Predictors Of Depression Research Articles

Death Anxiety and Depression among Nurses: The Mediating Role of Empathy

Background: The COVID-19 pandemic significantly affected life all over the world. Death anxiety has a significant impact on the mental health of individuals, especially in the health care professionals. The fear and apprehension surrounding mortality has significantly affected nurses, leading to various mental health challenges, including depression. While the awareness of death can impose substantial psychological strain, it can also foster positive traits essential for patient care, such as empathy. Objective: The study identifies the relationship between death anxiety, depression and empathy. It also explores the mediating role of empathy in the relationship between death anxiety and depression among nurses. Method: A cross-sectional research design and a purposive sampling strategy were used to collect data from nurses (N=200) working at different government and private hospitals in Lahore, Pakistan, during the COVID-19 pandemic. The participants' ages ranged from 23 to 52. The Siddiqui-Shah Depression Scale, Urdu-translated versions of the Death Anxiety Scale, and Jefferson Scale of Empathy were administered to nurses. Results: The results reveal a positive relation between death anxiety with depression (r= .43**) and empathy (r = .31**). Death anxiety and empathy were found to be significant predictors of depression. Furthermore, empathy was found to be a significant mediator between death anxiety and depression. Conclusion: Based on the findings, clinical psychologists may devise various interventions/management plans to manage death anxiety and depression among nurses.

Impact of dengue fever on depression, anxiety, and stress symptoms in Esmeraldas Province, Ecuador: a prospective cohort study

BackgroundPhysical symptoms of dengue have been documented extensively, but knowledge gaps on dengue-associated mental health hazards remain. We investigated the frequency of psychiatric symptoms (depression, anxiety, and stress) and neurocognitive performance during the first year after a dengue episode.MethodsUsing DASS-21 scores at 3, 6, and 12 months, we assessed depression, anxiety, and stress in anti-dengue IgM-positive adults and matched controls during the 2021 dengue season in Esmeraldas Province, Ecuador. Patients with DASS-21 scores ≤ 4 were considered normal; those with scores of 5–7, 8–10, and ≥ 11 indicated mild, moderate, and severe depression, respectively; cutoff scores for anxiety and stress were ≥ 5 and ≥ 9, respectively. We also assessed ‘delayed matching to sample’ (DMS) and ‘spatial working memory’ (SWM) using the Cambridge Neuropsychological Test Automated Battery.ResultsWe enrolled 102 cases and 78 controls. At 3 months, 90 cases and 70 controls were available for follow-up, among these 40/90 (44.4%) cases and 12/70 (17.1%) controls had DASS-21 scores ≥ 5 (RR 2.7, 95% CI [1.5–4.7]). Dengue remained a predictor for depression after adjusting for age, sex, and COVID-19 status. We observed no difference in anxiety between the groups, but stress scores increased at month 3 (RR 1.87, 95% CI [1.01–3.4]). DASS-21 scores normalized during follow-up. DMS and SWM did not differ between groups at 3 and 6 months. At month 12, cases had lower SWM than controls did (p value < 0.001).ConclusionsCare providers should be aware of dengue-associated mood disorders and facilitate timely referral to mental health services. Future longitudinal studies are warranted to validate our observations regarding the impact of dengue on mental health and neurocognitive status in affected patients.

A longitudinal investigation of parenting, depression, and counseling use among Asian American adolescents.

Asian American adolescents are equally or more likely to experience depression but less likely to seek treatment for depression than adolescents from other racial and ethnic groups in the US. The current study examined the long-term effects of parental care, parental control, and parental closeness on depression and counseling use among Asian American adolescents. Using data from the National Longitudinal Study of Adolescent Health (Add Health), we conducted a cross-lagged path analysis with 270 Asian American adolescents (48.1% female; 51.9% male). The study used data from Waves I, II, and III (1994-2002) with participants' mean ages ranging from 14 to 23. Findings indicated that the cross-sectional relationships between parenting characteristics and depression were stronger than the longitudinal relationships suggesting that parenting practices may be a stronger proximal, rather than distal, predictor of depression. Specifically, parental closeness was associated with less depression in early and mid-adolescence (age 12-18), but the relationship changed direction in young adulthood (age 18-26). Additionally, a significant interaction suggested that parental care was related to fewer depressive symptoms for those who reported high, compared to low, parental control in mid-adolescence (age 14-18). Furthermore, high parental care was associated with more counseling use at high levels of control. However, high parental care was associated with less counseling use at low levels of parental control in early adolescence. These results highlight the importance of understanding parenting characteristics using longitudinal designs when examining the development of depression and help-seeking behaviors among Asian American adolescents.

High overcommitment and low reward as potential predictors for increased depressive symptoms, suicidal ideation, and suicide risk in German veterinarians.

Higher rates of depression, suicidal ideation and suicide risk have been reported for veterinarians in Germany. In this study, several demographic and job-related factors were examined to determine whether they could be considered possible predictors of depression, suicidal ideation, and suicide risk. For this purpose, a survey was conducted among veterinarians in Germany. The demographic factors surveyed were gender, age, working status (employed/self-employed), income, field of work (practicing/non-practicing veterinarian), weekly working hours and community size. For assessing job-related factors, the Effort-Reward-Imbalance questionnaire (effort, reward, overcommitment), several subscales of the Copenhagen Psychosocial Questionnaire (quantitative demands, emotional demands, demands for hiding emotions, meaning of work, work-privacy-conflict, thoughts of leaving the job) and the Copenhagen Burnout Inventory were used. A hierarchical logistic regression analysis was performed with the demographic and job-related factors as independent variables and depressive symptoms, suicidal ideation, and suicide risk as dependent variables, respectively. A total of 3.118 veterinarians (78.8% female) between 22 and 69 years (mean age 41.3 years) were included in the study. The factors used resulted in the highest variance explanation for depressive symptoms (57%), followed by suicidal ideation (34%) and suicide risk (23%). Low reward and high overcommitment were found to be the most important predictors of depressive symptoms, suicidal ideation, and suicide risk. Significant relationships with depressive symptoms, suicidal ideation, and suicide risk were also found for burnout, demands for hiding emotions, and thoughts of leaving the job. The results of this study point to opportunities for changes in the veterinary working environment, for the development of prevention and intervention programs for veterinarians, and for the further development of the veterinary curriculum to strengthen the mental health of veterinarians in Germany.

Investigation of Depression and Post-Traumatic Growth in Renal Transplant Recipients via Self-Assessment.

Objective: In this study, we aimed to determine post-traumatic growth and depression levels in renal transplant recipients and the relationship between these two variables. Design and Methods: The study was conducted with a descriptive, cross-sectional, and correlational design. The data for the study were collected at the organ transplant unit of a research and training hospital located in the west of Turkey. The sample of the study included 122 kidney transplant recipients (n = 122). A Sociodemographic Information Form, the Post-Traumatic Growth (PTG) Inventory, and the Beck Depression Inventory (BDI) were employed to collect data. In the analyses of the data, descriptive statistics, ANOVA, an independent-samples t-test, post hoc tests, and Pearson correlation tests were used. Results: As the ages of the renal transplant recipients increased, their depression scores decreased, while their PTG scores increased. Higher depression levels were identified in the female participants compared to the male participants and in those with a low income compared to other income groups. The lowest PTG levels were found in the recipients who received their kidney transplants from third-degree relatives. Age, gender, economic status, and time of transplant were predictors of depression. The identity of the donor was the most significant predictor of PTG (62% explanation rate). A strong and inverse correlation was found between depression and PTG (p < 0.05). Conclusions: Post-traumatic growth was found to decrease depression. However, while poor economic status led to depression, high economic status did not lead to a significant change in PTG. As education levels increased, PTG decreased, but education status did not have any significant effect on depression. On the other hand, there was a negative correlation between PTG and depression. The results obtained in this study are valuable and important in terms of understanding depression better and determining PTG as a significant factor that could alleviate it.

Predictors of depression among caregivers of patients with severe mental illness in Northwest Ethiopia, 2023: an explanatory sequential mixed-method study.

Severe mental illness results in an enormous social and economic burden on affected individuals, their families, and communities, especially in developing countries, such as Ethiopia. The aim of this study was to assess the level of depression among caregivers of patients with severe mental illness in Debre Tabor Town, Northwest Ethiopia in 2023. This institution-based explanatory mixed study was conducted at Debre Tabor Compressive Specialized Hospitals between September 30 to October 30, 2023. A systematic random sampling technique was used to select 260 study participants, and a public health questionnaire was used to assess depression. Epicollect5 was used to collect data, which were then exported to the SPSS-25 for analysis. Variables with a p-value <0.25 were considered candidates for the multivariate logistic regression analysis. The odds ratios with a 95% confidence interval were used to determine the strength of the association. An in-depth interview was conducted with 11 participants, selected using purposive sampling. The prevalence of depression was 31.3% (95% CI = 29.7-38.6). The multivariate analysis showed that being female (AOD = 2.43, CI = 1.42-7.23), divorced/widowed (AOD = 1.8, CI = 1.32-6.34), poor social support (AOD = 2.2, CI = 1.9-5.87), and perceived stigma (AOD = 2.33, CI = 0.24-13.22) were positively associated with depression. The qualitative results suggest that being female, illiterate, severity of the illness, poor social support, and stigma were factors for depression. The prevalence of depression was high among caregivers of patients with severe mental illness. Female sex, being divorced or widowed, being illiterate, poor social support, and perceived stigma were the contributing factors. This implies that a greater focus on caregivers and the government increases mental health literacy and mental health community services.

Perceived parental rearing styles and depression in Chinese adolescents: the mediating role of self-compassion.

Adolescence is a period characterized by rapid biological and psychological change, and adolescents have a heightened risk of depression. Parental rearing is an important influencing factor for depression in adolescence. However, the mechanism of influence needs further exploration. A total of 1839 adolescents were recruited from a junior and a senior high school in Zhongshan City, Guangdong Province, China. They were requested to completed the Parental Bonding Instrument (PBI), Self-Compassion Scale (SCS), and Depression Anxiety and Stress Scale-21(DASS-21). Adolescents recalled their mothers as being more caring and controlling than their fathers. Parental care (maternal care, paternal care) and parental encouragement of autonomy (maternal encouragement of autonomy, paternal encouragement of autonomy) were both negative predictors of depression, while parental control (maternal control, paternal control) was positive predictor of depression. Self-compassion mediated all relationships between parental rearing styles (parental care, parental encouragement of autonomy, and parental control) and depression but played different mediating roles (complete or incomplete mediating role) in different relationships. Self-compassion plays a mediator role in all relationships between perceived parental rearing styles (parental care, parental encouragement of autonomy, and parental control) and depression. Adolescents who grown up with less parental care, less parental encouragement of autonomy, and high parental control deserve special attention. Educators and clinicians could help those adolescents reduce the occurrence of depression by increasing their level of self-compassion.

The Prevalence and Determinants of Mental Health Problems in Lebanon: A Meta-Analytic Study of 3957 Healthcare Workers.

Healthcare workers are continuously exposed to challenging environments, making them liable for poor mental health. The COVID-19 pandemic exacerbated this problem, however available data in Lebanon is scarce. We conducted this investigation to provide comprehensive evidence on the mental health of Lebanese healthcare workers. In this systematic review, we analyzed 3957 workers reported in 15 cross-sectional studies (10 during and five before the pandemic), identified after searching four databases. Examined mental health problems included depression, anxiety, stress, posttraumatic stress disorder (PTSD), and poor sleep quality. STATA software was used to pool the prevalence across studies. Subgroup analyses were performed based on the pandemic status, severity of mental health problems, and healthcare worker type. Gender and marital status were analyzed as potential risk factors. The methodological quality of all included studies was good as per the National Institute of Health risk of bias tool. Anxiety, depression, stress, PTSD, insomnia, and poor sleep quality were reported in 50%, 52%, 50%, 35%, 45%, and 41% of the population, respectively. Most cases had mild anxiety (40%), mild depression (45%), but severe stress (27%). Depression and anxiety were highest among pharmacists (69% and 56%) and nurses (49% and 45%), respectively. Compared to the pre-pandemic period, depression (36% vs. 62%) and anxiety (30% vs. 56%) rates were higher during the pandemic, while stress levels were lower (62% vs. 45%). Both gender and marital status were insignificant predictors of depression, anxiety, stress, or PTSD. Depression, anxiety, posttraumatic stress, insomnia, and poor sleep quality are experienced by approximately one in every two Lebanese healthcare workers. The rate of depression and anxiety almost doubled during the pandemic with higher rates among pharmacists and nurses than physicians and residents. Both gender and marital status were deemed insignificant predictors of reported mental health problems.

Association between sleep disorder and depression in stroke in the National Health and Nutrition Examination Surveys (NHANES) 2005 to 2014

BackgroundTo investigate the association between sleep disorder and depression in stroke population using data from the National Health and Nutrition Examination Surveys (NHANES) conducted between 2005 and 2014. MethodsParticipants included stroke population who reported on sleep disorder and completed the Patient Health Questionnaire-9 (PHQ-9) to assess depressive symptom. Sleep disorder was self-reported and categorized dichotomously. Multivariate logistic regression, subgroup analysis, receiver operating characteristic curve (ROC) and restricted cubic spline (RCS) were used to explore the association between sleep disorder and depression. ResultsThe final sample included 566 stroke survivors (weighted n = 3,326,625). Multivariate logistic regression analysis confirmed that sleep disorder was independently associated with an increased risk of depression even after adjusting for potential confounders (OR = 2.616, 95 % CI: 2.561 to 2.599, P < 0.0001). Subgroup analysis indicated that this association was particularly strong among female stroke population (OR = 5.515). Sleep disorder as a significant predictor of depression, while the relationship between sleep time and depression is characterized by non-linearity. ConclusionsSleep disorder is significantly associated with an increased risk of depression in stroke. This relationship remains robust across various sociodemographic and lifestyle factors, highlighting the need for integrated interventions targeting both sleep and mood disturbances in stroke care.

Negative life events predict depressive trends: the moderating effect of overgeneral autobiographical memory and early parenting behaviour

ABSTRACT The Emerging Adulthood is a complex and chaotic period and depression is one of the main psychological health problems during this period. Overgeneral autobiographical memory (OGM) is prevalent among patients with clinical depression. However, the prediction of OGM in groups with non-clinical depression and its influencing mechanisms remain inconclusive. Studies have shown that OGM and early parenting behaviour are vulnerable factors of depression in emerging adulthood, which may be triggered by negative life events. Our longitudinal study included 241 participants (M age = 21.88 years). At baseline, participants completed measures of current negative life events, depression, early parenting behaviour and an autobiographical memory test. Thereafter, they were tracked for depression every 35 days. We used the latent class growth model to differentiate levels and trends of depression among non-clinical participants. The analysis showed that the effect of negative life events on depression was moderated by OGM and early parenting behaviour. However, this moderating effect was found only in the low-risk depression group. Our findings indicate that early parenting behaviour might account for the different mechanisms of OGM production in non-clinical groups. Moreover, it underlines the importance of OGM and early parenting behaviour as potential predictors of future depression in non-clinical groups.

COVID-19 and mental distress among health professionals in eight European countries during the third wave: a cross-sectional survey.

Even during the third wave of the COVID-19 pandemic health professionals were facing mental health challenges. The aim of this study was to examine the mental health of doctors, nurses and other professional groups in Europe and to identify differences between the professional groups. We conducted a cross-sectional online survey in 8 European countries. We asked for demographic data, whether the participants were exposed to COVID-19 at work, for main information sources about the pandemic, the Depression Anxiety Stress Scales (DASS-21), and major stressors. A MANCOVA was carried out to find predictors of mental health among health care professionals. The sample (N = 1398) consisted of 237 physicians, 459 nurses, and 351 other healthcare professionals and 351 non-medical professionals with no direct involvement in patient care. The mean mental health of all groups was affected to a mild degree. Major predictors for depression and anxiety weretheprofession groupwith higher scores especially in the group of the nurses and working directly with COVID-patients. In the third wave of the COVID-19 pandemic, the psychological burden on health professionals has remained high, with being nurse and working directly with COVID19 patients being particular risk factors for mental distress. We found as a main result that nurses scored significantly higher on depression and anxiety than practitioners.

Burnout syndrome, anxiety, and depression symptoms among workers in radiation field

BackgroundJob burnout is defined as physical, emotional, and mental exhaustion due to persistent work stress, and it includes emotional exhaustion (EE), cynicism (CY), and reduced personal accomplishment (PA) and usually leads to symptoms of depression, lack of motivation, and decreased enthusiasm. Previous studies from different countries have suggested that job burnout, depression, and anxiety are a common work-related problems. This study aims to assess for job burnout, depression, and anxiety among radiation workers in order to investigate the effects of radiation exposure during work on the mental health. This comparative cross-sectional study was performed on 208 workers in the Egyptian Atomic Energy Authority (EAEA) and the Egyptian Nuclear and Radiological Regulatory Authority (ENRRA) at Cairo Governorate, Egypt. Study participants were divided into 2 groups: 1st group which included 104 workers among radiation field and 2nd group which included 104 workers and employees who do not often work among radiation field. Maslach Burnout Inventory Scale (MBI), Hamilton Rating Scale for Depression (HAM-D), and Hamilton Rating Scale for Anxiety (HAM-A) were used to assess for burnout, depression, and anxiety among study participants.ResultsThe prevalence and severity of depression, anxiety, burnout, and among workers inside radiation field group were statistically significantly higher than those working outside radiation field group. Work type (WIRF) and number of working hours per week (> 40 h) were the significant risk factors for all the burnout, depression, and anxiety, while age (> 40–60 years old) was a significant predictor for depression, female gender was a significant predictor for anxiety, and both age (20–40 years old) and years of experience (≤ 10 years) were significant predictors for burnout among workers inside radiation field.ConclusionsBurnout, depression, and anxiety are common among workers inside radiation field with higher prevalence and severity than those working outside radiation field. Younger age, fewer years of experience, and more working hours per week are significantly associated risk factors for burnout among workers inside radiation field.

Evaluation of the Psychometric Properties of the 18-Items Dysfunctional Attitudes Scale (Form B) in a Portuguese Sample of People Aged 60 and Over.

The aim of the study is to assess the psychometric properties of the Portuguese version of the 18-items Dysfunctional Attitudes Scale (Form B) in a Portuguese sample of people aged 60 and over. Background: The 18-item Dysfunctional Attitudes Scale (Form B) is an instrument for assessing dysfunctional attitudes and can be useful as a predictor of depression for both initial episodes and relapses Methods: This was a one-stage cross-sectional survey of Portuguese-speaking people aged 60 years and over, able to read and write, functionally autonomous, and living in the community in their usual residences. The instrument was evaluated for its psychometric properties. Convergent validity with the Beck Depression Inventory-II was assessed. Results: The Portuguese version of the 18-item Dysfunctional Attitudes Scale (Form B) was structured into three factors, which explained a total of 58.95% of the total variance of the instrument. The exploratory factor analysis resulted in a modified model in which three factors were obtained with an eigenvalue greater than one (Kaiser's criterion). Three factors were obtained instead of two as in the original study. It showed an internal consistency (Cronbach's alpha = 0.770) and an interclass correlation coefficient ranging from 0.166 to 0.449, and the overall convergent validity with the Beck Depression Inventory-II was considered good; Conclusions: The Portuguese version of the Dysfunctional Attitudes Scale (DAS-18B) of people aged 60 and over demonstrated good psychometric properties.

Frequency &amp; Predictors of Depression in Patients of Chronic Heart Failure with Reduced Ejection Fraction (HFrEF)

Background: Clinically significant depression is estimated to occur in a significant portion of chronic heart failure (CHF) patients and increases sharply with increase in heart failure severity. However, the frequency and predictors of depression in this group of patients are underreported. This study was designed to assess frequency &amp; predictors of depression in patients of chronic heart failure with reduced ejection fraction (HFrEF). Methods: This cross-sectional analytical study was performed in the department of Cardiology, Dhaka Medical College Hospital, Dhaka, during the period from October’2018 to Septemeber’2019. One hundred and fifty-two CHF patients with reduced ejection fraction (&lt;40%) either admitted in the department of Cardiology or attended Cardiology OPD, Dhaka Medical College Hospital (DMCH), Dhaka who fulfilled the selection criteria were included into the study. A translated and validated Patient Health Questionnaire (PHQ-9) in Bengali was used to assess depression level in CHF patients in this study. Informed written consent was taken from each patient. Approval for the study was taken from Ethical Review Committee (ERC) of Dhaka Medical College before commencement of the study. After compiling data from all participants, statistical analyses were performed using the Statistical Package for Social Science (SPSS), version 22.0 for windows. Results: Mean age of the patients was 58.68±9.40 years, ranging from 36 to 75 years. Male predominance was noted (72% vs 28%). Overall, frequency of depression was 56%. Among the depressed patients (n=85), majority (40%) had minimal depression while 27%, 19% and 14% had mild, moderate and severe depression. respectively. Among the different risk factors, DM and sedentary lifestyle were significantly associated with depression (p&lt;0.05). Age &gt;65 years, sedentary lifestyle, and H/O past MI were independently associated with depression among chronic HErEF patients. Widowed patients, diabetes, hospital readmission in last 2 months before study inclusion and NYHA class III/IV were also significantly associated with depression among patients with chronic HFrEF (p&lt;0.05). Conclusion: More than half of the patients with chronic HFrEF had concurrent depression of varied severity. Proper care of depression along with HF may improve the survival and quality of life of these patients. Bangladesh Heart Journal 2024; 39(2): 74–84

Screening depression among university students utilizing GHQ-12 and machine learning

The escalating incidence of depression has brought attention to the increasing concern regarding the mental well-being of university students in the current academic environment. Given the increasing mental health challenges faced by students, there is a critical need for efficient, scalable, and accurate screening methods. This study aims to address the issue by using the General Health Questionnaire-12 (GHQ-12), a well recognized tool for evaluating psychological discomfort, in combination with machine learning (ML) techniques. Firstly, for effective screening of depression, a comprehensive questionnaire has been created with the help of an expert psychiatrist. The questionnaire includes the GHQ-12, socio-demographic, and job and career-related inquiries. A total of 804 responses has been collected from various public and private universities across Bangladesh. The data has been then analyzed and preprocessed. It has been found that around 60% of the study population are suffering from depression. Lastly, 16 different ML models, including both traditional algorithms and ensemble methods has been applied to examine the data to identify trends and predictors of depression in this demographic. The models' performance has been rigorously evaluated in order to ascertain their effectiveness in precisely identifying individuals who are at risk. Among the ML models, Extremely Randomized Tree (ET) has achieved the highest accuracy of 90.26%, showcasing its classification effectiveness. A thorough investigation of the performance of the models compared, therefore clarifying their possible relevance in the early detection of depression among university students, has been presented in this paper. The findings shed light on the complex interplay among socio-demographic variables, stressors associated with one's profession, and mental well-being, which offer an original viewpoint on utilizing ML in psychological research.

Predicting Depression Among Chinese Patients with Narcolepsy Type 1: A Machine-Learning Approach.

Depression is a common psychiatric issue among patients with narcolepsy type 1 (NT1). Effective management requires accurate screening and prediction of depression in NT1 patients. This study aims to identify relevant factors for predicting depression in Chinese NT1 patients using machine learning (ML) approaches. A total of 203 drug-free NT1 patients (aged 5-61), diagnosed based on the ICSD-3 criteria, were consecutively recruited from the Sleep Medicine Center at Peking University People's Hospital between September 2019 and April 2023. Depression, daytime sleepiness, and impulsivity were assessed using the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or the Self-Rating Depression Scale (SDS), the Epworth Sleepiness Scale for adult or children and adolescents (ESS or ESS-CHAD), and the Barratt Impulse Scale (BIS-11). Demographic characteristics and objective sleep parameters were also analyzed. Three ML models-Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)-were used to predict depression. Model performance was evaluated using receiver operating curve (AUC), accuracy, precision, recall, F1 score, and decision curve analysis (DCA). The LR model identified hallucinations (OR 2.21, 95% CI 1.01-4.90, p = 0.048) and motor impulsivity (OR 1.10, 95% CI 1.02-1.18, p = 0.015) as predictors of depression. Among the ML models, SVM showed the best performance with an AUC of 0.653, accuracy of 0.659, sensitivity of 0.727, and F1 score of 0.696, reflecting its effectiveness in integrating sleep-related and psychosocial factors. This study highlights the potential of ML models for predicting depression in NT1 patients. The SVM model shows promise in identifying patients at high risk of depression, offering a foundation for developing a data-driven, personalized decision-making tool. Further research should validate these findings in diverse populations and include additional psychological variables to enhance model accuracy.

Self-Guided Behavioral Activation Using an Online Single-Session Intervention: Content and Lexical Analyses of Activity Scheduling

The Common Elements Toolbox (COMET) is a self-guided online single-session intervention (SSI) containing cognitive-behavioral elements, including behavioral activation (BA). Little is known about the process of activity scheduling in BA. Using data from an 8-week randomized controlled trial of COMET with 409 online workers with a history of psychopathology, two raters coded the types of activities individuals scheduled during the intervention. Additionally, we compared the activities to a BA dictionary developed from therapist-led psychotherapy. We explored baseline clinical and demographic variables that were predictive of the activity category scheduled and explored the scheduled activity category as a predictor of depression, anxiety, and well-being post-intervention. Results yielded 9 different activity types, most commonly sedentary hobbies (41%), physical activity (29%), and active hobbies (18%). We found a small overlap (17%) between the self-guided BA activities in our COMET sample and those in the existing BA dictionary. Demographic variables were predictive of activity category, but clinical variables were not. The type of activity scheduled was not predictive of post-intervention outcomes. In self-guided BA, individuals, particularly men, less educated participants, and racial-ethnic minorities, tend to pick sedentary activities. Findings underscore the need for adaptive and personalized interventions.

Predictive models of post-traumatic stress disorder, complex post-traumatic stress disorder, depression, and anxiety in children and adolescents following a single-event trauma.

This study examined the power of theory-derived models to account for the development of PTSD, Complex PTSD (CPTSD), depression, and anxiety in children and adolescents who had experienced a single-event trauma. Children (n = 234, aged 8-17 years) recruited from local Emergency Departments were assessed at two and nine weeks post-trauma. Data obtained from self-report questionnaires completed by the child, telephone interviews with parents, and hospital data were used to develop four predictive models of risk factors for PTSD, CPTSD, depression, and Generalized Anxiety Disorder (GAD). ICD-11 proposed diagnostic criteria were used to generate measures for CPTSD and PTSD to assess for risk factors and identify the sample prevalence of these disorders. At nine weeks post-trauma, 64% did not meet criteria for any disorder, 23.5% met criteria for PTSD, and 5.2% met criteria for CPTSD. 23.9% and 10.7% had developed clinically significant symptoms of depression and GAD, respectively. A cognitive model was the most powerful predictive model, a psychosocial model was weak, and subjective markers of event severity were more powerful than objective measures. Youth exposed to single-incident trauma may develop different forms of psychopathology, and PTSD and CPTSD are frequently experienced alongside other conditions. The cognitive model of PTSD shows utility in identifying predictors of PTSD, CPTSD, depression, and GAD, particularly the role of trauma-related negative appraisals. This supports the application of cognitive interventions which focus upon re-appraising trauma-related beliefs in youth.

Factors predicting depression among persons post-coronary artery bypass graft surgery: A cross-sectional study in Thailand.

Coronary artery bypass graft (CABG) surgery is a highly effective coronary artery disease treatment, providing immediate relief and promising long-term benefits. However, it is a major procedure with significant risks, including the potential for depression. Many patients experience depression following CABG, which can negatively impact their overall recovery, affecting both physical and mental health. This study aimed to determine factors predicting depression in patients following CABG surgery. This cross-sectional study was conducted with data collected between January and April 2024. A total of 272 post-CABG patients from two super tertiary care hospitals in Bangkok, Thailand, were recruited through purposive sampling. All research instruments were validated and tested for reliability. Data were analyzed using multiple regression analysis. The study found that hope, optimism, illness perception, social support, and anxiety were correlated with depression (adjusted R² = 0.381), but these variables explained only 38.1% of the variance (p <0.05). Among these factors, anxiety (β = 0.311), optimism (β = 0.203), social support (β = -0.117), and illness perception (β = -0.143) were significant predictors (p <0.05), while hope was not a significant predictor. Thus, anxiety emerged as the most crucial predictor of depression in patients who have undergone CABG. Nurses play a vital role in preventing and managing depression in post-CABG patients. Screening for anxiety and addressing it can prevent depression, enhance social support, and improve outcomes. To develop effective nursing strategies, it is essential for nurses to assess anxiety and implement interventions that promote social support, optimism, and illness perception. These measures can improve care quality, reduce readmission rates, and enhance patients' overall quality of life.

Longitudinal Impact of Disordered Eating Attitudes on Depression, Anxiety, and Somatization in Young Women with Anorexia and Bulimia.

Background/Objectives: Eating disorders, characterized by severe disturbances in eating behavior, are a public health concern, particularly among young women. This longitudinal study aimed to investigate the relationship between disordered eating attitudes and mental health outcomes, including depression, anxiety, and somatization, among individuals with eating disorders. Methods: A total of 471 young German women hospitalized with anorexia nervosa or bulimia nervosa participated in this study. Assessments were conducted at two points over a two-month interval using the Eating Disorder Inventory-2 (EDI-2) and the Patient Health Questionnaire. Regression analyses were performed to determine predictors of depression, anxiety, and somatization. The study controlled for socio-demographic segmentation using Sinus-Milieus, a social classification system, as a covariate. Results: Regression analyses revealed that interpersonal distrust and impulse regulation were significant predictors of subsequent depression. Impulse regulation strongly predicted subsequent anxiety, while both impulse regulation and social insecurity were strong predictors of subsequent somatization. The Neo-Ecological Milieu emerged as the most prevalent socio-demographic group (34.4% of participants). The Sinus-Milieus segmentation, however, did not significantly impact the health outcomes, suggesting consistent mental health issues across socio-demographic groups. Conclusions: This study's findings underscored the role of disordered eating attitudes in predicting mental health outcomes among young women with eating disorders. Addressing these attitudes in therapeutic settings may help mitigate symptoms of not only the primary condition but also depression, anxiety, and somatization.