Dealing with bi-directionality in mental health research: The experience of the mental health project of the MRC/UVRI

E. Kinyanda1,2

1MRC/UVRI Uganda Research Unit on AIDS

2Department of Psychiatry, Makerere University, Uganda

Definitions:

Bidirectional:

“Moving or operating in two usually opposite

directions”

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A B

“Studies from USA and Europe suggest that people with HIV often suffer from depression and anxiety disorders”

“Psychiatric disorders increase one’s vulnerability to HIV infection”

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Severe mental illness and HIV infection•Demonstrated that HIV infection was responsible for the Organic affective disorder, HIV mania

(Nakimuli-Mpungu et al, 2006, Am J Psychiatry)•Patients with severe mental illness (SMI) have higher rates of HIV infection than general population

(Maling et al, 2011, AIDS Care)•Similarly observed high rates of HIV infection in SMI•Noted that these results may have been confounded by bidirectionality. Previous studies have included 1st time psychiatric admissions (Lundberg et al, 2013, Intern J Ment Health Systems )

Other examples in mental health research where bidirectional

relationships may apply

• Relationship between intimate partner violence and alcohol abuse (Campbell, 2002, Lancet )

• Relationship between depression and high risk sexual behaviour (Seth et al, 2011, Psychology, Health & Medicine )

• Relationship between severe mental illness and low socio-economic status (social causation of mental illness & social drift associated with SMI)

• Relationship between high risk sexual behaviour and alcohol abuse

Nature of studies that we do:

• Cross-sectional studies are the most commonly employed study design

• Collect data on a sample at one time point • Limitation of this design: do not get information on the

temporal relationship between variables:

Example: study looking at severe mental illness (SMI) and HIV infection

• Using the cross-sectional study, collect data on SMI status and HIV status all at one time point

Cannot Answer the question:

Is it the HIV that came first ?

Or SMI that came first ?

Longitudinal study of Depression and its impact on HIV related Outcomes

(EDCTP mental health study)

• Longitudinal study among other things looked at the epidemiology of major depressive disorder (MDD)

• Sample 1100 HIV positive adults in semi-urban and rural sites in Uganda

• Assessment were done baseline, 6 months and 12-months

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EDCTP mental health study

Outcomes: Prevalent MDD & Incident MDD

Risk factors/Predictors and confounders: •Socio-demographic factors: study site, age, sex, highest educational attainment, marital status, employment status, SES •Clinical factors: WHO stage, CD4 counts•Psychosocial factors: childhood trauma, social support, felt stigma, negative coping style, resilience, negative life events, stress scores•In this paper compare risk factor analyses of prevalent MDD & Incident MDD 8

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Discussion:

Correlates of Prevalent Major depressive•Study site, inverse of resilience, felt stigma, childhood trauma, negative coping style, negative life events

Predictors of incident Major depressive disorder•Study site, baseline depressive scores and stress score•Cross sectional study provides many factors that were associated with prevalent MDD•Longitudinal study analysis provides only 2 potential modifiable factors (baseline depression scores & Stress) that predictors of incident MDD 0

How do we deal with the issue of bidirectionality in presenting our study

results?• Need to recognising that the relationship between

the variables we may be investigating may be bidirectional

• In cross-sectional studies we should use with caution terms such ‘risk factors’ and ‘predictors’ should consider using terms such as ‘associated with’ or ‘correlated with’ when not sure about direction of causality

• When discussing limitations of our studies, we should be modest and admit that we cannot state with certainty the direction of causality

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How do we deal with the issue of bidirectionality in presenting our study

results?• Need to embrace other study designs such

longitudinal study design• Need use other analyses methodologies apart

from multiple regression analysis such as structural equation modelling to test out how our data fits the conceptual frameworks were are using

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