Mental health interventions and future major depression among primary care patients with subthreshold depression

Development and validation of a prediction score to assess the risk of depression in primary care

BACKGROUND

Major depression is the most frequent psychiatric disorder and primary care is a crucial setting for its early recognition. This study aimed to develop and validate the DEP-HScore as a tool to predict depression risk in primary care and increase awareness and investigation of this condition among General Practitioners (GPs).

METHODS

The DEP-HScore was developed using data from the Italian Health Search Database (HSD). A cohort of 903,748 patients aged 18 years or older was selected and followed until the occurrence of depression, death or end of data availability (December 2019). Demographics, somatic signs/symptoms and psychiatric/medical comorbidities were entered in a multivariate Cox regression to predict the occurrence of depression. The coefficients formed the DEP-HScore for individual patients. Explained variance (pseudo-R2), discrimination (AUC) and calibration (slope estimating predicted-observed risk relationship) assessed the prediction accuracy.

RESULTS

The DEP-HScore explained 18.1 % of the variation in occurrence of depression and the discrimination value was equal to 67 %. With an event horizon of three months, the slope and intercept were not significantly different from the ideal calibration.

LIMITATIONS

The DEP-HScore has not been tested in other settings. Furthermore, the model was characterized by limited calibration performance when the risk of depression was estimated at the 1-year follow-up.

CONCLUSIONS

The DEP-HScore is reliable tool that could be implemented in primary care settings to evaluate the risk of depression, thus enabling prompt and suitable investigations to verify the presence of this condition.

Using machine learning to forecast symptom changes among subclinical depression patients receiving stepped care or usual care

BACKGROUND

Subclinical depression (SD) is a mental health disorder characterized by minor depressive symptoms. Most SD patients are treated in the primary practice, but many respond poorly to treatment at the expense of provider resources. Stepped care approaches are appealing for tiering SD care to efficiently allocate scarce resources while jointly optimizing patient outcomes. However, stepped care can be time inefficient, as some persons may respond poorly and be forced to suffer with their symptoms for prolonged periods. Machine learning can offer insight into optimal treatment paths and inform clinical recommendations for incident patients.

METHODS

As part of the Step-Dep trial, participants with SD were randomized to receive stepped care (N=96) or usual care (N=140). Machine learning was used to predict changes in depressive symptoms every three months over a year for each treatment group.

RESULTS

Tree-based models were effective in predicting PHQ-9 changes among patients who received stepped care (r=0.35-0.46, MAE=0.14-0.17) and usual care (r=0.34-0.49, MAE=0.15-0.18). Patients who received stepped care were more likely to reduce PHQ-9 scores if they had high PHQ-9 but low HADS-A scores at baseline, a low number of chronic illnesses, and an internal locus of control.

LIMITATIONS

Models may suffer from potential overfitting due to sample size limitations.

CONCLUSION

Our findings demonstrate the promise of machine learning for predicting changes in depressive symptoms for SD patients receiving different treatments. Trained models can intake incident patient information and predict outcomes to inform personalized care.

Predictive potential of somatic symptoms for the identification of subthreshold depression and major depressive disorder in primary care settings

BACKGROUND

The presence of heterogenous somatic symptoms frequently obscures the recognition of depression in primary care. We aimed to explore the association between somatic symptoms and subthreshold depression (SD) and Major Depressive Disorder (MDD), as well as to determine the predictive potential of somatic symptoms in identifying SD and MDD in primary care.

METHODS

Data were derived from the Depression Cohort in China study (ChiCTR registry number: 1900022145). The Patient Health Questionnaire-9 (PHQ-9) was used to assess SD by trained general practitioners (GPs), and the Mini International Neuropsychiatric Interview depression module was used to diagnose MDD by professional psychiatrists. Somatic symptoms were assessed using the 28-item Somatic Symptoms Inventory (SSI).

RESULTS

In total of 4,139 participants aged 18-64 years recruited from 34 primary health care settings were included. The prevalence of all 28 somatic symptoms increased in a dose-dependent manner from non-depressed controls to SD, and to MDD (P for trend <0.001). Hierarchical clustering analysis grouped the 28 heterogeneous somatic symptoms into three clusters (Cluster 1: energy-related symptoms, Cluster 2: vegetative symptoms, and Cluster 3: muscle, joint, and central nervous symptoms). Following adjustment for potential confounders and the other two clusters of symptoms, per 1 increase of energy-related symptoms exhibited significant association with SD (OR = 1.24, 95% CI, 1.18-1.31) and MDD (OR = 1.50, 95% CI, 1.41-1.60) The predictive performance of energy-related symptoms in identifying individuals with SD (AUC = 0.715, 95% CI, 0.697-0.732) and MDD (AUC = 0.941, 95% CI, 0.926-0.963) was superior to the performance of total SSI and the other two clusters (P < 0.05).

CONCLUSIONS

Somatic symptoms were associated with the presence of SD and MDD. In addition, somatic symptoms, notably those related to energy, showed good predictive potential in identifying SD and MDD in primary care. The clinical implication of the present study is that GPs should consider the closely related somatic symptoms for early recognition for depression in practice.

Patient reported self-help strategies and the perceived benefits for managing sub-threshold depressive symptoms: A nested qualitative study of Australian primary care attendees

BACKGROUND

Subthreshold depression is common in primary care, but there is little information about the self-help strategies that patients use and the perceived benefits of these.

AIM

This study sought to elicit the self-help strategies that primary care attendees identified as beneficial for the self-management of subthreshold depressive symptoms and the implications for general practitioners.

METHOD

Semi-structured telephone interviews were conducted with 14 people (April-May 2017) from the Target-D randomised controlled trial (RCT). Target-D investigated whether using a patient-centred clinical prediction tool and an e-health platform to match mental health management options to prognosis was beneficial for improving depressive symptoms at 3 months compared to usual care. Interviews were thematically analysed to identify self-help strategies and their perceived benefits.

RESULTS

Four overarching domains for the self-management strategies were identified: social, cognitive, behavioural and restorative. Interviewees reported using strategies across multiple domains, which included undertaking enjoyable, immersive activities, that provided relief from automatic negative thoughts and had a perceived cognitive benefit. Differences in the perceived sense of agency were noted around the self-regulation of mood, which indicated more explicit direction to patient-identified self-help management strategies by general practitioners for some may be of benefit in routine care.

CONCLUSION

Some of the reported self-management strategies aligned with evidence-based approaches such as physical activity and mindfulness for mental health symptom management. These findings can inform low-intensity interventions within stepped care models for mental health in primary care, social prescribing models and, help to guide the management of patients by GPs for subthreshold depression.

The prevalence of subthreshold psychiatric symptoms and associations with alcohol and substance use disorders: from a nationally representative survey of 36,309 adults

BACKGROUND

Our aim was to describe a broad number of subthreshold psychiatric symptoms (SPS) in a nationally representative population and evaluate associations with substance use. SPS describe groups of symptoms with significant pathology, but that do not quite meet full psychiatric diagnostic criteria. They have been associated with significant impairment and cost.

METHODS

The National Epidemiologic Survey on Alcohol and Related Conditions-III was a multistage, weighted, cross-sectional survey completed in the United States in 2013 comprising 36,309 noninstitutionalized adults. We report lifetime prevalence rates of 14 SPS related to mood, anxiety, trauma, eating, and personality disorders. We then evaluate associations with lifetime alcohol use disorders (AUD) and all substance use disorders (SUD) using logistic regression and adjusted odds ratios. SPS and psychiatric diagnoses were mutually exclusive (could not co-occur).

RESULTS

Lifetime prevalence of having at least one of 14 SPS was 57% compared with 37% for the related psychiatric disorders. This was similar for males and females, in contrast to psychiatric disorders in which prevalence was 42% in females and 31% in males. Otherwise, overall SPS and disorders had similar prevalence patterns across sociodemographic characteristics. Subthreshold personality symptoms had the highest prevalence rates (schizotypal 21.3%, antisocial 18.3%, and borderline 17.6%), followed by posttraumatic stress (13.1%). Subthreshold bipolar and depression had lifetime prevalence rates of 2.7 and 8.5%, respectively. Prevalence rates of subthreshold anxiety symptoms ranged from 2.2% (agoraphobia) to 9.8% (specific phobia). Subthreshold eating disorder related symptoms had the lowest prevalence rates (anorexia 1.5% and bulimia 1.7%). Half (seven) of the SPS had significantly increased odds of lifetime AUD. This number increased to 12 for all SUD. Subthreshold antisocial personality symptoms had the highest odds of AUD (2.2; 95% CI 2.00-2.37) and SUD (3.5; 95% CI 3.22-3.81).

CONCLUSIONS

We found high lifetime SPS prevalence rates and significant associations with AUD and SUD. To our knowledge, this is the first published study evaluating a broad number of SPS. This indicates possible opportunities for early intervention and prevention but requires additional research and development of infrastructure and guidelines to better understand and manage patients who experience SPS.

Can increased cognitive load help people with subthreshold depression to forget negative information?

BACKGROUND

Given that major depression is a global public health problem, and that sub-threshold depression (SD) has been shown to be a significant risk indicator of major depression disorder, the awareness of SD interventions has increased. The current study explored the effect of increasing cognitive load on the forgetting of unwanted and negative memories of sub-threshold depression individuals (SDs) (Study 1) and proposed a cognitive load intervention (CLI) (study 2).

METHODS

53 SDs and 52 normal participants were recruited to explore the effect of cognitive load on the directed forgetting of negative items (Study 1). The treatment effect of CLI on 62 SDs was investigated. SDs completed up to 8 CLI/control sessions over an 8-week period while regularly recording their depression symptoms (Study 2).

RESULTS

The results showed that it is more difficult for SDs to forget negative 'to-be-forgotten' items than normal controls (F (1, 99) = 27.98, p < 0.001, η² = 0.22). In study 1, increasing cognitive load promoted directed forgetting for negative items in SDs. Study 2 showed that there were significant reductions in depression symptoms of SDs over the 8-week CLI (e.g. BDI-Ⅱ scores: F (1, 60) = 99.93, p < 0.001, η² = 0.63).

LIMITATIONS

Small sample size and lack of verification by neuroimaging may limit the generalizability of these results.

CONCLUSIONS

The study revealed that increasing cognitive load can promote SDs to forget negative information, while the CLI project effectively reduced the depression level of SDs, thus providing encouraging initial support for its use in the treatment of SD.

Diagnostic accuracy of depression questionnaires in adult patients with diabetes: A systematic review and meta-analysis

BACKGROUND

Comorbid depression is common among patients with diabetes and has severe health consequences, but often remains unrecognized. Several questionnaires are used to screen for depression. A systematic review and meta-analysis regarding the diagnostic accuracy of depression questionnaires in adults with diabetes is unavailable. Our aim was to conduct a systematic review and meta-analysis to evaluate the diagnostic accuracy of depression questionnaires in adults with type 1 or type 2 diabetes.

METHODS

PubMed, Embase and PsycINFO were searched from inception to 28 February 2018. Studies were included when the diagnostic accuracy of depression questionnaires was assessed in a diabetes population and the reference standard was a clinical interview. Data extraction was performed by one reviewer and checked by another. Two reviewers independently conducted the quality assessment (QUADAS-2). Diagnostic accuracy was pooled in bivariate random effects models. The main outcome was diagnostic accuracy, expressed as sensitivity and specificity, of depression questionnaires in an adult diabetes population. This study is reported according to PRISMA-DTA and is registered with PROSPERO (CRD42018092950).

RESULTS

A total 6,097 peer-reviewed articles were screened. Twenty-one studies (N = 5,703 patients) met the inclusion criteria for the systematic review. Twelve different depression questionnaires were identified, of which the CES-D (n = 6 studies) and PHQ-9 (n = 7 studies) were the most frequently evaluated. Risk of bias was unclear for multiple domains in the majority of studies. In the meta-analyses, five (N = 1,228) studies of the CES-D (≥16), five (N = 1,642) of the PHQ-9 (≥10) and four (N = 822) of the algorithm of the PHQ-9 were included in the pooled analysis. The CES-D (≥16) had a pooled sensitivity of 85.0% (95%CI, 71.3-92.8%) and a specificity of 71.6% (95%CI, 62.5-79.2%); the PHQ-9 (≥10) had a sensitivity of 81.5% (95%CI, 57.1-93.5%) and a specificity of 79.7% (95%CI, 62.1-90.4%). The algorithm for the PHQ-9 had a sensitivity of 60.9% (95%CI, 52.3-90.8%) and a specificity of 64.0% (95%CI, 53.0-93.9%).

CONCLUSIONS

This review indicates that the CES-D had the highest sensitivity, whereas the PHQ-9 had the highest specificity, although confidence intervals were wide and overlapping. The algorithm for the PHQ-9 had the lowest sensitivity and specificity. Given the variance in results and suboptimal reporting of studies, further high quality studies are needed to confirm the diagnostic accuracy of these depression questionnaires in patients with diabetes.

Childhood adversities, negative life events and outcomes of non-pharmacological treatments for depression in primary care: A secondary analysis of a randomized controlled trial

Non-pharmacological treatments for depression are effective and available in primary care, but useful prognostic factors are lacking. Childhood adversities (CA) and negative recent life events (RLE) increase the risk and severity of depression, though their effect on treatment outcomes remains understudied. Using a sample of 737 adult participants of a multicenter randomized controlled trial receiving physical exercise, internet based cognitive-behavioral therapy or treatment as usual, alone or in combination with antidepressants, this prospective study aimed to determine the impact of CA, RLE and their interaction as predictors of outcomes of non-pharmacological treatments for mild-moderate depression in primary care. Outcomes were depression severity (MADRS score) and response to treatment (≥50% reduction in MADRS score) after three months. Linear regression and modified Poisson regression were used, interaction was assessed with a product term (CA*RLE) and epidemiological measures of interaction. The number of CA and RLE were associated with higher depression severity at follow-up (CA: β = 0.79, 95% CI: 0.14 to 1.44 and RLE: β = 0.52, 95% CI: 0.14 to 0.72) and showed a trend towards lower rates of response to treatment (RR = 0.94, 95% CI: 0.86 to 1.03; and RLE: RR = 0.95, 95% CI: 0.90 to 0.99). Interaction between CA and RLE was not significant for depression severity (β = 0.10, 95% CI: -2.12 to 0.41) nor for response to treatment (RERI = -0.05, 95% CI = -0.33 to 0.24). CA and RLE are associated with worse outcomes of non-pharmacological treatments in primary care. Further studies to identify predictors of outcomes of non-pharmaological treatments for depression are needed.

The risk of developing major depression among individuals with subthreshold depression: a systematic review and meta-analysis of longitudinal cohort studies

BACKGROUND

Studies have consistently shown that subthreshold depression is associated with an increased risk of developing major depression. However, no study has yet calculated a pooled estimate that quantifies the magnitude of this risk across multiple studies.

METHODS

We conducted a systematic review to identify longitudinal cohort studies containing data on the association between subthreshold depression and future major depression. A baseline meta-analysis was conducted using the inverse variance heterogeneity method to calculate the incidence rate ratio (IRR) of major depression among people with subthreshold depression relative to non-depressed controls. Subgroup analyses were conducted to investigate whether IRR estimates differed between studies categorised by age group or sample type. Sensitivity analyses were also conducted to test the robustness of baseline results to several sources of study heterogeneity, such as the case definition for subthreshold depression.

RESULTS

Data from 16 studies (n = 67 318) revealed that people with subthreshold depression had an increased risk of developing major depression (IRR = 1.95, 95% confidence interval 1.28-2.97). Subgroup analyses estimated similar IRRs for different age groups (youth, adults and the elderly) and sample types (community-based and primary care). Sensitivity analyses demonstrated that baseline results were robust to different sources of study heterogeneity.

CONCLUSION

The results of this study support the scaling up of effective indicated prevention interventions for people with subthreshold depression, regardless of age group or setting.

Patients' and practice nurses' perceptions of depression in patients with type 2 diabetes and/or coronary heart disease screened for subthreshold depression

BACKGROUND

Comorbid depression is common in patients with type 2 diabetes (DM2) and/or coronary heart disease (CHD) and is associated with poor quality of life and adverse health outcomes. However, little is known about patients' and practice nurses' (PNs) perceptions of depression. Tailoring care to these perceptions may affect depression detection and patient engagement with treatment and prevention programs. This study aimed to explore patients' and PNs' perceptions of depression in patients with DM2/CHD screened for subthreshold depression.

METHODS

A qualitative study was conducted as part of a Dutch stepped-care prevention project. Using a purposive sampling strategy, data were collected through semi-structured interviews with 15 patients and 9 PNs. After consent, all interviews were recorded, transcribed verbatim and analyzed independently by two researchers with Atlas.ti.5.7.1 software. The patient and PN datasets were inspected for commonalities using a constant comparative method, from which a final thematic framework was generated.

RESULTS

Main themes were: illness perception, need for care and causes of depression. Patients generally considered themselves at least mildly depressed, but perceived severity levels were not always congruent with Patient Health Questionnaire 9 scores at inclusion. Initially recognizing or naming their mental state as a (subthreshold) depression was difficult for some. Having trouble sleeping was frequently experienced as the most burdensome symptom. Most experienced a need for care; psycho-educational advice and talking therapy were preferred. Perceived symptom severity corresponded with perceived need for care, but did not necessarily match help-seeking behaviour. Main named barriers to help-seeking were experienced stigma and lack of awareness of depression and mental health care possibilities. PNs frequently perceived patients as not depressed and with minimal need for specific care except for attention. Participants pointed to a mix of causes of depression, most related to negative life events and circumstances and perceived indirect links with DM2/CHD.

CONCLUSION

Data of the interviewed patients and PNs suggest that they have different perceptions about (subthreshold) depressive illness and the need for care, although views on its causes seem to overlap more.

Two-year effectiveness of a stepped-care depression prevention intervention and predictors of incident depression in primary care patients with diabetes type 2 and/or coronary heart disease and subthreshold depression: data from the Step-Dep cluster randomised controlled trial

INTRODUCTION

Major depressive disorders (MDD), diabetes mellitus type 2 (DM2) and coronary heart disease (CHD) are leading contributors to the global burden of disease and often co-occur.

OBJECTIVES

To evaluate the 2-year effectiveness of a stepped-care intervention to prevent MDD compared with usual care and to develop a prediction model for incident depression in patients with DM2 and/or CHD with subthreshold depression.

METHODS

Data of 236 Dutch primary care patients with DM2/CHD with subthreshold depression (Patient Health Questionnaire 9 (PHQ-9) score ≥6, no current MDD according to the Mini International Neuropsychiatric Interview (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria)) who participated in the Step-Dep trial were used. A PHQ-9 score of ≥10 at minimally one measurement during follow-up (at 3, 6, 9, 12 and 24 months) was used to determine the cumulative incidence of MDD. Potential demographic and psychological predictors were measured at baseline via web-based self-reported questionnaires and evaluated using a multivariable logistic regression model. Model performance was assessed with the Hosmer-Lemeshow test, Nagelkerke's R² explained variance and area under the receiver operating characteristic curve (AUC). Bootstrapping techniques were used to internally validate our model.

RESULTS

192 patients (81%) were available at 2-year follow-up. The cumulative incidence of MDD was 97/192 (51%). There was no statistically significant overall treatment effect over 24 months of the intervention (OR 1.37; 95% CI 0.52 to 3.55). Baseline levels of anxiety, depression, the presence of >3 chronic diseases and stressful life events predicted the incidence of MDD (AUC 0.80, IQR 0.79-0.80; Nagelkerke's R² 0.34, IQR 0.33-0.36).

CONCLUSION

A model with 4 factors predicted depression incidence during 2-year follow-up in patients with DM2/CHD accurately, based on the AUC. The Step-Dep intervention did not influence the incidence of MDD. Future depression prevention programmes should target patients with these 4 predictors present, and aim to reduce both anxiety and depressive symptoms.

TRIAL REGISTRATION NUMBER

NTR3715.

Development of a Mobile Clinical Prediction Tool to Estimate Future Depression Severity and Guide Treatment in Primary Care: User-Centered Design

Background

Around the world, depression is both under- and overtreated. The diamond clinical prediction tool was developed to assist with appropriate treatment allocation by estimating the 3-month prognosis among people with current depressive symptoms. Delivering clinical prediction tools in a way that will enhance their uptake in routine clinical practice remains challenging; however, mobile apps show promise in this respect. To increase the likelihood that an app-delivered clinical prediction tool can be successfully incorporated into clinical practice, it is important to involve end users in the app design process.

Objective

The aim of the study was to maximize patient engagement in an app designed to improve treatment allocation for depression.

Methods

An iterative, user-centered design process was employed. Qualitative data were collected via 2 focus groups with a community sample (n=17) and 7 semistructured interviews with people with depressive symptoms. The results of the focus groups and interviews were used by the computer engineering team to modify subsequent protoypes of the app.

Results

Iterative development resulted in 3 prototypes and a final app. The areas requiring the most substantial changes following end-user input were related to the iconography used and the way that feedback was provided. In particular, communicating risk of future depressive symptoms proved difficult; these messages were consistently misinterpreted and negatively viewed and were ultimately removed. All participants felt positively about seeing their results summarized after completion of the clinical prediction tool, but there was a need for a personalized treatment recommendation made in conjunction with a consultation with a health professional.

Conclusions

User-centered design led to valuable improvements in the content and design of an app designed to improve allocation of and engagement in depression treatment. Iterative design allowed us to develop a tool that allows users to feel hope, engage in self-reflection, and motivate them to treatment. The tool is currently being evaluated in a randomized controlled trial.

A Review on the General Stability of Mood Disorder Diagnoses Along the Lifetime

PURPOSE OF REVIEW

The purpose of this review is to review the most recent literature regarding diagnostic stability of mood disorders, focusing on epidemiological, clinical-psychopathological, and neurobiological data for unipolar and bipolar affective disorders.

RECENT FINDINGS

Unipolar depression follows a chronic course in at least half of all cases and presents a considerable diagnostic stability across all age ranges. Studies using latent class analysis are allowing improved profiling of depressive subtypes and assessment of their prevalence. Advances have been made in our understanding of the neurobiological underpinnings of depression, with data highlighting the roles of amyloid deposits, the ApoE4 allele, and atrophy of the anterior hippocampus or frontal cortex. The diagnostic instability of bipolar disorder is manifest in the early years, seen in both the extent of diagnostic delay and the high rate of diagnostic conversion from unipolar depression. Regarding disruptive mood dysregulation disorder, we have little data to date, but those which exist indicate a high rate of comorbidity and minimal diagnostic stability for this disorder. Diagnostic stability varies substantially among mood disorders, which would be related to the validity of current diagnostic categories and our diagnostic accuracy.

Development of a prognostic model for predicting depression severity in adult primary patients with depressive symptoms using the diamond longitudinal study

BACKGROUND

Depression trajectories among primary care patients are highly variable, making it difficult to identify patients that require intensive treatments or those that are likely to spontaneously remit. Currently, there are no easily implementable tools clinicians can use to stratify patients with depressive symptoms into different treatments according to their likely depression trajectory. We aimed to develop a prognostic tool to predict future depression severity among primary care patients with current depressive symptoms at three months.

METHODS

Patient-reported data from the diamond study, a prospective cohort of 593 primary care patients with depressive symptoms attending 30 Australian general practices. Participants responded affirmatively to at least one of the first two PHQ-9 items. Twenty predictors were pre-selected by expert consensus based on reliability, ease of administration, likely patient acceptability, and international applicability. Multivariable mixed effects linear regression was used to build the model.

RESULTS

The prognostic model included eight baseline predictors: sex, depressive symptoms, anxiety, history of depression, self-rated health, chronic physical illness, living alone, and perceived ability to manage on available income. Discrimination (c-statistic =0.74; 95% CI: 0.70-0.78) and calibration (agreement between predicted and observed symptom scores) were acceptable and comparable to other prognostic models in primary care.

LIMITATIONS

More complex model was not feasible because of modest sample size. Validation studies needed to confirm model performance in new primary care attendees.

CONCLUSION

A brief, easily administered algorithm predicting the severity of depressive symptoms has potential to assist clinicians to tailor treatment for adult primary care patients with current depressive symptoms.

Effectiveness of a stepped-care intervention to prevent major depression in patients with type 2 diabetes mellitus and/or coronary heart disease and subthreshold depression: A pragmatic cluster randomized controlled trial

Purpose

Given the public health significance of poorly treatable co-morbid major depressive disorders (MDD) among patients with type 2 diabetes mellitus (DM2) and coronary heart disease (CHD), we need to investigate whether strategies to prevent the development of major depression could reduce its burden of disease. We therefore evaluated the effectiveness of a stepped-care program for subthreshold depression in comparison with usual care in patients with DM2 and/or CHD.

Methods

A cluster randomized controlled trial, with 27 primary care centers serving as clusters. A total of 236 DM2 and/or CHD patients with subthreshold depression (nine item Patient Health Questionnaire (PHQ-9) score ≥ 6, no current MDD according to DSM-IV criteria) were allocated to the intervention group (N = 96) or usual care group (n = 140). The stepped-care program was delivered by trained practice nurses during one year and consisted of four sequential treatment steps: watchful waiting, guided self-help, problem solving treatment and referral to the general practitioner. The primary outcome was the 12-month cumulative incidence of MDD as measured with the Mini International Neuropsychiatric Interview (MINI). Secondary outcomes included severity of depression (measured by PHQ-9) at 3, 6, 9 and 12 months.

Results

Of 236 patients (mean age, 67,5 (SD 10) years; 54.7% men), 210 (89%) completed the MINI at 12 months. The cumulative incidence of MDD was 9 of 89 (10.1%) participants in the intervention group and 12 of 121 (9.9%) participants in the usual care group. We found no statistically significant overall effect of the intervention (OR = 1.21; 95% confidence interval (0.12 to 12.41)) and there were no statistically significant differences in the course or severity of depressive symptoms between the two groups.

Conclusions

This study suggest that Step-Dep was not more effective in preventing MDD than usual care in a primary care population with DM2 and/or CHD and subthreshold depression.

Identification of common words to improve self-confidence in Japanese students with subthreshold depression

Background Subthreshold depression (StD) is more common than major depressive disorder. Objective The study aimed to identify common words to improve self-confidence in Japanese university students with StD for developing a smartphone application to help those with StD. Methods In this cross-sectional study, words participants used to improve their self-confidence were gathered using self-report questionnaires in 154 university students in Japan. The words used to improve self-confidence were categorized using a computerized text analysis method based on the frequency of appearance. Results Participants were 154 male and females [StD group (n = 82) and healthy control (HC) group (n = 72); median age = 20 years]. A total of 290 words for improving self-confidence were identified. In the StD group, the keywords that appeared with the highest frequencies were "can", "let's try", "good luck", "able", and "don't worry". The keywords that occurred with the highest frequencies (the top eight) were common across both groups. The keywords were grouped into eight categories. The "encouragement" and "praise" categories were found in the responses of more than 80% of participants in both groups. Frequencies of the "determination" and "trust" categories were significantly higher in the StD group than in the HC group. Conclusions We conclude that "can", "let's try", and "good luck" are the most common words that Japanese students with StD use when describing how they improve their self-confidence. Future work will use these common words to develop a smartphone application to help those suffering from StD.

Effects of subclinical depression, anxiety and somatization on brain structure in healthy subjects

BACKGROUND

Dimensional approaches in highly prevalent psychiatric disorders like depression or anxiety could lead to a better understanding of pathogenesis and advantages in early detection and prevention. In an effort to better understand associations of brain structural variation across the depression/anxiety spectra, we investigated minor subclinical symptoms in a non-clinical healthy population.

METHODS

We studied 177 healthy subjects from the community, who underwent high-resolution T1-weighted 3T MRI and completed the symptom-checklist-90 (SCL-90-R). Using voxel-based morphometry (VBM) analysis with CAT12 software, we correlated SCL-90-R-subscales for depression, anxiety, and somatization with gray matter across the brain.

RESULTS

Significant positive gray matter correlations emerged across all three scales in different areas: the depression subscale correlated positively with gray matter in the Rolandic operculum, superior temporal gyrus (left) and postcentral gyrus (bilateral), the anxiety subscale correlated positively with middle temporal gyrus, Rolandic operculum, middle cingular gyrus and precuneus bilaterally, and the somatization subscale with left inferior prefrontal cortex. Somatization also showed negative correlations with cerebellar vermis and right supplementary motor area.

LIMITATIONS

Our study is limited to VBM and does not include surface-based measures. It also only contains subjects with very small psychological distress by partly overlapping symptoms.

CONCLUSION

Our findings are consistent with a non-linear relationship between symptom severity and cortical volume in several brain areas involved in both emotion regulation as well as altered in clinically manifest depressive/anxiety disorders.

Affective concordance in couples: a cross-sectional analysis of depression and anxiety consultations within a population of 13,507 couples in primary care

BACKGROUND

Depression and anxiety are common and have a significant impact on the individual and wider society. One theory proposed to explain a heightened risk for depression and anxiety is affective concordance in couples (e.g. influence of shared mood states, shared health beliefs). Whilst research has shown concordance for severe psychiatric illnesses and general mood in couples, little attention has been given to concordance for common psychiatric conditions such as depression and anxiety. The aims of this study were to test affective concordance in couples and examine potential influences on concordance.

METHODS

Study design is a 1-year cross-sectional study of anxiety and depression consultations in primary care. Data were obtained from a validated primary care database of recorded consultations. Outcome was the presence of an anxiety or depression Read Code (GP recorded reason for consultation) in the female (within the couple dyad), and exposure was a recorded Read Code of anxiety or depression in the male. Logistic regression was used to test associations with odds ratios (OR) and 95% confidence intervals (95% CI) reported. Statistical adjustment was carried out on potential influences of concordance; age, environment (deprivation), healthcare behaviour (consultation frequency), and comorbidity.

RESULTS

A population of 13,507 couples were identified in which 927 people consulted for anxiety and 538 for depression. Logistic regression showed a 3 times increase in odds of an anxiety consultation in females if their male partner had also consulted OR 2.98 (95% CI 2.15 to 4.13). For depression females were over 4 times the odds of consulting if their male partner had also consulted OR 4.45 (95% CI 2.79 to 7.09). Adjustment within a multivariable model showed some reduction in odds; concordant anxiety was reduced to 2.5 times odds OR 2.48 (95%CI 1.76 to 3.50) and depression reduced to OR 3.39 (2.07 to 5.54).

CONCLUSION

Results show significant associations for affective concordance in couples. Factors influencing concordance are comorbidity and environmental factors, however reasons for deciding to consult (positive or negative) are unknown. This study highlights the patients' social context as a factor in consultations for anxiety and depression and gives support to the consideration of the patient's household as an influence on mental health.

Impact of functional and structural social relationships on two year depression outcomes: A multivariate analysis

BACKGROUND

High rates of persistent depression highlight the need to identify the risk factors associated with poor depression outcomes and to provide targeted interventions to people at high risk. Although social relationships have been implicated in depression course, interventions targeting social relationships have been disappointing. Possibly, interventions have targeted the wrong elements of relationships. Alternatively, the statistical association between relationships and depression course is not causal, but due to shared variance with other factors. We investigated whether elements of social relationships predict major depressive episode (MDE) when multiple relevant variables are considered.

METHOD

Data is from a longitudinal study of primary care patients with depressive symptoms. 494 participants completed questionnaires at baseline and a depression measure (PHQ-9) two years later. Baseline measures included functional (i.e. quality) and structural (i.e. quantity) social relationships, depression, neuroticism, chronic illness, alcohol abuse, childhood abuse, partner violence and sociodemographic characteristics. Logistic regression with generalised estimating equations was used to estimate the association between social relationships and MDE.

RESULTS

Both functional and structural social relationships predicted MDE in univariate analysis. Only functional social relationships remained significant in multivariate analysis (OR: 0.87; 95%CI: 0.79-0.97; p=0.01). Other unique predictors of MDE were baseline depression severity, neuroticism, childhood sexual abuse and intimate partner violence.

LIMITATIONS

We did not assess how a person's position in their depression trajectory influenced the association between social relationships and depression.

CONCLUSIONS

Interventions targeting relationship quality may be part of a personalised treatment plan for people at high risk due of persistent depression due to poor social relationships.