469 resultados para Postpartum Depression


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OBJECTIVE: Depression has been identified as a priority disorder among children and adolescents. While numerous reviews have examined the individual and family factors that contribute to child and adolescent depressive symptoms, less is known about community-level risk and protective factors. The aim of this study was to complete a systematic review to identify community risk and protective factors for depression in school-aged children (4-18 years). METHOD: The review adopted the procedures recommended by the Cochrane Non-Randomised Studies Methods Working Group and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted to identify both observational and intervention study designs in both peer-reviewed and non-peer reviewed publications. RESULTS: A total of 21 studies met the inclusion criteria. Seventeen of the 18 community association studies and 2 of the 3 intervention studies reported one or more significant effects. Results indicated that community safety and community minority ethnicity and discrimination act as risk factors for depressive symptoms in school-aged children. Community disadvantage failed to achieve significance in meta-analytic results but findings suggest that the role of disadvantage may be influenced by other factors. Community connectedness was also not directly associated with depressive symptoms. CONCLUSION: There is evidence that a number of potentially modifiable community-level risk and protective factors influence child and adolescent depressive symptoms suggesting the importance of continuing research and intervention efforts at the community-level.

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AIMS: This aim of this study was to obtain a consensus from clinicians regarding occupational therapy for people with depression, for the assessments and practices they use that are not currently supported by research evidence directly related to functional performance. The study also aimed to discover how many of these assessments and practices were currently supported by research evidence.

METHODS: Following a previously reported systematic review of assessments and practices used in occupational therapy for people with depression, a modified nominal group technique was used to discover which assessments and practices occupational therapists currently utilize. Three online surveys gathered initial data on therapeutic options (survey 1), which were then ranked (survey 2) and re-ranked (survey 3) to gain the final consensus. Twelve therapists completed the first survey, whilst 10 clinicians completed both the second and third surveys.

MAJOR FINDINGS: Only 30% of the assessments and practices identified by the clinicians were supported by research evidence. A consensus was obtained on a total of 35 other assessments and interventions. These included both occupational-therapy-specific and generic assessments and interventions. Principle conclusion. Very few of the assessments and interventions identified were supported by research evidence directly related to functional performance. While a large number of options were generated, the majority of these were not occupational therapy specific.

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A single imaging gene-environment (IGxE) framework that is able to simultaneously model genetic, neurobiological, and environmental influences on psychopathology outcomes is needed to improve understanding of how complex interrelationships between allelic variation, differences in neuroanatomy or neuroactivity, and environmental experience affect risk for psychiatric disorder. In a longitudinal study of adolescent development we demonstrate the utility of such an IGxE framework by testing whether variation in parental behavior at age 12 altered the strength of an imaging genetics pathway, involving an indirect association between allelic variation in the serotonin transporter gene to variation in hippocampal volume and consequent onset of major depressive disorder by age 18. Results were consistent with the presence of an indirect effect of the serotonin transporter S-allele on depression onset via smaller left and right hippocampal volumes that was significant only in family environments involving either higher levels of parental aggression or lower levels of positive parenting. The previously reported finding of S-allele carriers' increased risk of depression in adverse environments may, therefore, be partly because of the effects of these environments on a neurobiological pathway from the serotonin transporter gene to depression onset that proceeds through variation in hippocampal volume. 

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PURPOSE: This study explores the depression literacy in adolescents in South Africa. METHOD: A semi-structured questionnaire was administered to 2,050 students from disadvantaged secondary schools in Johannesburg region. RESULT: A total of 90.9% reported depression as an illness, and 41.4% considered it a sign of weakness. Parents and siblings followed by friends and teachers were the preferred support options. The indicators of depression identified were socialisation pattern changes (24.6%), sad mood (23.6%), sleeping and eating pattern changes (18.3%), irritable behaviour (12.5%) and other health risk behaviours (9.7%). CONCLUSION: The majority considered depression an illness. An improvement in adolescent mental health literacy will increase access to help when needed.

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OBJECTIVES: There has been limited research examining how organizational factors are associated with the level of confidence of residential aged care staff in managing both residents' depression and the behavioural and psychological symptoms of residents with dementia (BPSD). This study investigated this issue. METHOD: A cross-sectional study design was employed. In total, 255 aged care staff (131 senior staff, 124 junior staff) from 21 residential care facilities participated in the study. All staff completed measures of self-efficacy in managing BPSD as well as confidence in working with older people with depression. They also completed measures of organizational climate (autonomy, cohesion, trust, pressure, support, recognition, fairness and encouragement of innovation) and measures of workplace experience (job role, number of years working in aged care facilities), job stress and satisfaction, and knowledge of depression. RESULTS: The results demonstrated that autonomy, trust, support, and job stress were associated with confidence in managing BPSD, while the factors related to confidence in managing depression were autonomy, support, job stress, job satisfaction, and knowledge of depression. CONCLUSION: These findings highlight that organizational climate factors need to be addressed in order to increase staff confidence in managing BPSD and depression. In particular, the findings demonstrate the importance of fostering organizational environments in which autonomy is promoted and there is support and cooperation among aged care staff. Attention to these factors is likely to increase the confidence of staff as they carry out their carer role.

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Background: Postnatal depression is a serious illness in new mothers. In the general population, physical activity (PA) has been found to reduce the risk of depression, whilst sedentary behaviour (SB; in particular television viewing) has been linked to higher levels of depressive symptoms, yet little is known regarding associations between PA, SB and postnatal depression. This study aimed to investigate associations between PA, television viewing and postnatal depressive symptoms in healthy primiparous mothers.. Methods: Cross-sectional survey data were provided by 406 first-time mothers (approximately 3-months postpartum) enrolled in the Melbourne InFANT Extend trial (2012/2013). Women self-reported PA (time spent walking for leisure and transport, and other moderate and vigorous PA), television viewing, and depressive symptoms (CES-D 10). Random intercept linear models examined associations between PA, television viewing and depressive symptoms. Results: In crude models total PA was inversely associated with risk of postnatal depressive symptoms (B = -0.122; 95% CI = -0.24, -0.01). In models adjusted for key sociodemographic and behavioural covariates the association did not remain statistically significant. No other associations between PA, television viewing and postnatal depressive symptoms were evident.. Conclusions: Postnatal depressive symptoms may not be related to PA and television viewing in the same way that these behaviours predict depressive symptoms in the general population. Further investigation of the specific domains of PA, as well as different types/contexts of SB and their respective associations with postnatal depressive symptoms is warranted in order to better inform development of targeted interventions aimed at enhancing postnatal mental health..

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The present investigation aims to identify the factors which differentiate violent from non-violent juvenile offenders, with a particular emphasis on the association between internalizing psychiatric morbidity (i.e. anxiety and depression), impulsivity, substance misuse, and violence. A total of 323 incarcerated male juvenile offenders from one of three Youth Detention Centers (YDCs) in China were recruited between August 2007 and November 2008. Interviews were conducted by trained psychiatrists using the Barratt Impulsivity Scale (BIS-11), the Screen for Child Anxiety Related Emotional Disorders (SCARED), and the Birleson Depression Self-Rating Scale (DSRS) to assess impulsivity, anxiety and depression, respectively. The Schedule for Affective Disorder and Schizophrenia for School-Age Children Present and Lifetime (K-SADS-PL) was also used to assess psychiatric diagnoses. Violent offenders had significantly higher BIS-11 total scores, and attention and nonplanning subscale scores (p<0.05). In the multiple logistic regression model, substance use disorders (SUD) and BIS-11 total scores independently predicted violence. Prison-based treatment services designed to reduce impulsivity and substance misuse in juvenile detention facilities should be prioritized.

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BACKGROUND: Numerous health benefits are associated with achieving optimal diet and physical activity behaviours during and after pregnancy. Understanding predictors of these behaviours is an important public health consideration, yet little is known regarding associations between clinician advice and diet and physical activity behaviours in postpartum women. The aims of this study were to compare the frequency of dietary and physical activity advice provided by clinicians during and after pregnancy and assess if this advice is associated with postpartum diet and physical activity behaviours.

METHODS: First time mothers (n = 448) enrolled in the Melbourne InFANT Extend trial completed the Cancer Council of Australia's Food Frequency Questionnaire when they were three to four months postpartum, which assessed usual fruit and vegetable intake (serves/day). Total physical activity time, time spent walking and time in both moderate and vigorous activity for the previous week (min/week) were assessed using the Active Australia Survey. Advice received during and following pregnancy were assessed by separate survey items, which asked whether a healthcare practitioner had discussed eating a healthy diet and being physically active. Linear and logistic regression assessed associations of advice with dietary intake and physical activity.

RESULTS: In total, 8.6 % of women met guidelines for combined fruit and vegetable intake. Overall, mean total physical activity time was 350.9 ± 281.1 min/week. Time spent walking (251.97 ± 196.78 min/week), was greater than time spent in moderate (36.68 ± 88.58 min/week) or vigorous activity (61.74 ± 109.96 min/week) and 63.2 % of women were meeting physical activity recommendations. The majority of women reported they received advice regarding healthy eating (87.1 %) and physical activity (82.8 %) during pregnancy. Fewer women reported receiving healthy eating (47.5 %) and physical activity (51.9 %) advice by three months postpartum. There was no significant association found between provision of dietary and/or physical activity advice, and mother's dietary intakes or physical activity levels.

CONCLUSIONS: Healthy diet and physical activity advice was received less after pregnancy than during pregnancy yet no association between receipt of advice and behaviour was observed. More intensive approaches than provision of advice may be required to promote healthy diet and physical activity behaviours in new mothers.

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BACKGROUND: Depression is widely considered to be an independent and robust predictor of Coronary Heart Disease (CHD), however is seldom considered in the context of formal risk assessment. We assessed whether the addition of depression to the Framingham Risk Equation (FRE) improved accuracy for predicting 10-year CHD in a sample of women.

DESIGN: A prospective, longitudinal design comprising an age-stratified, population-based sample of Australian women collected between 1993 and 2011 (n=862).

METHODS: Clinical depressive disorder was assessed using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID-I/NP), using retrospective age-of-onset data. A composite measure of CHD included non-fatal myocardial infarction, unstable angina coronary intervention or cardiac death. Cox proportional-hazards regression models were conducted and overall accuracy assessed using area under receiver operating characteristic (ROC) curve analysis.

RESULTS: ROC curve analyses revealed that the addition of baseline depression status to the FRE model improved its overall accuracy (AUC:0.77, Specificity:0.70, Sensitivity:0.75) when compared to the original FRE model (AUC:0.75, Specificity:0.73, Sensitivity:0.67). However, when calibrated against the original model, the predicted number of events generated by the augmented version marginally over-estimated the true number observed.

CONCLUSIONS: The addition of a depression variable to the FRE equation improves the overall accuracy of the model for predicting 10-year CHD events in women, however may over-estimate the number of events that actually occur. This model now requires validation in larger samples as it could form a new CHD risk equation for women.

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BACKGROUND: According to a recent position paper by the American Heart Association, it remains unclear whether depression is a risk factor for incident Coronary Heart Disease (CHD). We assessed whether a depressive disorder independently predicts 18-year incident CHD in women. METHOD: A prospective longitudinal study of 860 women enrolled in the Geelong Osteoporosis Study (1993-2011) was conducted. Participants were derived from an age-stratified, representative sample of women (20-94 years) randomly selected from electoral rolls in South-Eastern Australia. The exposure was a diagnosis of a depressive disorder using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders. Outcomes data were collected from hospital medical records: (1) Primary outcome: a composite measure of cardiac death, non-fatal Myocardial Infarction or coronary intervention. (2) Secondary outcome: any cardiac event (un/stable angina, cardiac event not otherwise defined) occurring over the study period. RESULTS: Seven participants were excluded based on CHD history. Eighty-three participants (9.6%) recorded ≥1 cardiac event over the study period; 47 had a diagnosis that met criteria for inclusion in the primary analysis. Baseline depression predicted 18-year incidence, adjusting for (1) anxiety (adj. OR:2.39; 95% CIs:1.19-4.82), plus (2) typical risk factors (adj. OR:3.22; 95% CIs:1.45-6.93), plus (3) atypical risk factors (adj. OR:3.28; 95% CIs:1.36-7.90). This relationship held when including all cardiac events. No relationship was observed between depression and recurrent cardiac events. CONCLUSION: The results of this study support the contention that depression is an independent risk factor for CHD incidence in women. Moreover, the strength of association between depression and CHD incidence was of a greater magnitude than any typical and atypical risk factor.

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BACKGROUND: Little is known about predictors of recovery from bipolar depression. AIMS: We investigated affective instability (a pattern of frequent and large mood shifts over time) as a predictor of recovery from episodes of bipolar depression and as a moderator of response to psychosocial treatment for acute depression. METHOD: A total of 252 out-patients with DSM-IV bipolar I or II disorder and who were depressed enrolled in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) and were randomised to one of three types of intensive psychotherapy for depression (n = 141) or a brief psychoeducational intervention (n = 111). All analyses were by intention-to-treat. RESULTS: Degree of instability of symptoms of depression and mania predicted a lower likelihood of recovery and longer time until recovery, independent of the concurrent effects of symptom severity. Affective instability did not moderate the effects of psychosocial treatment on recovery from depression. CONCLUSIONS: Affective instability may be a clinically relevant characteristic that influences the course of bipolar depression.

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BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study.

METHODS: The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators.

RESULTS: After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001).

CONCLUSION: The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

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Mental illness has a deep impact on individuals, families, and by extension, society as a whole. Social networks allow individuals with mental disorders to communicate with others sufferers via online communities, providing an invaluable resource for studies on textual signs of psychological health problems. Mental disorders often occur in combinations, e.g., a patient with an anxiety disorder may also develop depression. This co-occurring mental health condition provides the focus for our work on classifying online communities with an interest in depression. For this, we have crawled a large body of 620,000 posts made by 80,000 users in 247 online communities. We have extracted the topics and psycho-linguistic features expressed in the posts, using these as inputs to our model. Following a machine learning technique, we have formulated a joint modelling framework in order to classify mental health-related co-occurring online communities from these features. Finally, we performed empirical validation of the model on the crawled dataset where our model outperforms recent state-of-the-art baselines.