How patients understand depression associated with chronic physical disease - A systematic review

Background: Clinicians are encouraged to screen people with chronic physical illness for depression. Screening alone may not improve outcomes, especially if the process is incompatible with patient beliefs. The aim of this research is to understand peoples beliefs about depression, particularly in the presence of chronic physical disease. Methods: A mixed method systematic review involving a thematic analysis of qualitative studies and quantitative studies of beliefs held by people with current depressive symptoms. MEDLINE, EMBASE, PSYCHINFO, CINAHL, BIOSIS, Web of Science, The Cochrane Library, UKCRN portfolio, National Research Register Archive, Clinicaltrials.gov and OpenSIGLE were searched from database inception to 31st December 2010. A narrative synthesis of qualitative and quantitative data, based initially upon illness representations and extended to include other themes not compatible with that framework. Results: A range of clinically relevant beliefs was identified from 65 studies including the difficulty in labeling depression, complex causal factors instead of the biological model, the roles of different treatments and negative views about the consequences of depression. We found other important themes less related to ideas about illness: the existence of a self-sustaining depression spiral; depression as an existential state; the ambiguous status of suicidal thinking; and the role of stigma and blame in depression. Conclusions: Approaches to detection of depression in physical illness need to be receptive to the range of beliefs held by patients. Patient beliefs have implications for engagement with depression screening

Rejection sensitivity as a vulnerability marker for depressive symptom deterioration in men

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Impact of rotamer diversity on the self-assembly of nearly isostructural molecular semiconductors

Conformational diversity due to different orientations of structural subunits has a complex impact on morphological disorder of organic semiconductors. Here, we isolate the impact of a specific structural change: replacing bithiophene (biTh) units with thieno[3,2-b]thiophene (TT). We compare four molecules with an alternating donor-acceptor structure (D'-A-D-A-D') composed of a central, electron-rich dithienosilole (DTS) unit flanked by pyridyl-[2,1,3]thiadiazole (PT) or fluorinated benzo[c][1,2,5]thiadiazole (FBT) and end-capped with bithiophene biTh or TT groups. We find that using TT instead of biTh results in an increased degree of order within films cast directly from solution by influencing the self-assembly tendencies of the different molecules. Unlike switching the acceptor subunit, such as FBT for PT, the TT for biTh structural change has little impact on the electronic structure of these molecular semiconductors. Instead, these morphological effects can be understood within the context of the predicted conformational diversity. TT units limit the number of rotational conformations (rotamers) available within this molecular architecture; low rotamer dispersity facilitates self-assembly into ordered domains. As a practical illustration of this greater drive toward self-assembly, we use the TT-containing molecules as donors in bulk heterojunction solar cells with PC70BM. Devices with TT-containing molecules show improved photovoltaic performance compared to their previously characterized biTh analogs (d-DTS(PTTh2)(2) and p-DTS(FBTTh2)(2)) in both as-cast and optimized conditions, with efficiencies up to 6.4% and 8.8% for PT-TT and FBT-TT, respectively. The TT subunit and, more broadly, the strategy of limiting conformational diversity can be readily applied toward the design of solution-processable organic semiconductors with increased as-cast order

What is the Value of Agricultural Economics Research?

The output of agricultural economics research is information, much of it aimed at designing or improving institutions. Bayesian decision theory and economic surplus analysis have been suggested as possible approaches to evaluate that information. This article takes a critical look at the strengths and weaknesses of combining those approaches for empirical evaluation of agricultural economics research. It presents three case studies, utilizing prior and posterior probabilities elicited from key decision makers. Direct application of the probabilities to a simple set of states and actions is best suited to situations involving a single policy-making center, or a consensus decision-making process. Copyright 2003, Oxford University Press.