Explanations for variation in cognitive ability : behavioural ecology meets comparative cognition

Sara Shettleworth has played a defining role in the development of animal cognition and its integration into other parts of biology, especially behavioural ecology. Here we chart some of that progress in understanding the causes and importance of variation in cognitive ability and highlight how Tinbergen's levels of explanation provide a useful framework for this field. We also review how experimental design is crucial in investigating cognition and stress the need for naturalistic experiments and field studies. We focus particularly on the example of the relationship among food hoarding, spatial cognition and hippocampal structure, and review the conflicting evidence for sex differences in spatial cognition. We finish with speculation that a combination of Tinbergen and Shettleworth-style approaches would be the way to grapple with the as-yet unanswered questions of why birds mimic heterospecifics.

Distributed cognition and IT support for knowledge work in breakdowns : match or mismatch?

Knowledge is instrumental in organisational problem solving and is embedded in organisational processes and routines. We explore the application of IT in breakdowns (forms of interruptions from normal organisational work routines) and illustrate the application of distributed cognition theory (DCT) as a useful lens to explain the exchange of knowledge in breakdowns. DCT also allows for a rich analysis of the role that information technology (IT) can play to foster knowledge exchange in breakdown situations. We use two cases to illustrate that DCT is useful in identifying the matches and mismatches in IT support for exchanging knowledge in breakdowns.

Identifying depression and anxiety disorders in people presenting for substance use treatment

Objective: To identify the type and proportion of depressive and related mental health disorders in a group of individuals seeking outpatient treatment at an alcohol and other drug (AOD) service.
Design, setting and participants: A cross-sectional study using diagnostic interviews with 95 participants (56 men, 39 women) seeking treatment from an AOD service.
Main outcome measures: Mental health and substance disorders were measured using the Composite International Diagnostic Interview, Posttraumatic Stress Disorder Checklist, Beck Depression Inventory, and State–Trait Anxiety Inventory (Trait Version).
Results: This was a complex group with addiction, mental health and physical health conditions; 76% had a depressive disorder and 71% had an anxiety disorder. Most were diagnosed with at least two mental health disorders and 25% were diagnosed with four or more different disorders. Alcohol and cannabis use were the most commonly diagnosed AOD disorders. Further, those diagnosed with a drug use disorder reported significantly higher levels of depression compared with those with an alcohol-only disorder. Finally, 60% of the sample reported chronic health conditions, with over one third taking medication for a physical condition on a regular basis.
Conclusions: Primary care providers such as general practitioners are likely to be increasingly called on to assess, treat and/or coordinate care of patients with AOD disorders. We show that this group will likely present to their GP with more than one MJA 2011; 195: S60–S63 mental health disorder in addition to acute and chronic physical health conditions.

Association of adolescent symptoms of depression and anxiety with alcohol use disorders in young adulthood : findings from the Victorian Adolescent Health Cohort Study

Objective: To examine the association of adolescent depression and anxiety symptoms with alcohol abuse or dependence in young adulthood.

Design, setting and participants: Cohort study of the health and wellbeing of adolescents and young adults in Victoria, assessed at 8 waves (periods) of data collection, from age 14 to 24 years, between 1992 and 2003. Young people who participated in the cohort study at least once during the six adolescent assessment points (conducted 6 months apart, from age 14 to 17 years), at least once during young adulthood and who were alive at Wave 8 (n = 1758).

Main outcome measure: Alcohol abuse or dependence assessed using the alcohol and substance abuse modules of the Composite International Diagnostic Interview at age 24 years.

Results: Adolescents with moderate to high levels of depression and anxiety symptoms (measured by the revised Clinical Interview Schedule) had an increased risk of alcohol abuse or dependence in young adulthood, compared with young adults with low levels of adolescent depression and anxiety symptoms, after adjusting for potential confounding factors. Risk was higher for those with symptoms at more than two adolescent assessment points (odds ratio [OR] 1.9; 95% CI, 1.7–2.0) and for those with symptoms at one or two assessment points (OR 1.3; 95% CI, 1.2–1.4), compared with those with no above-threshold symptoms in adolescence.

Conclusions: Adolescents with depression and anxiety symptoms are at increased risk for alcohol use disorders into young adulthood. They warrant vigilance from primary care providers in relation to alcohol use well into adulthood.

How will information about the genetic risk of mental disorders reduce stigma?

Objectives: To suggest ways of testing hypotheses about the impact that information on genetic risk may have on the social stigma of mental disorders and to analyse the implications of these hypotheses for genetic screening for mental disorders.

Method: Literature review and critical analysis and synthesis.

Results: An optimistic view is that information on the genetic risk for mental disorders will reduce blame and social stigma experienced by individuals living with mental disorder. A more pessimists view is that genetic risk information and the use of predictive genetic testing will lead to earlier stigmatization of those at risk of mental disorders. Research is identified that is needed to provide a better understanding of the implications of predictive genetic testing for the stigmatization of different mental health disorders.

Conclusions: It is essential that research on the genetics of mental disorders is accompanied by social science research on the ways in which genetic findings influence the lives of those who are tested.

Special interests and mental health in autism spectrum disorders

Special interests (SIs) in autism spectrum disorders are a prevalent though relatively under-researched phenomenon. There was partial support for the hypotheses and factors influencing the relationship between SIs and mental health were identified. Findings contribute to a better understanding of SIs including their importance for individuals with ASD.