![]() ![]() ![]() A comprehensive risk communication program may improve the uptake and maximize the impact on behavior changes and risk reduction. The most significant motivation for, and benefit of receiving one’s personalized depression risk score was improved awareness of one’s mental health. The final theme focussed on improvements including: the best delivery methods, having resources and strategies, and targeting younger people. Most participants found that receiving their score was positive because it improved their awareness of their mental health, but some participants could see that some people would have negative feelings when getting the score causing them to be more likely to get depression. The results revealed three sub-themes surrounding perceptions and implication of receiving their risk score: positive, negative, and neutral. Most participants chose to receive their personalised depression risk score with the goal of improving their self-awareness. The first theme explained the motivation for receiving a risk score. We conducted a content analysis to describe the content and contextual meaning of data collected from participants. The qualitative interviews were conducted through telephone, audio recorded and transcribed verbatim. The participants (20 males and 20 females) were randomly selected from the intervention arm of the RCT after the 12-month assessment. To understand users’ perceptions about receiving their personalized depression risk score and to gain an understanding about how to improve the efficiency of risk communication from the user perspective.Ī qualitative study embedded in a randomized controlled trial (RCT) on evaluating the impact of providing personalized depression risk information on psychological harms and benefits. Ultimately, application of algorithms may lead to increased personalization of treatment, and better clinical outcomes. However, the ability of a small number of easily assessed variables to predict MDE risk indicates that algorithms are a promising strategy for identifying individuals in need of enhanced monitoring and preventive interventions. More studies are needed to further validate and refine these algorithms. It was not feasible to validate the algorithms in different populations from different countries. The algorithms had good predictive power and calibrated well in the development and validation data. In the training data, the C statistics for algorithms in men was 0.7953 and was 0.7667 for algorithm in women. MDE was assessed using the World Health Organization's Composite International Diagnostic Interview(CIDI)-Short Form for Major Depression (CIDI-SFMD). Validation was also conducted in sub-populations that are of practice and policy importance. 10,601 participants who were aged 18 years and older and who did not meet the criteria for MDE in the 12 months prior to a baseline interview in 2000/01 were included in algorithm development data from 7902 participants who were aged 18 and older and who were free of MDE in 2004/05 were used for validation. Household residents from 10 provinces were randomly recruited and interviewed by Statistics Canada. To develop and validate sex specific prediction algorithms for 4-year risk of major depressive episode (MDE) using data from a population-based longitudinal cohort.
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