The responsiveness of quality of life utilities to change in depression: a comparison of instruments (SF-6D, EQ-5D, and DFD).

BACKGROUND: Utilities are often a main outcome parameter in economic evaluations. Because depression has a large influence on quality of life, it is expected that utilities are responsive to changes in depression. OBJECTIVE: To evaluate the change in utility derived from different instruments in depression, including the Short Form 6D (SF-6D), the Euroqol based on the UK (EQ-5D(UK)), the Euroqol based on the Dutch tariff (EQ-5D(NL)), and utilities derived from Beck Depression Inventory Second Edition (BDI-II) using the Depression-Free-Day method. METHOD: This study evaluated the responsiveness, the minimally important difference, and the agreement in utility change derived from the different instruments. RESULTS: The SF-6D, EQ-5D(UK), and EQ-5D(NL) were responsive. The minimally important difference values are in line with previous studies, about 0.3. The Depression-Free-Day method nearly always resulted in positive utility changes, even for subgroups that had no change or deterioration in health status or depression. There was poor agreement between utility changes of the SF-6D, EQ-5D (either EQ-5D(UK) or EQ-5D(NL)), and DFDu. CONCLUSIONS: The SF-6D, EQ-5D(UK), and EQ-5D(NL) seem responsive and thus adequate for estimating utility in depression treatment. We do not recommend the use of the Depression-Fee-Day method. The low agreement between utility changes indicates that outcomes of the different instruments are incomparable.

Discrepancy in rating health-related quality of life of depression between patient and general population.

OBJECTIVE: To compare the quality of life valuation of a hypothetical depression health state between a general population versus a depressive patient population, and within a patient population. METHOD: In a self-administered Internet questionnaire, both patient and general population groups filled in the Euroqol 5D (EQ-5D) questionnaire for a hypothetical depression health state describing mild (N = 740), moderate (N = 691), or severe (N = 670) depression and valued it using a rating scale (RS). The 'patient' group consisted of people reporting depressive complaints on the Internet questionnaire, subdivided into three depression severity groups (mild, moderate, severe) based on the Beck Depression Inventory Second Edition (BDI-II) and two groups according to self-perceived duration (≤ 3 months, ≥ 4 months) of depressive complaints (SPDD). RESULTS: Significant differences were found between the patient and general population and within the patient population on RS outcomes and on the Euroqol domains usual activities, pain/discomfort, and anxiety/depression. The direction of the differences shows that subgroups with higher severity or longer duration of depressive complaints value depression health states worse compared with subgroups with less severe complaints, a shorter duration, or no depressive complaints. Moreover, the discrepancy in valuation of a health state between different subgroups changes according to the severity of the health state described. CONCLUSION: There are discrepancies in the valuation of a hypothetical depression health state between a patient and general population, whereby depression leads to a worse valuation. But also within the patient population, the valuation differs according to depression severity and duration. Identification with the hypothetical health state description might explain the varying differences found between subgroups for the different hypothetical health state descriptions.

Use and acceptability of unsupported online computerized cognitive behavioral therapy for depression and associations with clinical outcome.

BACKGROUND: In a recent randomized trial, we were unable to confirm the previously reported high effectiveness of CCBT. Therefore, the aim of the current study was to have a closer look at usage and acceptability (i.e. expectancy, credibility, and satisfaction) of the intervention. METHODS: Depressed participants (N=200) were given login codes for unsupported online CCBT. A track-and-trace system tracked which components were used. We used a 9-month follow-up period. RESULTS: Uptake was sufficient, but dropout was high. Many usage indices were positively associated with short-term depressive improvement, whereas only homework was related to long-term improvement. Acceptability was good and expectancy could predict long-term, but not short-term outcome. LIMITATIONS: Associations between use of CCBT and improvement are merely correlational. Our sample was too depressed in relation to the scope of the intervention. We relied on online self-report measures. Analyses were exploratory in nature. CONCLUSIONS: Although CCBT might be a feasible and acceptable treatment for depression, means to improve treatment adherence are needed for moderately to severely depressed individuals.

Clinical and cost-effectiveness of computerised cognitive behavioural therapy for depression in primary care: design of a randomised trial.

BACKGROUND: Major depression is a common mental health problem in the general population, associated with a substantial impact on quality of life and societal costs. However, many depressed patients in primary care do not receive the care they need. Reason for this is that pharmacotherapy is only effective in severely depressed patients and psychological treatments in primary care are scarce and costly. A more feasible treatment in primary care might be computerised cognitive behavioural therapy. This can be a self-help computer program based on the principles of cognitive behavioural therapy. Although previous studies suggest that computerised cognitive behavioural therapy is effective, more research is necessary. Therefore, the objective of the current study is to evaluate the (cost-) effectiveness of online computerised cognitive behavioural therapy for depression in primary care. METHODS/DESIGN: In a randomised trial we will compare (a) computerised cognitive behavioural therapy with (b) treatment as usual by a GP, and (c) computerised cognitive behavioural therapy in combination with usual GP care. Three hundred mild to moderately depressed patients (aged 18-65) will be recruited in the general population by means of a large-scale Internet-based screening (N = 200,000). Patients will be randomly allocated to one of the three treatment groups. Primary outcome measure of the clinical evaluation is the severity of depression. Other outcomes include psychological distress, social functioning, and dysfunctional beliefs. The economic evaluation will be performed from a societal perspective, in which all costs will be related to clinical effectiveness and health-related quality of life. All outcome assessments will take place on the Internet at baseline, two, three, six, nine, and twelve months. Costs are measured on a monthly basis. A time horizon of one year will be used without long-term extrapolation of either costs or quality of life. DISCUSSION: Although computerised cognitive behavioural therapy is a promising treatment for depression in primary care, more research is needed. The effectiveness of online computerised cognitive behavioural therapy without support remains to be evaluated as well as the effects of computerised cognitive behavioural therapy in combination with usual GP care. Economic evaluation is also needed. Methodological strengths and weaknesses are discussed. TRIAL REGISTRATION: The study has been registered at the Netherlands Trial Register, part of the Dutch Cochrane Centre (ISRCTN47481236).