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Classic theories posit that depression is driven by a negative learning bias. Most studies supporting this proposition used small and selected samples, excluding patients with comorbidities. However, comorbidity between psychiatric disorders occurs in up to 70% of the population. Therefore, the generalizability of the negative bias hypothesis to a naturalistic psychiatric sample as well as the specificity of the bias to depression, remain unclear. In the present study, we tested the negative learning bias hypothesis in a large naturalistic sample of psychiatric patients, including depression, anxiety, addiction, attention-deficit/hyperactivity disorder, and/or autism. First, we assessed whether the negative bias hypothesis of depression generalized to a heterogeneous (and hence more naturalistic) depression sample compared with controls. Second, we assessed whether negative bias extends to other psychiatric disorders. Third, we adopted a dimensional approach, by using symptom severity as a way to assess associations across the sample.
Methods
We administered a probabilistic reversal learning task to 217 patients and 81 healthy controls. According to the negative bias hypothesis, participants with depression should exhibit enhanced learning and flexibility based on punishment v. reward. We combined analyses of traditional measures with more sensitive computational modeling.
Results
In contrast to previous findings, this sample of depressed patients with psychiatric comorbidities did not show a negative learning bias.
Conclusions
These results speak against the generalizability of the negative learning bias hypothesis to depressed patients with comorbidities. This study highlights the importance of investigating unselected samples of psychiatric patients, which represent the vast majority of the psychiatric population.
As depression has a recurrent course, relapse and recurrence prevention is essential.
Aims
In our randomised controlled trial (registered with the Nederlands trial register, identifier: NTR1907), we found that adding preventive cognitive therapy (PCT) to maintenance antidepressants (PCT+AD) yielded substantial protective effects versus antidepressants only in individuals with recurrent depression. Antidepressants were not superior to PCT while tapering antidepressants (PCT/−AD). To inform decision-makers on treatment allocation, we present the corresponding cost-effectiveness, cost-utility and budget impact.
Method
Data were analysed (n = 289) using a societal perspective with 24-months of follow-up, with depression-free days and quality-adjusted life years (QALYs) as health outcomes. Incremental cost-effectiveness ratios were calculated and cost-effectiveness planes and cost-effectiveness acceptability curves were derived to provide information about cost-effectiveness. The budget impact was examined with a health economic simulation model.
Results
Mean total costs over 24 months were €6814, €10 264 and €13 282 for AD+PCT, antidepressants only and PCT/−AD, respectively. Compared with antidepressants only, PCT+AD resulted in significant improvements in depression-free days but not QALYs. Health gains did not significantly favour antidepressants only versus PCT/−AD. High probabilities were found that PCT+AD versus antidepressants only and antidepressants only versus PCT/−AD were dominant with low willingness-to-pay thresholds. The budget impact analysis showed decreased societal costs for PCT+AD versus antidepressants only and for antidepressants only versus PCT/−AD.
Conclusions
Adding PCT to antidepressants is cost-effective over 24 months and PCT with guided tapering of antidepressants in long-term users might result in extra costs. Future studies examining costs and effects of antidepressants versus psychological interventions over a longer period may identify a break-even point where PCT/−AD will become cost-effective.
Declaration of interest
C.L.H.B. is co-editor of PLOS One and receives no honorarium for this role. She is also co-developer of the Dutch multidisciplinary clinical guideline for anxiety and depression, for which she receives no remuneration. She is a member of the scientific advisory board of the National Insure Institute, for which she receives an honorarium, although this role has no direct relation to this study. C.L.H.B. has presented keynote addresses at conferences, such as the European Psychiatry Association and the European Conference Association, for which she sometimes receives an honorarium. She has presented clinical training workshops, some including a fee. She receives royalties from her books and co-edited books and she developed preventive cognitive therapy on the basis of the cognitive model of A. T. Beck. W.A.N. has received grants from the Netherlands Organisation for Health Research and Development and the European Union and honoraria and speakers' fees from Lundbeck and Aristo Pharma, and has served as a consultant for Daleco Pharma.
Mindfulness-based cognitive therapy (MBCT) and maintenance antidepressant medication (mADM) both reduce the risk of relapse in recurrent depression, but their combination has not been studied.
Aims
To investigate whether MBCT with discontinuation of mADM is non-inferior to MBCT+mADM.
Method
A multicentre randomised controlled non-inferiority trial (ClinicalTrials.gov: NCT00928980). Adults with recurrent depression in remission, using mADM for 6 months or longer (n = 249), were randomly allocated to either discontinue (n = 128) or continue (n = 121) mADM after MBCT. The primary outcome was depressive relapse/recurrence within 15 months. A confidence interval approach with a margin of 25% was used to test non-inferiority. Key secondary outcomes were time to relapse/recurrence and depression severity.
Results
The difference in relapse/recurrence rates exceeded the non-inferiority margin and time to relapse/recurrence was significantly shorter after discontinuation of mADM. There were only minor differences in depression severity.
Conclusions
Our findings suggest an increased risk of relapse/recurrence in patients withdrawing from mADM after MBCT.
This article describes several indicators and methods for estimating nitrogen flows and balance sheets. It reviews their strengths and weaknesses according to user types and their objectives. The nitrogen balance sheets, based on the difference between inputs and outputs are by far the most-often used estimator of nitrogen management on livestock farms. Among those, the soil surface balance helps in guiding the fertilisation and the farmgate balance is logically higher. The indicators of practices are easy to use but are poor predictors of nitrogen losses, whereas the indicators of emissions allow for estimating nitrogen losses using either direct measurements or models thereby providing a dynamic assessment of these flows. The coupling of balance sheets and indicators of emissions offers a certain potential for improvement of diagnosis and support of decision making. Finally, the indicators of impacts, including the life cycle analyses are currently the most popular for qualifying the impacts of animal production.
Substantial improvements of agricultural systems are necessary to meet the future requirements of humanity. However, current agricultural knowledge and information systems are generally not well suited to meet the necessary improvements in productivity and sustainability. For more effective application of research output, research producers and research consumers should not be considered as separate individuals in the knowledge chain but as collaborating partners creating synergy. The current paper investigates the relationships between scientists and stakeholders and identifies approaches to increase the effectiveness of their communication. On-farm research has proven to be an effective means of improving exploitation of research output at farm level because it connects all relevant partners in the process. Furthermore, pilot farms can act as an effective platform for communication and dissemination. Regional networks of pilot farms should be established and connected across regions.