Niels Smits

Effectiveness of a Web-Based Self-Help Intervention for Symptoms of Depression, Anxiety, and Stress: Randomized Controlled Trial

Background Self-help therapies are often effective in reducing mental health problems. We developed a new Web-based self-help intervention based on problem-solving therapy, which may be used for people with different types of comorbid problems: depression, anxiety, and work-related stress. Objective The aim was to study whether a Web-based self-help intervention is effective in reducing depression, anxiety, and work-related stress (burnout). Methods A total of 213 participants were recruited through mass media and randomized to the intervention (n = 107) or a waiting list control group (n = 106). The Web-based course took 4 weeks. Every week an automated email was sent to the participants to explain the contents and exercises for the coming week. In addition, participants were supported by trained psychology students who offered feedback by email on the completed exercises. The core element of the intervention is a procedure in which the participants learn to approach solvable problems in a structured way. At pre-test and post-test, we measured the following primary outcomes: depression (CES-D and MDI), anxiety (SCL-A and HADS), and work-related stress (MBI). Quality of life (EQ-5D) was measured as a secondary outcome. Intention-to-treat analyses were performed. Results Of the 213 participants, 177 (83.1%) completed the baseline and follow-up questionnaires; missing data were statistically imputed. Of all 107 participants in the intervention group, 9% (n = 10) dropped out before the course started and 55% (n = 59) completed the whole course. Among all participants, the intervention was effective in reducing symptoms of depression (CES-D: Cohen’s d = 0.50, 95% confidence interval (CI) 0.22-0.79; MDI: d = 0.33, 95% CI 0.03-0.63) and anxiety (SCL-A: d = 0.42, 95% CI 0.14-0.70; HADS: d = 0.33, 95% CI 0.04-0.61) as well as in enhancing quality of life (d = 0.31, 95% CI 0.03-0.60). Moreover, a higher percentage of patients in the intervention group experienced a significant improvement in symptoms (CES-D: odds ratio [OR] = 3.5, 95% CI 1.9-6.7; MDI: OR = 3.7, 95% CI 1.4-10.0; SCL-A: OR = 2.1, 95% CI 1.0-4.6; HADS: OR = 3.1, 95% CI 1.6-6.0). Patients in the intervention group also recovered more often (MDI: OR = 2.2; SCL-A: OR = 2.0; HADS < 8), although these results were not statistically significant. The course was less effective for work-related stress, but participants in the intervention group recovered more often from burnout than those in the control group (OR = 4.0, 95% CI 1.2-13.5). Conclusions We demonstrated statistically and clinically significant effects on symptoms of depression and anxiety. These effects were even more pronounced among participants with more severe baseline problems and for participants who fully completed the course. The effects on work-related stress and quality of life were less clear. To our knowledge, this is the first trial of a Web-based, problem-solving intervention for people with different types of (comorbid) emotional problems. The results are promising, especially for symptoms of depression and anxiety. Further research is needed to enhance the effectiveness for work-related stress. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN) 14881571

Internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years old:a randomized controlled clinical trial

BACKGROUND Subthreshold depression is a highly prevalent condition and a risk factor for developing a major depressive episode. Internet-based cognitive behaviour therapy may be a promising approach for the treatment of subthreshold depression. The current study had two aims: (1) to determine whether an internet-based cognitive behaviour therapy intervention and a group cognitive behaviour therapy intervention are more effective than a waiting-list control group; and (2) to determine whether the effect of the internet-based cognitive behaviour therapy differs from the group cognitive behaviour therapy intervention. METHOD A total of 191 women and 110 men with subthreshold depression were randomized into internet-based treatment, group cognitive behaviour therapy (Lewinsohns Coping With Depression course), or a waiting-list control condition. The main outcome measure was treatment response after 10 weeks, defined as the difference in pre- and post-treatment scores on the Beck Depression Inventory (BDI). Missing data, a major limitation of this study, were imputed using the Multiple Imputation (MI) procedure Data Augmentation. RESULTS In the waiting-list control group, we found a pre- to post-improvement effect size of 0.45, which was 0.65 in the group cognitive behaviour therapy condition and 1.00 within the internet-based treatment condition. Helmert contrasts showed a significant difference between the waiting-list condition and the two treatment conditions (p=0.04) and no significant difference between both treatment conditions (p=0.62). CONCLUSIONS An internet-based intervention may be at least as effective as a commonly used group cognitive behaviour therapy intervention for subthreshold depression in people over 50 years of age.

Screening for mood and anxiety disorders with the five-item, the three-item, and the two-item mental health inventory

The Mental Health Inventory (MHI)-5 is an attractive, brief screening questionnaire for depression and anxiety disorders. It has been suggested that the three questions on depression (MHI-d) may be as good as the full MHI-5 in assessing depressive disorders. We examined the validity of the MHI-d and the MHI-a (the remaining two items on anxiety) in a large population-based sample of 7076 adults in the Netherlands. We also examined the validity of the MHI in assessing specific anxiety disorders. The presence of depressive and anxiety disorders in the past month was assessed with the Composite International Diagnostic Interview (CIDI), computerized version 1.1. ROC analyses indicated no significant difference between the MHI-5 (area under the curve of 0.93) and the MHI-d (area under the curve of 0.91) in detecting major depression and dysthymia. There was no difference either between the MHI-5 (area under the curve of 0.73) and the MHI-a (area under the curve 0.73) in detecting anxiety disorders. Both the MHI-5 and the MHI-a also seem to be adequate as a screener for some anxiety disorders (generalized anxiety disorder; panic disorder; obsessive-compulsive disorder), but not others, especially phobias (agoraphobia; social phobia; simple phobia).

One-year follow-up results of a randomized controlled clinical trial on internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years

BACKGROUND Internet-based cognitive behaviour therapy (CBT) is a promising new approach for the treatment of depressive symptoms. The current study had two aims: (1) to determine whether, after 1 year, an internet-based CBT intervention was more effective than a waiting-list control group; and (2) to determine whether the effect of the internet-based CBT differed from the group CBT intervention, 1 year after the start of treatment. METHOD A total of 191 women and 110 men (mean age=55 years, s.d.=4.6) with subthreshold depression were randomized into internet-based treatment, group CBT (Lewinsohns Coping with Depression Course), or a waiting-list control condition. The main outcome measure was treatment response after 1 year, defined as the difference in pretreatment and follow-up scores on the Beck Depression Inventory (BDI). Missing data were imputed using the multiple imputation procedure of data augmentation. Analyses were performed using multiple imputation inference. RESULTS In the waiting-list control group, we found a pretreatment to follow-up improvement effect size of 0.69, which was 0.62 in the group CBT condition and 1.22 with the internet-based treatment condition. Simple contrasts showed a significant difference between the waiting-list condition and internet-based treatment (p=0.03) and no difference between both treatment conditions (p=0.08). CONCLUSIONS People aged over 50 years with subthreshold depression can still benefit from internet-based CBT 1 year after the start of treatment.

Characteristics of effective psychological treatments of depression: A metaregression analysis.

Abstract Although many meta-analyses have shown that psychological therapies are effective in the treatment of depression, no comprehensive metaregression analysis has been conducted to examine which characteristics of the intervention, target population, and study design are related to the effects. The authors conducted such a metaregression analysis with 83 studies (135 comparisons) in which a psychological treatment was compared with a control condition. The mean effect size of all comparisons was 0.69 (95% confidence interval = 0.60–0.79). In multivariate analyses, several variables were significant: Studies using problem-solving interventions and those aimed at women with postpartum depression or specific populations had higher effect sizes, whereas studies with students as therapists, those in which participants were recruited from clinical populations and through systematic screening, and those using care-as-usual or placebo control groups had lower effect sizes.

Measurement invariance of the center for epidemiological studies depression scale (CES-D) among chinese and dutch elderly

BackgroundAlthough previous studies using non- elderly groups have assessed the factorial invariance of the Center for Epidemiological Studies Depression Scale (CES-D) across different groups with the same social-cultural backgrounds, few studies have tested the factorial invariance of the CES-D across two elderly groups from countries with different social cultures. The purposes of this study were to examine the factorial structure of the CES-D, and test its measurement invariance across two different national elderly populations.MethodsA total of 6806 elderly adults from China (n = 4903) and the Netherlands (n = 1903) were included in the final sample. The CES-D was assessed in both samples. Three strategies were used in the data analysis procedure. First, a confirmatory factor analysis (CFA) was carried out to determine the factor structures of the CES-D that best fitted the two samples. Second, the best fitting model was incorporated into a multi-group CFA model to test measurement invariance of the CES-D across the two population groups. Third, latent mean differences between the two groups were tested.ResultsThe results of confirmatory factor analysis (CFA) showed: 1) in both samples, Radloffs four-factor model resulted in a significantly better fit and the four dimensions (somatic complaints, depressed affect, positive affect, and interpersonal problems) of the CES-D seem to be the most informative in assessing depressive symptoms compared to the single-, three-, and the second-order factor models; and 2) the factorial structure was invariant across the populations under study. However, only partial scalar and uniqueness invariance of the CES-D items was supported. Latent means in the partial invariant model were lower for the Dutch sample, compared to the Chinese sample.ConclusionsOur findings provide evidence of a valid factorial structure of the CES-D that could be applied to elderly populations from both China and the Netherlands, producing a meaningful comparison of total scores between the two elderly groups. However, for some specific factors and items, caution is required when comparing the depressive symptoms between Chinese and Dutch elderly groups.

An epidemiological approach to depression prevention in old age

OBJECTIVE To identify target groups for prevention of chronic or recurrent depression in old age such that prevention is likely to become cost-effective. METHODS Data were used from a population-based cohort study (N = 2,200). Chronic or recurrent depression was defined when people presented with clinically high levels of depression at two time points separated by 3 years. Risk profiles of these conditions were identified using classification and regression trees analysis. The combinations of risk factors were then evaluated in multivariate models to ascertain their utility for preventing depression in high-risk groups. RESULTS People are placed at a high risk of depression when having symptoms of anxiety, functional impairments, two or more chronic illnesses, and either a low attained educational level or below average levels of mastery, while living without a partner. These risk profiles correspond with groups no larger than 8.3% of the older population. Containing the adverse effects of the risk factors would help to reduce the incidence of depression by possibly as much as 48.7%, indicating that large health gains can be generated, which can also be done efficiently with numbers-needed-to-be-treated, perhaps as small as three. CONCLUSION Targeting prevention on the selected high-risk groups is likely to become a cost-effective endeavor, because optimal health gains can be generated efficiently in groups small enough to be logistically manageable. The burden of illness associated with depression, particularly depression, in aging populations underscores the public health significance of such an approach.

Personality traits and health-related quality of life in patients with mood and anxiety disorders

BackgroundHealth-related quality of life (HRQL) is an accepted outcome measure in patients with mood and anxiety disorders. Yet, surprisingly little attention has been paid to the determinants. In this paper we test the hypothesis that it is associated with personality traits while controlling for mental disorders.MethodsA large sample of outpatients (n=640) with mood and anxiety disorders was studied. The empirically supported five factor model of normal personality traits was assessed using the NEO-FFI and includes: neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. Mental disorders were assessed with the CIDI, and HRQL with the SF-36.ResultsRegression analyses revealed that the NEO-FFI scores, with the exception of conscientiousness, were significantly associated with SF-36 subscales and summary scores, independently from the mental disorders. The percentage of explained variance due to the personality traits was highest for the subscales Vitality (10.0%), Mental Health (13.3%) and the Mental Health Summary Score (9.5%). Furthermore, specific personality traits were related to specific SF-36 subscales.ConclusionsA low HRQL of patients with mood or anxiety disorders is not only determined by the disease or the current health but is also shaped by personality traits that are relatively stable throughout an individual’s life time.

Using decision theory to derive optimal cut-off scores of screening instruments: an illustration explicating costs and benefits of mental health screening.

This paper shows how decision theory can be used to determine optimal cut‐off scores on mental health screeners. The procedure uses (a) the costs and benefits of correct and erroneous decisions, and (b) the rates of correct and erroneous decisions as a function of the cut‐off score. Using this information, for each cut‐off point expected costs are calculated. The cut‐off point with the lowest expected costs is the optimal cut‐off score. An illustration is given in which the General Health Questionnaire is employed as a major depression screener. Optimal cut‐off points are determined for four different contexts: patients, health service providers, society, and mental health researchers. As in these four situations different costs are encountered, different optimal cut‐off points were found. Copyright

Sensitivity and specificity of the Major Depression Inventory in outpatients.

BackgroundThe Major Depression Inventory (MDI) is a new, brief, self-report measure for depression based on the DSM-system, which allows clinicians to assess the presence of a depressive disorder according to the DSM-IV, but also to assess the severity of the depressive symptoms.MethodsWe examined the sensitivity, specificity, and psychometric qualities of the MDI in a consecutive sample of 258 psychiatric outpatients. Of these patients, 120 had a mood disorder (70 major depression, 49 dysthymia). A total of 139 subjects had a comorbid axis-I diagnosis, and 91 subjects had a comorbid personality disorder.ResultsCrohnbachs alpha of the MDI was a satisfactory 0.89, and the correlation between the MDI and the depression subscale of the SCL-90 was 0.79 (p < .001). Subjects with major depressive disorder (MDD) had a significantly higher MDI score than subjects with anxiety disorders (but no MDD), dysthymias, bipolar, psychotic, other neurotic disorders, and subjects with relational problems. In ROC analysis we found that the area under the curve was 0.68 for the MDI. A good cut-off point for the MDI seems to be 26, with a sensitivity of 0.66, and a specificity of 0.63. The indication of the presence of MDD based on the MDI had a moderate agreement with the diagnosis made by a psychiatrist (kappa: 0.26).ConclusionThe MDI is an attractive, brief depression inventory, which seems to be a reliable tool for assessing depression in psychiatric outpatients.