Friday, March 17, 2017
For years decision support tools have been available for certain diseases, but not usually for mental health. However, there has recently been an emergence of some on-line calculators for supporting important clinical decisions such as "should I take an antidepressant" and "should I stop my antidepressant." The extent of evidence underpinning the decision support is difficult to discern, but these tools are interesting because they walk a person though a decision making process, soliciting ratings from the decision-maker to inform the final decision.
Saturday, November 19, 2016
Wednesday, October 12, 2016
Major depression is thought to be more common in the winter than the summer months in Canada (e.g. follow this link), and changing circadian patterns are believed to have a role in this. It has sometimes been suspected that there would be a north-south latitude gradient as well. However, the small number of studies that have looked at this have failed to find an association, see Partonen et al. and Grimaldi et al. Using data from many large scale Canadian surveys, were able to examine this association with a much larger sample size than was previously possible. These surveys included a measure of past year major depressive episodes called the Composite International Diagnostic Interview, Short Form and by linking to postal code files we were able to determine the approximate latitude of each respondent. A small gradient was found, with more northerly latitudes having a higher prevalence. A link to be the abstract is available here. It is possible that the etiology of such depression is related to factors such as sunlight exposure or shifting circadian patterns with more northerly latitudes. Of course, the difference could also be due to social determinants. Additional studies will be needed to determine this, but with adjustment for many potential determinants (age, sex, marital status, income, education) the association persisted. These results may contain clues to understanding the causes of depression more clearly, but they certainly also have implications for planning health services in more northerly places.
Tuesday, July 19, 2016
Understanding how depression prevalence varies by person, place and time variables can help to plan for services and also generate hypotheses for future research. With respect to planning services an important question is whether there is more depression in urban or rural areas. The evidence so far has been mixed, with a few studies finding an association and others not. A recent analysis of data from a series of Canadian Community Health Surveys was able to incorporate a larger number of observations than any previous study and to settle the issue. The answer is that depression prevalence is about 20% higher in urban areas. This is not a large difference. Some risk factors such as childhood adversities are associated with an approximate doubling (100% increase) in prevalence. Indeed the modest effect of urban living probably explains the previously inconsistent literature. Analyses of individual surveys probably lacked power to detect it. However, from the point of view of planning services, a 18% difference is not trivial. Why would the prevalence be higher in urban areas? There are many possible explanations. One is that the environment there may convey a higher risk of becoming depressed (aka a higher incidence of depression), however, a longer duration of depressive episodes or lower mortality (e.g. due to suicide) in urban areas could also explain it. Finally, migration of depressed people from rural to rural areas is another possible reason for the difference. This work has been published in the Canadian Journal of Psychiatry, a link to the abstract is available here.
Tuesday, March 29, 2016
A 2012 mental health survey conducted in Canada (called the Canadian Community Health Survey-Mental Health or CCHS-MH) included a brief interview module designed to assess perceived stigma among those accessing mental health services. The module was called the Mental Health Experiences Scale, developed by Dr. Heather Stuart, at Queens University. The CCHS was a large survey, with a sample size of > 25,000 respondents. It employed a sophisticated sampling design to ensure representation of the national household population. However, the stigma scale was only administered to a subset (an estimated 8% of the population) who reported accessing mental health services in the preceding year. However, the questions in the scale asked about perceived stigma from any source, not just health professionals. About one in four of these respondents reported encountering stigma. The survey also included measures of mental health status, such as perceived mental health, a distress scale, self-reported diagnosis and a structured diagnostic interview. People with diagnoses were more likely to report stigmatization (irrespective of whether the diagnoses were from the diagnostic interview or from a health professional). Surprisingly, the frequency of perceived stigma was almost as high in people with mood and anxiety disorders as among people with Schizophrenia. Similar to previous studies, the perception of stigma was found to be lower in older respondents, over the age of 55. It is often assumed that stigma results from labelling, or that labelling is an essential component of the process of stigmatization. In this regard, an interesting finding was that people who reported receiving no diagnosis still often reported stigmatization, especially if they had symptoms suggestive of a diagnosable disorder (e.g. high distress, pronounced depressive symptoms). This suggests that stigma can occur directly as a result of manifestations of mental health difficulties, without the need for a diagnostic label. The paper is available here.
Sunday, March 6, 2016
In this study, information gleaned from a sample assessed during childhood and then subsequently followed in an adult health survey was used to assess adverse health outcomes associated with adverse childhood events (ACEs). Some studies have suggested that many adult health outcomes are associated with ACEs. For example, cardiovascular disease may have a higher risk in people exposed to ACEs as children. However, such associations are not fully confirmed. Most such studies are based on retrospective reports of ACEs, and retrospective recall is not very reliable. It is possible, for example, that people with more adverse health outcomes during adulthood are more likely to report or remember childhood adversities. Many of these studies have used clinical samples - and ACEs may affect health care use, which could distort the associations. If such associations exist (e.g. cardiovascular disease) it is likely that they occur through complex pathways, e.g. if ACEs increase the risk of depression, this may lead to higher rates of other behaviours (e.g. dietary and lifestyle factors) that may in turn increase the risk of cardiovascular disease. For these reasons, we recently sought to link survey that collected data from the same people during childhood and adulthood in representative community samples and to look at proximate changes that occur in relation to ACEs (i.e. changes that are evident in young adulthood). We found the most convincing evidence of associations for three inter-related outcomes and ACEs: Major depression, psychotropic medication use and smoking. The abstract is available here. This study provides some insights into the early life impact of ACEs and suggests and smoking, especially, may be a link connecting ACEs to later health difficulties.
Tuesday, February 2, 2016
Depression is common and sometimes undetected. This has led to a continued interest in screening for depression. The assumption behind screening is that there must be a lot of people who meet criteria for a depressive episode and who could be benefit from treatment, except that they have not sought treatment because they don't know that they are depressed. A screening scale such as the PHQ-9 could possibly assist with the identification of these episodes, leading to initiation of treatment and hopefully better outcomes. However, there are some unexpected drawbacks of depression screening in practice. One is that these scales produce false positives. For example, if a scale such as the PHQ-9 is roughly 80% specific, this means that 20% of people without depression will screen positive. These would need to be assessed along with other positive results, resulting in an inefficient use of resources. A related problem is that many depressive episodes are mild and self-limited. These episodes will resolve on their own. This wouldn't necessarily be a big problem for screening except that most new episodes (the ones that screening would presumably try to detect) ARE brief. This is an under-appreciated fact since in the population the average episode is about 3-4 months. However, this average is a mixture of many brief episodes and a smaller number of longer episodes - so that screening is likely to divert resources towards those with lower levels of need, or those with no treatment needs at all. This dynamic is hard to conceptualize, but I've made animation, part of a paper published in 2006, to illustrate it. In the animation the people depicted with lighter coloured shirts have brief episodes but those with darker shirts (longer episodes) predominate in the population of people with episodes because they stay longer in the population. The most effective intervention would be to help those with longer episodes recover faster through treatment as opposed to earlier detection through screening. You can see the animation here.