Impact of Pharmacist Intervention on Medication Adherence and Patient-Reported Outcomes among Depressed Patients in a Private Psychiatric Hospital of Nepal: a randomised controlled trial.

Aim: We aimed to evaluate the impact of pharmaceutical service intervention on medication adherence and patient-reported outcomes among patients diagnosed with depression in a private psychiatric hospital in Nepal. Methods: A single-center, open trial with a parallel design was conducted among 18 to 65 years aged patients, diagnosed with depression and under antidepressant medication(s) for ≥2 months. Patients were randomised into either the intervention or control group. The control group (n = 98) received the usual care, while the intervention group (n = 98) received a pharmaceutical service intervention. The two groups were compared using the Mann-Whitney U test, independent t-test, or chi-square test at 2 and 4 months for changes in medication adherence and patient-reported [severity of depression and health-related quality of life (HRQoL)] outcomes. Results: One hundred ninety adult patients were enrolled in the study. At baseline, there were no significant differences in any of the outcome measures between the intervention and control groups. At 2 and 4 months, the intervention group had a significant improvement only in medication adherence (P < .001) compared with the control group [MGL score: 1 (2) vs 2 (2) and 1 (1) vs 2 (1), P < .001, respectively]. Conclusion: Our study suggests that a brief pharmaceutical service intervention in the hospital setting can have a significant impact on patients' adherence to antidepressants but does not improve their severity of depression and HRQoL.

Unmet needs in the depressed primary care elderly and their relation to severity of depression: results from the AgeMooDe study.

OBJECTIVES: This study aims at examining the distribution of unmet environmental, physical, social and psychological care needs in a sample of the oldest old primary care patients with different levels of depression severity. Furthermore, the objective of this study was to analyze the association between specific unmet care needs and severity of depression. METHOD: The sample of patients aged 75 years (n = 202) and more was derived from the multicenter prospective cohort study AgeMooDe ('Late-life depression in primary care: Needs, health care utilization and costs'). Patients were assessed via structured clinical interviews containing the German version of the Camberwell Assessment of Need for the Elderly (CANE) and the German Hospital Anxiety and Depression Scale (HADS-D). Descriptive statistics, Spearman correlation coefficients and binary logistic regression analyses were computed. RESULTS: Unmet needs appeared to be substantially higher in the patient group with higher levels of depression severity according to the HADS-D score. Overall, there was weak positive linear correlation between depression and CANE total unmet needs. Except of the physical unmet needs category, all other CANE care categories showed little to moderate positive linear correlations with depression according to the HADS-D score. Depression and psychological unmet needs showed the strongest of all correlations, followed by social unmet needs. The binary logistic regression analysis revealed that patients having psychological unmet needs were 4.8 times more likely diagnosed with a probable depression. CONCLUSION: Systematic needs assessment, especially psychological needs, may play a crucial role in the course of prevention and effective treatment of late-life depression in the primary care context.

Corrigendum: Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

[This corrects the article DOI: 10.3389/fnagi.2023.1241516.].

Functional near-infrared spectroscopy-based diagnosis support system for distinguishing between mild and severe depression using machine learning approaches.

Significance: Early diagnosis of depression is crucial for effective treatment. Our study utilizes functional near-infrared spectroscopy (fNIRS) and machine learning to accurately classify mild and severe depression, providing an objective auxiliary diagnostic tool for mental health workers. Aim: Develop prediction models to distinguish between severe and mild depression using fNIRS data. Approach: We collected the fNIRS data from 140 subjects and applied a complete ensemble empirical mode decomposition with an adaptive noise-wavelet threshold combined denoising method (CEEMDAN-WPT) to remove noise during the verbal fluency task. The temporal features (TF) and correlation features (CF) from 18 prefrontal lobe channels of subjects were extracted as predictors. Using recursive feature elimination with cross-validation, we identified optimal TF or CF and examined their role in distinguishing between severe and mild depression. Machine learning algorithms were used for classification. Results: The combination of TF and CF as inputs for the prediction model yielded higher classification accuracy than using either TF or CF alone. Among the prediction models, the SVM-based model demonstrates excellent performance in nested cross-validation, achieving an accuracy rate of 92.8%. Conclusions: The proposed model can effectively distinguish mild depression from severe depression.

Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

Background: Although the study of the neuroanatomical correlates of depression in Parkinson's Disease (PD) is gaining increasing interest, up to now the cortical gyrification pattern of PD-related depression has not been reported. This study was conducted to investigate the local gyrification index (LGI) in PD patients with depression, and its associations with the severity of depression. Methods: LGI values, as measured using FreeSurfer software, were compared between 59 depressed PD (dPD), 27 non-depressed PD (ndPD) patients and 43 healthy controls. The values were also compared between ndPD and mild-depressed PD (mi-dPD), moderate-depressed PD (mo-dPD) and severe-depressed PD (se-dPD) patients as sub-group analyses. Furthermore, we evaluated the correlation between LGI values and depressive symptom scores within dPD group. Results: Compared to ndPD, the dPD patients exhibited decreased LGI in the left parietal, the right superior-frontal, posterior cingulate and paracentral regions, and the LGI values within these areas negatively correlated with the severity of depression. Specially, reduced gyrification was observed in mo-dPD and involving a larger region in se-dPD, but not in mi-dPD group. Conclusion: The present study demonstrated that cortical gyrification is decreased within specific brain regions among PD patients with versus without depression, and those changes were associated with the severity of depression. Our findings suggested that cortical gyrification might be a potential neuroimaging marker for the severity of depression in patients with PD.

Influence of Initial Severity of Depression on the Effectiveness of a Multimodal Therapy on Depressive Score, Heart Rate Variability, and Hemodynamic Parameters.

Depression is a major cause of disability among populations worldwide. Apart from primary symptoms, depressed patients often have a higher cardiovascular risk profile. Multimodal therapy concepts, including exercise, have emerged as promising approaches that not only improve depressive symptoms but also have a positive impact on cardiovascular risk profile. However, controversies have arisen concerning the influence of baseline severity on the effects of therapy concepts for this demographic. This study assessed whether pretreatment severity moderates psychological and physiological treatment outcomes of a multimodal therapy. A total of 16 patients diagnosed with mild depression (MD) and 14 patients diagnosed with severe depression (SD) took part in a 3-month outpatient multimodal treatment therapy. Before and after the treatment, depression score (Beck Depression Inventory (BDI)), peripheral systolic (pSBP) and diastolic (pDBP) blood pressure, central systolic (cSBP) and diastolic (cDBP) blood pressure, pulse wave velocity (PWV), heart rate (HR), and parasympathetic parameters of heart rate variability (RMSSD) were assessed. Significant time effects were detected for BDI (−20.0 ± 11.6, p > 0.001, η2 = 0.871), pSBP (−4.7 ± 6.8 mmHg, p < 0.001, η2 = 0.322), pDBP (−3.5 ± 6.9 mmHg, p = 0.01, η2 = 0.209), cSBP (−4.8 ± 6.5 mmHg, p < 0.001, η2 = 0.355), cDBP (−3.6 ± 6.8 mmHg, p = 0.008, η2 = 0.226), PWV (−0.13 ± 0.23 m/s, p = 0.008, η2 = 0.229), HR (4.3 ± 8.8 min−1, p = 0.015, η2 = 0.193), RMSSD (−12.2 ± 23.9 ms, p = 0.017, η2 = 0.251), and and SDNN (10.5 ± 17.8 ms, p = 0.005, η2 = 0.330). Significant time × group interaction could be revealed for BDI (p < 0.001, η2 = 0.543), with patients suffering from SD showing stronger reductions. Pretreatment severity of depression has an impact on the effectiveness of a multimodal therapy regarding psychological but not physiological outcomes.

Risk factors for severity of depression in participants with chronic medical conditions in rural primary health care settings in India.

BACKGROUND: Depression and chronic medical disorders are strongly linked. There are limited studies addressing the correlates of the severity of depression in patients with co-morbid disorders in primary care settings. This study aimed to identify the socio-demographic and disease-specific risk factors associated with the severity of depression at baseline among patients participating in a randomized controlled trial (HOPE study). METHODS: Participants were part of a randomized controlled trial in 49 primary care health centers in rural India. We included adults (≥ 30 years) with at least mild Depression or Anxiety Disorder and at least one Cardiovascular disorder or Type 2 Diabetes mellitus. They were assessed for the severity of depression using the PHQ-9, severity of anxiety, social support, number of co-morbid chronic medical illnesses, anthropometric measurements, HbA1c, and lipid profile. RESULTS: Proportionately there were more women in the moderate category of depression than men. Ordinal logistic regression showed co-morbid anxiety and a lower level of education significantly increased the odds of more severe depression, while more social support was significantly negatively associated with depression severity in women. In men, anxiety was positively associated with greater depression severity; while reporting more social support was negatively associated with depression. LIMITATIONS: This is a cross-sectional study and thus, no causal conclusions are possible. CONCLUSIONS: Anxiety and poor social support in both genders and lower educational levels in women were associated with increased severity of depression. Early identification of risk factors and appropriate treatment at a primary care setting may help in reducing the morbidity and mortality associated with depression.

Predictors and correlates of lifetime and persistent non-suicidal self-injury and suicide attempts among adult survivors of childhood sexual abuse.

Background: Childhood sexual abuse (CSA) is a well-established risk factor for non-suicidal self-injury (NSSI) and suicide attempts (SA); still few studies have examined predictors of individual differences in NSSI/SA amongst CSA survivors. Objective: To examine predictors of NSSI and SA among adult CSA-survivors. Methods: In a sample of 516, primarily female adult CSA-survivors recruited from support centres for sexual abuse survivors in Norway, we examined the role of abuse/perpetrator characteristics, and the degree/severity of exposure to other types of childhood maltreatment (cumulative childhood maltreatment; CCM), as predictors of lifetime NSSI and SA. In a subsample of 138 individuals responding to follow-up waves two- and four years later, these same distal factors, as well as previous NSSI and proximal factors in the form of symptoms of mental health disorders (posttraumatic stress, anxiety, depression, sleep disturbances, and eating disorders), relational problems, and perceived social support, were examined as predictors of persistent NSSI. Finally, those attempting new SA during the follow-up period were compared to those who did not on these variables. Results: Higher CCM scores and having had an unknown perpetrator positively predicted lifetime NSSI scores. Higher CCM scores, violent abuse, and having had an unknown perpetrator predicted lifetime SA. Higher CCM scores, previous NSSI, having had a known perpetrator, as well as higher depression-, anxiety- and eating disorder scores, positively predicted persistent NSSI during the four-year follow-up period. Compared to those with no new SA, those reporting new SA during the follow-up period had higher CCM, lifetime NSSI, mental health symptoms and relational problem scores, lower perceived social support scores, and were more likely to have done a past SA and to have experienced abuse involving physical violence. Conclusions: A broad range of both distal and proximal factors should be assessed as potential predictors of NSSI and SA among adult CSA-survivors.

Antecedentes: El abuso sexual infantil (CSA por sus siglas en inglés) es un factor de riesgo bien establecido para las autolesiones no suicidas (NSSI por sus siglas en inglés) y los intentos suicidas (SA por sus siglas en inglés); aun así, pocos estudios han examinado los predictores de las diferencias individuales en NSSI/SA en los sobrevivientes de CSA. Objetivo: Examinar los predictores de NSSI y SA entre adultos sobrevivientes de CSA.Métodos: En una muestra de 516, primariamente mujeres adultas sobrevivientes de CSA reclutadas de centros de apoyo para sobrevivientes de abuso sexual en Noruega, examinamos el rol de las características del abuso/perpetrador y el grado/severidad de la exposición a otros tipos de maltrato infantil (maltrato acumulativo infantil; CCM por sus siglas en ingles), como predictores de NSSI y SA en la vida. En una submuestra de 138 individuos que respondieron a las etapas de seguimiento dos y cuatro años después, se examinaron como predictores de NSSI persistente, estos mismos factores distales, así como NSSI previos y factores proximales en la forma de síntomas de trastornos de salud mental (estrés postraumático, ansiedad, depresión, trastornos del sueño y trastornos de la conducta alimentaria), problemas relacionales, y apoyo social percibido. Finalmente, se compararon en estas variables los que intentaron un nuevo SA durante el periodo de seguimiento con los que no lo hicieron.Resultados: Puntajes más altos de CCM y haber tenido un perpetrador desconocido, predijeron positivamente puntajes de NSSI en la vida. Puntajes de CCM más altos, abuso violento y haber tenido un perpetrador desconocido predijeron el SA en la vida. Los puntajes más altos de CCM, NSSI previos, haber tenido un perpetrador conocido, así como puntajes más altos de depresión, ansiedad y trastornos alimentarios, predijeron positivamente NSSI persistente durante el periodo de seguimiento de 4 años. Comparado con los individuos sin nuevos SA, los que reportaron SA nuevos durante el periodo de seguimiento tenían puntajes más altos de CCM, NSSI en la vida, síntomas de salud mental y problemas relacionales, puntajes más bajos de apoyo social percibido y tenían más probabilidades de haber realizado SA en el pasado y haber experimentado abuso que involucraba violencia física.Conclusiones: Se debe evaluar una amplia gama de factores distales y proximales como posibles predictores de NSSI y SA entre adultos sobrevivientes de CSA.

Prediction by data mining, of suicide attempts in Korean adolescents: a national study.

OBJECTIVE: This study aimed to develop a prediction model for suicide attempts in Korean adolescents. METHODS: We conducted a decision tree analysis of 2,754 middle and high school students nationwide. We fixed suicide attempt as the dependent variable and eleven sociodemographic, intrapersonal, and extrapersonal variables as independent variables. RESULTS: The rate of suicide attempts of the total sample was 9.5%, and severity of depression was the strongest variable to predict suicide attempt. The rates of suicide attempts in the depression and potential depression groups were 5.4 and 2.8 times higher than that of the non-depression group. In the depression group, the most powerful factor to predict a suicide attempt was delinquency, and the rate of suicide attempts in those in the depression group with higher delinquency was two times higher than in those in the depression group with lower delinquency. Of special note, the rate of suicide attempts in the depressed females with higher delinquency was the highest. Interestingly, in the potential depression group, the most impactful factor to predict a suicide attempt was intimacy with family, and the rate of suicide attempts of those in the potential depression group with lower intimacy with family was 2.4 times higher than that of those in the potential depression group with higher intimacy with family. And, among the potential depression group, middle school students with lower intimacy with family had a 2.5-times higher rate of suicide attempts than high school students with lower intimacy with family. Finally, in the non-depression group, stress level was the most powerful factor to predict a suicide attempt. Among the non-depression group, students who reported high levels of stress showed an 8.3-times higher rate of suicide attempts than students who reported average levels of stress. DISCUSSION: Based on the results, we especially need to pay attention to depressed females with higher delinquency and those with potential depression with lower intimacy with family to prevent suicide attempts in teenagers.

Effect of depression on sleep: Qualitative or quantitative?

BACKGROUND: THE PRESENT STUDY WAS DESIGNED TO ASSESS WHETHER SUBJECTIVE SLEEP PATTERNS DIFFER BETWEEN: (i) depressed patients and controls, and (ii) between subjects with different severity of depression. Based on available literature, it was hypothesized that sleep patterns must be different between the above mentioned groups. MATERIALS AND METHODS: This study included 60 subjects with major depressive disorder and 40 subjects in the control group. Subjects with sleep disturbance secondary to any other factor, e.g., medical illness, environmental factors, other psychiatric illness etc, were not included in the study. Depression severity was assessed in the subjects with depression with the help of Beck Depression Inventory II. Subjective sleep complaints were noted in the presence of a reliable informant, preferably bed partner. All the information was recorded in a semistructured performa. Statistical analysis was done with the help of SPSS v 11.0. The Chi square and Fisher exact tests were used for categorical variables; independent t-test and one way ANOVA were applied for numerical variables. Ordinal variables were analyzed using Mann Whitney U and Kruskall-Wallis tests. RESULTS: Depression and control groups were similar in age (P = 0.32) and gender (P = 0.14) distribution. Subjects in the depression group had lesser total sleep time (P = 0.001), longer sleep latency (P = 0.001), frequent awakenings (P = 0.04), greater wake-after-sleep onset and offset times (both P = 0.001), lesser sleep efficiency, and tended to wake up early (Mann Whitney U = 913.5; P = 0.05). Subjects with severe depression were different from the mild and moderate groups with regards to total sleep time (P = 0.002), night-time sleep (P = 0.007), and sleep efficiency (P = 0.001) even when the three groups were comparable in age. CONCLUSION: Depression is associated with sleep disturbances, not only qualitatively, but also quantitatively. Sleep disturbance arises only after a critical level of depression is reached, and depression of varying severity may selectively affect different sleep parameters.