. (3) A proposed Cross-Channel Attention Convolutional Neural Network can enhance the interaction between tensor channel layers. Compared to other methods for automatic depression identification, a superior method was obtained by conducting extensive experiments on the depression dataset AVEC 2014, where the Root Mean Square Error and the Mean Absolute Error were 8.65 and 6.66, respectively.

Bariatric surgery patients in AUD treatment in Norway-an exploratory cross-sectional study

AIMS

Patients who have undergone some forms of bariatric surgery have increased risk of developing alcohol use disorder (AUD). In the present observational study, we compared patients with AUD who themselves reported to having undergone bariatric surgery with other patients in treatment for AUD.

MATERIALS

One-hundred-and-six consecutively enrolled patients in residential treatment for AUD were asked if they had undergone bariatric surgery. Sociodemographics, mental health-related, and alcohol use-related parameters were compared between those who had and those who had not undergone bariatric surgery.

RESULTS

Of the 106 patients with AUD, seven (6.6%; 95% confidence interval, 2.7%-13.1%) had undergone bariatric surgery. Six of seven patients had undergone such surgery were women (P < .001). The patients with AUD who had undergone bariatric surgery were similar to other patients with AUD on most other parameters, the exception being a larger number of alcohol units ingested to feel an effect of alcohol (adjusted odds ratio 7.1; 95% confidence interval 2.0-12.2; P = .007).

CONCLUSION

The high number of patients with AUD that reported having undergone bariatric surgery emphasizes the risks following such a procedure. The overrepresentation of women may reflect than more women undergo such procedures. The unexpected finding that patients with AUD having undergone bariatric surgery seemed to need more alcohol to feel intoxicated warrants further research.

Neural correlates of risk taking in patients with obsessive-compulsive disorder during risky decision-making

BACKGROUND

The risk preference during decision-making and the neural substrates involved in patients with obsessive-compulsive disorder (OCD) remained unclear. The current study was designed to evaluate the risk-taking behaviors during decision-making and neural correlates in patients with OCD, thereby providing a deeper insight into their impaired decision-making function.

METHODS

Fifty-one patients with OCD and 50 healthy controls (HCs) were included in this study. All subjects underwent functional magnetic resonance imaging (fMRI) scans while completing the Balloon Analog Risk Task (BART). The behavior indicator and cognitive model parameter in BART, as well as the neural correlates of risk-taking behaviors were analyzed.

RESULTS

Compared to HCs, the OCD group performed a significantly higher level of risk-averse behaviors, and the cognitive model parameter revealed that patients with OCD tend to decrease their risk level after receiving negative feedbacks during BART. The fMRI results based on prespecified brain regions showed that the OCD group exhibited significantly decreased activation modulated by risk levels both in the left and right insula.

LIMITATIONS

The effect of medication in this study could not be completely ruled out, and it is difficult to temporally separate different states of decision-making in the BART.

CONCLUSIONS

Individuals with OCD exhibited a higher level of risk aversion during decision-making process, and the dysfunction of the insula may be the neural basis of the increased risk aversion in OCD. These findings provide further insights into the mechanism of risk aversion and impaired decision-making function in individuals with OCD.

Levels of IL-6 are Associated with Lifetime Attempted Suicide in Alcohol Use Disorder Patients

Background

Patients with alcohol use disorder (AUD) have an increased risk of suicide. Neuroimmunological measures, such as cytokines, are shown to deviate in people with attempted suicide. Few studies have investigated this among AUD patients.

Patients and Methods

One-hundred and fourteen patients undergoing residential treatment for AUD were interviewed on lifetime suicide attempts (SA) along with several other background variables and clinical characteristics. Serum blood samples were drawn for analysis of cytokines.

Results

Thirty-one patients (27%) reported at least one SA. These patients had more symptoms of current affective disorders and more severe dependence. In bivariate analysis only IL-6 and IL-10 appeared to be associated with lifetime SA but without reaching statistical significance. In multivariate linear regression, adjusting for sex, nicotine use, somatic illness, and the use of anti-inflammatory drugs, IL-6 was associated to SA (p = 0.033).

Conclusion

The cytokine IL-6 has repeatedly been found to be associated with suicidality. The present study concurs with this role of IL-6 in a naturalistic observational study of AUD patients.

A facial depression recognition method based on hybrid multi-head cross attention network

Introduction

Deep-learn methods based on convolutional neural networks (CNNs) have demonstrated impressive performance in depression analysis. Nevertheless, some critical challenges need to be resolved in these methods: (1) It is still difficult for CNNs to learn long-range inductive biases in the low-level feature extraction of different facial regions because of the spatial locality. (2) It is difficult for a model with only a single attention head to concentrate on various parts of the face simultaneously, leading to less sensitivity to other important facial regions associated with depression. In the case of facial depression recognition, many of the clues come from a few areas of the face simultaneously, e.g., the mouth and eyes.

Methods

To address these issues, we present an end-to-end integrated framework called Hybrid Multi-head Cross Attention Network (HMHN), which includes two stages. The first stage consists of the Grid-Wise Attention block (GWA) and Deep Feature Fusion block (DFF) for the low-level visual depression feature learning. In the second stage, we obtain the global representation by encoding high-order interactions among local features with Multi-head Cross Attention block (MAB) and Attention Fusion block (AFB).

Results

We experimented on AVEC2013 and AVEC2014 depression datasets. The results of AVEC 2013 (RMSE = 7.38, MAE = 6.05) and AVEC 2014 (RMSE = 7.60, MAE = 6.01) demonstrated the efficacy of our method and outperformed most of the state-of-the-art video-based depression recognition approaches.

Discussion

We proposed a deep learning hybrid model for depression recognition by capturing the higher-order interactions between the depression features of multiple facial regions, which can effectively reduce the error in depression recognition and gives great potential for clinical experiments.

Longitudinal determinants of insomnia among patients with alcohol use disorder

Insomnia is common among patients with AUD and can impair quality of life and cognitive functioning, as well as cause psycho-social problems and increased risk of relapse. Nonetheless, determinants of insomnia in patients with AUD have scarcely been studied. We aimed to examine prevalence and development of self-perceived insomnia among inpatients in treatment for AUD, and to examine factors in this group known to be associated with sleep disturbance in the general population. We examined self-reported information about sleep from 94 AUD inpatients in long-term treatment (up to 9 months) using a questionnaire identifying probable insomnia. Potential predictors identified in bivariate tests were used in binomial logistic regressions to examine the effect on sleep at baseline and at 6-week follow-up. Longitudinal multilevel analyses were used to examine factors affecting development of sleep quality during the treatment stay. At baseline, 54% of the patients reported sleep problems indicating insomnia. This was reduced to 35% at 6-week follow-up. In a cross-sectional analysis of sleep at baseline, we found that being male (OR 0.18, p = 0.042) and engaging in physical activity (OR 0.09, p < 0.001) were negatively associated with insomnia, while a high level of depressive symptoms (OR 1.10, p = 0.010) was positively associated after adjustment for age, history of trauma, and severity of dependence. Multilevel analyses of data over a 6-month period showed time interactions with physical activity, such that sleep improvement was greater in patients who initially had a low level of physical activity. This longitudinal study corroborates findings of high prevalence of insomnia among AUD patients and identifies factors in this group associated with insomnia, such as sex, depression, and physical activity. Future longitudinal studies are needed to examine the causal directions between sleep, depression, and physical activity and how these might be targeted in clinical settings.

Emotion detection for supporting depression screening

Depression is the most prevalent mental disorder in the world. One of the most adopted tools for depression screening is the Beck Depression Inventory-II (BDI-II) questionnaire. Patients may minimize or exaggerate their answers. Thus, to further examine the patient's mood while filling in the questionnaire, we propose a mobile application that captures the BDI-II patient's responses together with their images and speech. Deep learning techniques such as Convolutional Neural Networks analyze the patient's audio and image data. The application displays the correlation between the patient's emotional scores and DBI-II scores to the clinician at the end of the questionnaire, indicating the relationship between the patient's emotional state and the depression screening score. We conducted a preliminary evaluation involving clinicians and patients to assess (i) the acceptability of proposed application for use in clinics and (ii) the patient user experience. The participants were eight clinicians who tried the tool with 21 of their patients. The results seem to confirm the acceptability of the app in clinical practice.

History of Delirium Tremens in AUD Patients in Treatment: Relationship to AUD Severity and Other Factors

Introduction

Delirium tremens (DT) occurs after stopping prolonged, high alcohol intake and may be life-threatening if untreated. We need to know about clinical correlates of DT in order to provide the best clinical care.

Methods

At admission to inpatient treatment a cohort of 114 alcohol use disorder (AUD) patients were interviewed and examined concerning psychiatric diagnosis and symptoms, trauma experiences and alcohol related measures and if they had experienced DT.

Results

Twenty-four percent of the patients reported a life-time experience of DT. These patients were predominantly males and had lower educational level. More of the patients in the DT than the non-DT group reported at least one suicide attempt, were diagnosed with PTSD, and dropped out of treatment. Also, having parents with alcohol problems was more common among these patients, and they reported a longer duration of problematic drinking and a higher number of drinks needed to feel an effect of drinking. In the multivariable adjusted analysis only a diagnosis of PTSD (OR=5.71; 95% confidence interval (CI): 1.34–24.31) and duration of problematic drinking with a 6% increase in risk for every year (OR=1.06; 95% CI: 1.01–1.11) remained significant risk factors for having DT experience.

Discussion and conclusion

Having experienced DT was more prevalent in the current investigation than in earlier studies. Patients that had experienced DT seemed to have more serious AUD, especially signified by a longer duration of drinking. These patients seemed to have many clinical disadvantages including more drop-out and higher suicide rate. PTSD could be a risk factor for DT but may also follow the DT experience.

The Therapeutic Effect of Exogenous Melatonin on Depressive Symptoms: A Systematic Review and Meta-Analysis

Background

Depression-related mortality and morbidity pose growing public health burdens worldwide. Although the therapeutic effect of exogenous melatonin on depression has been investigated, findings remain inconsistent. We conducted this systematic review and meta-analysis to clarify the effectiveness of melatonin in the treatment of depression, including primary and secondary depression symptoms.

Methods

We searched the online databases of PubMed, EMBASE, and the Cochrane Library for original studies published up to May 2021. We used STATA 14.0 software to synthesize the results of included studies. To evaluate the effectiveness of melatonin, we calculated the standardized mean differences (SMDs) and 95% confidence intervals (CIs) of depression scores between the melatonin and placebo groups.

Results

Our literature search returned 754 publications, among which 19 studies with 1,178 patients (715 women, 463 men; mean age: 56.77 years) met inclusion criteria. Melatonin dosages ranged from 2 to 25 mg per day; treatment durations were between 10 days and 3.5 years. Our synthesized results showed that melatonin was not found significantly beneficial for alleviating depressive symptoms (SMD = -0.17, 95% CI = [-0.38, 0.05]). Subgroup analysis demonstrated that the decrease in depression scores measured with the Beck Depression Inventory (BDI) was significant (SMD = -0.52, 95% CI = [-0.73, -0.31]).

Conclusions

There is very limited evidence for effects of melatonin on depression.

YES-10 Improves Stress, Tension, and Fatigue by Reducing Cortisol and IL-6 Levels

The extract of Clematis mandshurica Rupr. (CMR) inhibits the production of proinflammatory mediators from lipopolysaccharide-stimulated peritoneal macrophages and concanavalin A-stimulated splenocytes. Erigeron annuus Pers. (EAP) extract suppresses the production of reactive oxygen species (ROS) from preadipocytes. Furthermore, the mixture of the leaf extracts of CMR and EAP, YES-10^®, protected against nerve injuries induced by ischemia/reperfusion, suggesting a ROS-scavenging action. These observations show the anti-inflammatory action of YES-10. Inflammatory cytokines can cause alterations in mental function, including depression, by influencing the neurotransmitter system. Thus, it was hypothesized that YES-10 could improve mental health, such as depression, anxiety, and sense of well-being. Seventy-two subjects were recruited and randomly divided into YES-10 or placebo groups (n = 36 per group). Each group was daily administered two capsules orally, containing 200 mg of YES-10 or placebo, for 4 weeks in a double-blinded manner and tested for levels of depression, anxiety, well-being, and mental fitness using the Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Psychosocial Well-being Index (PWI), and Mental Fitness Scale (MFS). In addition, the levels of cortisol (a stress hormone), interleukin-6 (IL-6) (an inflammatory cytokine), and 8-hydroxydeoxyguanosine (8-OHdG; a marker of oxidative stress) in the serum were measured. The BDI, BAI, PWI, and MFS scores decreased significantly, and the serum levels of cortisol, IL-6, and 8-OHdG were lowered significantly (P < .05), suggesting that YES-10 has the ability to improve mental health by relieving stress and by decreasing inflammation and oxidative stress.

Screening for depression in patients in treatment for alcohol use disorder using the Beck Depression Inventory-II and the Hopkins Symptom Checklist-10

Alcohol use disorder (AUD) and major depressive disorder (MDD) are prevalent disorders that often co-occur. The aim of the study was to investigate how the Beck Depression Inventory (BDI-II) and Hopkins Symptom Checklist (HSCL-10) perform as screening instruments for MDD in AUD patients in treatment. The study included 127 mainly AUD inpatients currently in treatment at rehabilitation clinics in Norway. Demographic and clinical variables were examined using questionnaires and clinical interviews. The factor structures of the BDI-II and HCSL-10 were examined, as well as internal consistency and receiver operating characteristic (ROC) curve analyses. The Mini International Neuropsychiatric Interview (M.I.N.I.) was used as standard for diagnosing MDD. In total, 14% of the participants were diagnosed with MDD. BDI-II factor analysis retrieved three factors; cognition, somatic complaints and affect, and factor analysis for the HSCL-10 retrieved two factors; depression and anxiety. The optimal cut-off for the BDI-II was 24.5 with sensitivity of 80% and specificity of 78%. For HSCL-10 the optimal cut-off was 2.35, giving sensitivity of 80% and specificity of 69%. Both the BDI-II and HSCL-10 may be clinically useful screening instruments for MDD in AUD patients. There was a tendency that the affect factor of the BDI-II and the depression factor of the HSCL-10 were slightly more suitable for identifying MDD than the other factors. Optimal cut-offs for both the BDI-II and the HSCL-10 in this patient group were higher than cut-offs commonly used in the general population.

Deep Neural Networks for Depression Recognition Based on 2D and 3D Facial Expressions Under Emotional Stimulus Tasks

The proportion of individuals with depression has rapidly increased along with the growth of the global population. Depression has been the currently most prevalent mental health disorder. An effective depression recognition system is especially crucial for the early detection of potential depression risk. A depression-related dataset is also critical while evaluating the system for depression or potential depression risk detection. Due to the sensitive nature of clinical data, availability and scale of such datasets are scarce. To our knowledge, there are few extensively practical depression datasets for the Chinese population. In this study, we first create a large-scale dataset by asking subjects to perform five mood-elicitation tasks. After each task, subjects' audio and video are collected, including 3D information (depth information) of facial expressions via a Kinect. The constructed dataset is from a real environment, i.e., several psychiatric hospitals, and has a specific scale. Then we propose a novel approach for potential depression risk recognition based on two kinds of different deep belief network (DBN) models. One model extracts 2D appearance features from facial images collected by an optical camera, while the other model extracts 3D dynamic features from 3D facial points collected by a Kinect. The final decision result comes from the combination of the two models. Finally, we evaluate all proposed deep models on our built dataset. The experimental results demonstrate that (1) our proposed method is able to identify patients with potential depression risk; (2) the recognition performance of combined 2D and 3D features model outperforms using either 2D or 3D features model only; (3) the performance of depression recognition is higher in the positive and negative emotional stimulus, and females' recognition rate is generally higher than that for males. Meanwhile, we compare the performance with other methods on the same dataset. The experimental results show that our integrated 2D and 3D features DBN is more reasonable and universal than other methods, and the experimental paradigm designed for depression is reasonable and practical.

Gender Differences in Anxiety and Depression before and after Alcohol Detoxification: Anxiety and Depression as Gender-Related Predictors of Relapse

BACKGROUND/AIMS

The aim of this prospective study was to estimate gender differences in anxiety, depression, and alcohol use severity among patients with alcohol use disorder (AUD) before and after detoxification program and within 12 months after discharge.

METHODS

AUD severity, state and trait anxiety, and depression were assessed in 187 patients entering an inpatient alcohol detoxification program. Follow-up assessments were performed at 6 and 12 months after discharge. A between- and within-subjects analyses explored gender differences. The predictive value of anxiety and depression for alcohol relapse was analyzed by logistic and linear regression in both genders.

RESULTS

Females had higher levels of anxiety and depression than males both at admission and after discharge. Trait anxiety and depression significantly increased 6 months after discharge in males and females respectively. Both state and trait anxiety levels at the 6-month follow-up predicted alcohol relapse at the 12-month follow-up in males. Conversely, in females, depression level at the 6-month follow-up was a predictor of relapse at the 12-month follow-up.

CONCLUSIONS

In both genders, the psychopathological dimension that showed the most significant worsening at 6-month follow-up (i.e., anxiety in males and depression in females) was found to be a significant predictor of relapse at the 12-month follow-up.

Determinants of Blood Brain-Derived Neurotrophic Factor Blood Levels in Patients with Alcohol Use Disorder

BACKGROUND

Blood brain-derived neurotrophic factor (BDNF) levels are influenced by both addiction and mood disorders, as well as somatic conditions, gender, and genetic polymorphisms, leading to widely varying results. Depressive symptoms and episodes are frequently observed in patients with alcohol use disorder, and vary widely over time, making it a challenge to determine which aspects are specifically involved in variations of serum BDNF levels in this population.

METHODS

We assessed 227 patients with alcohol dependence involved in a detoxification program, at baseline and after a follow-up of 6 months, for the Alcohol Use Disorders Identification Test score, the length of alcohol dependence, and the number of past detoxification programs. The Beck Depression Inventory and information on current tobacco and alcohol use, suicidal ideation, body mass index, age, gender, and psychotropic treatments were also collected. Serum BDNF (ELISA) and 2 genetic polymorphisms of the BDNF gene (Val33Met and rs962369) were analyzed.

RESULTS

The presence of the Met allele, 2 markers of the history of alcohol dependence (gamma glutamyl transferase and the number of past treatments in detoxification programs), and the presence of a depressive episode (but not depressive score) were significantly associated with the 2 blood levels of BDNF at baseline and after 6 months. After controlling for baseline BDNF levels, the presence of the Met allele and an ongoing depressive episode were the only variables associated with changes in BNDF levels after 6 months.

CONCLUSIONS

Low serum BDNF levels are associated with characteristics related to alcohol consumption and mood disorders, and variants of the BDNF gene in alcohol use disorder patients. The factors that most strongly influenced changes in serum BDNF levels following treatment in an alcohol detoxification program were variants of the BDNF gene and ongoing depression.

The Validity of the Montgomery-Asberg Depression Rating Scale in an Inpatient Sample with Alcohol Dependence

BACKGROUND

The Montgomery-Asberg Depression Rating Scale (MADRS) is commonly used to examine depressive symptoms in clinical settings, including facilities treating patients for alcohol addiction. No studies have examined the validity of the MADRS compared to an established clinical diagnostic tool of depression in this population. This study aimed to examine the following: (i) the validity of the MADRS compared to a clinical diagnosis of a depressive disorder (using the Structured Clinical Interview for DSM-IV-TR [SCID-IV-TR]) in patients seeking treatment for alcohol dependence (AD); (ii) whether the validity of the MADRS differs by type of SCID-IV-TR-based diagnosis of depression; and (iii) which items contribute to the optimal predictive model of the MADRS compared to a SCID-IV-TR diagnosis of a depressive disorder.

METHODS

Individuals seeking treatment for AD and admitted to an inpatient unit were administered the MADRS at day 2 of their detoxification program. Clinical diagnoses of AD and depression were made via the SCID-IV-TR at the beginning of treatment.

RESULTS

In total, 803 participants were included in the study. The MADRS demonstrated low overall accuracy relative to the clinical diagnosis of depression with an area under the receiver operating characteristic curve of 0.68. The optimal threshold for balancing sensitivity and specificity identified by the Euclidean distance was >14. This cut-point demonstrated a sensitivity of 66%, a specificity of 60%, a positive predictive value of 50%, and a negative predictive value of 75%. The MADRS performed slightly better for major depressive disorders compared to alcohol-induced depression. Items related to lassitude, concentration, and appetite slightly decreased the accuracy of the MADRS.

CONCLUSIONS

The MADRS does not appear to be an appropriate substitute for a diagnostic tool among alcohol-dependent patients. The MADRS may, however, still be a useful screening tool assuming careful consideration of cut-points.

Lipids and polyunsaturated fatty acid levels in deliberate self-harm: a 10-year follow-up study

OBJECTIVES

To evaluate if n-3 polyunsaturated fatty acids (PUFAs) and lipid levels are associated with episodes of self-harm or depression over a 10-year period.

METHODS

We included 40 individuals who self-harmed and 40 controls. Episodes of self-harm and depression were ascertained and levels of depression, impulsivity, suicidal ideation and plasma lipid levels measured at baseline and at 10-year follow-up.

RESULTS

Further episode(s) of self-harm occurred in 26% of cases. Omega-3 PUFAs or lipids were not predictive of depressive or self-harm episodes. Baseline eicosapentaenoic acid levels were modestly correlated with suicidal ideation at follow-up and dihomo-γ-linolenic acid and arachidonic acid were modestly correlated with motor impulsivity at follow-up in cases.

CONCLUSIONS

Despite significant negative correlations at baseline between plasma lipids, n-3 PUFAs and psychopathology, these levels were not predictive of clinical outcome over a 10-year period. Further research however is required due to the relatively low sample size and the risk of selection bias due to loss to follow-up in this study.

A prospective hospital study of alcohol use disorders, comorbid psychiatric conditions and withdrawal prognosis

BACKGROUND

The objective of this study was to describe the profile and alcoholic status of a population with alcohol use disorders (AUD) requesting help from a psychiatric hospital to stop drinking, as well as their clinical outcome and care consumption over the 2 years following the request.

METHODS

The visits were conducted at baseline (M0) and at 6, 12, 18 and 24 months (M6, M12, M18, M24). Demographic, clinical and psychometric data [Beck Depression Inventory (BDI), AUDIT questionnaire, Global Assessment of Functioning (GAF) scale], and information regarding the use of psychiatric care and therapeutics were collected.

RESULTS

The 330 subjects included were mostly male, aged 45.2 ± 10.2 years with an employment rate of 55.4 %, living alone (69.1 %), with a psychiatric comorbidity (60.9 %), especially depressive, and with few somatic complications. Their global functioning was poor (GAF score 49.14 ± 15.6), and less than 10 % were addicted to another substance. The abstinence rate at 24 months was 41.4 %, but only 23 % (20) abstained continuously between M0 and M24, and 66.7 % (58) intermittently. The likelihood of abstinence at M24 was greater for females aged over 60 years. The BDI score decreased significantly between M0 and M24. In all, 56.2 % of the participants were re-hospitalized after weaning, but were not integrated in long-term medical care.

CONCLUSIONS

Abstinence after alcohol withdrawal fluctuated over time indicating the need for long-term support. The treatment of AUD should not target total, continuous abstinence. Prognostic profiles combining socio-demographic, clinical and biological indicators must be established.

Validation of an Arabic Version of the GHQ-28 against the Beck Depression Inventory for Screening for Depression in War-Exposed Civilians

This study estimates the psychometric properties of the Arabic GHQ-28 against the BDI–II for screening for depression in war-exposed civilians. Two data sets collected in a civilian sample from South Lebanon were analyzed. Internal consistency in the two samples was high for the GHQ-28 (0.91 and 0.80) and the BDI–II (0.88 and 0.84). The BDI–II was significantly correlated with the GHQ-28 total score and the Depression subscale. The GHQ-28 yielded similar findings for depression cut-off scores compared to the BDI–II: for the GHQ-28 total score, a cut-off at 5/6 is recommended for detecting “severe/moderate” depression, and 8/9 for “severe” only, while from the Depression subscale analysis the recommendation was to use 8/9 as a cutoff for “severe/moderate” and 9/10 for “severe” depression. The Arabic GHQ-28 was found to be a valid instrument for screening for depression in the studied population.

Quality of life, alcohol detoxification and relapse: is quality of life a predictor of relapse or only a secondary outcome measure?

PURPOSE

To estimate variations in Overall Quality Of Life (OQOL) within 12 months following alcohol detoxification and to evaluate the predictive value of OQOL for relapse and alcohol use severity.

METHODS

Alcohol use disorders and four OQOL domains (physical health, psychological health, social relationships and environment) were assessed in 199 patients entering in-patient alcohol detoxification. Follow-up assessments were performed at 6 and 12 months after discharge. Cross-sectional and longitudinal analyses explored the relationship between OQOL and alcohol use severity, examining differences between abstinent and relapsed patients. The predictive value of OQOL was analyzed by logistic and linear regression.

RESULTS

Correlation between OQOL and Alcohol Use Disorders Identification Test scores was confirmed at all stages of observation. Abstinent patients showed a significant improvement in all OQOL domains at 6 months after discharge, whereas OQOL domains did not undergo any significant change in relapsed patients. Baseline OQOL did not prove to be predictive of either relapse or alcohol use severity.

CONCLUSIONS

Overall quality of life changed in parallel with alcohol use severity throughout the duration of the study, confirming it to be a useful and sensitive measure of secondary outcome for alcohol detoxification. Conversely, none of the OQOL baseline scores functioned as predictors of relapse within 12 months following discharge or alcohol use severity in relapsed patients.

Identification of psychological dysfunctions and eating disorders in obese women seeking weight loss: cross-sectional study

Objective. The aim of this study is to analyse associations between eating behaviour and psychological dysfunctions in treatment-seeking obese patients and identify parameters for the development of diagnostic tools with regard to eating and psychological disorders. Design and Methods. Cross-sectional data were analysed from 138 obese women. Bulimic Investigatory Test of Edinburgh and Eating Disorder Inventory-2 assessed eating behaviours. Beck Depression Inventory II, Spielberger State-Trait Anxiety Inventory, form Y, Rathus Assertiveness Schedule, and Marks and Mathews Fear Questionnaire assessed psychological profile. Results. 61% of patients showed moderate or major depressive symptoms and 77% showed symptoms of anxiety. Half of the participants presented with a low degree of assertiveness. No correlation was found between psychological profile and age or anthropometric measurements. The prevalence and severity of depression, anxiety, and assertiveness increased with the degree of eating disorders. The feeling of ineffectiveness explained a large degree of score variance. It explained 30 to 50% of the variability of assertiveness, phobias, anxiety, and depression. Conclusion. Psychological dysfunctions had a high prevalence and their severity is correlated with degree of eating disorders. The feeling of ineffectiveness constitutes the major predictor of the psychological profile and could open new ways to develop screening tools.

Assessment of depression in medical patients: a systematic review of the utility of the Beck Depression Inventory-II

To perform a systematic review of the utility of the Beck Depression Inventory for detecting depression in medical settings, this article focuses on the revised version of the scale (Beck Depression Inventory-II), which was reformulated according to the DSM-IV criteria for major depression. We examined relevant investigations with the Beck Depression Inventory-II for measuring depression in medical settings to provide guidelines for practicing clinicians. Considering the inclusion and exclusion criteria seventy articles were retained. Validation studies of the Beck Depression Inventory-II, in both primary care and hospital settings, were found for clinics of cardiology, neurology, obstetrics, brain injury, nephrology, chronic pain, chronic fatigue, oncology, and infectious disease. The Beck Depression Inventory-II showed high reliability and good correlation with measures of depression and anxiety. Its threshold for detecting depression varied according to the type of patients, suggesting the need for adjusted cut-off points. The somatic and cognitive-affective dimension described the latent structure of the instrument. The Beck Depression Inventory-II can be easily adapted in most clinical conditions for detecting major depression and recommending an appropriate intervention. Although this scale represents a sound path for detecting depression in patients with medical conditions, the clinician should seek evidence for how to interpret the score before using the Beck Depression Inventory-II to make clinical decisions.

Quality of life determinants in patients of a Psychosocial Care Center for alcohol and other drug users

Quality of life assessments in patients receiving treatment for substance dependence can serve as one predictor of response to treatment. This study aimed to identify determinants of quality of life in patients of a Psychosocial Care Center for alcohol and other drug users (CAPSad). The sample consisted of 77 patients with a diagnosis of substance dependence being treated at CAPSad for more than six months. Severity of substance dependence was assessed using the Addiction Severity Index (ASI-6), quality of life was assessed using the World Health Organization Quality of Life assessment instrument-short version (WHOQOL-BREF), and depressive symptoms were assessed by the Beck Depression Inventory (BDI). Data on CAPSad activities, psychiatric diagnoses, and medications used were collected from the medical records. Quality of life was significantly impaired in more severe cases of substance dependence and in those with more severe depressive symptoms. As for other variables, poorer quality of life was significantly associated with a greater number of years of education, unemployment, use of medications, and greater use of individual sessions with the reference professional. Linear regression analysis revealed depressive symptom severity to be an independent determinant of quality of life impairment, accounting for over 50% of the variation in physical and psychological domains. These results demonstrate the need to consider other factors, such as depressive symptoms and quality of life, in the treatment of substance dependence.