Diamond outcomes

Learn more about Diamond’s key findings and why it was twice named one of the National Health and Medical Research Council’s (NHMRC) ’10 of the best’ projects in Australia.

Research projects informed by the Diamond study

Diamond outcomes overview

Depression complexity

Gunn, J. Gilchrist, G. Chondros, P. Ramp, M. Hegarty, K. Blashki, G. Pond, D. Kyrios, M. Herrman, H. (2008). "Who is identified when screening for depression is undertaken in general practice? Baseline findings from the Diagnosis, Management and Outcomes of Depression in Primary Care (diamond) longitudinal study." Med J Aust188(12 Suppl): S119-125.

Screening for depressive symptoms in general practice identified a group of patients with substantial multiple comorbidities.

Major depressive syndrome (MDS) was associated with somatic symptoms, psychiatric comorbidity, and childhood abuse.
Of the patients with current MDS, 84.4% were receiving mental health care.

Depressive symptoms often co-exist with psychiatric, physical and social problems.

Depression and chronic physical illness

Gunn, J. Ayton, D. Densley, K. Pallant, J. Chondros, P. Herrman, H. Dowrick, C. (2012). "The association between chronic illness, multimorbidity and depressive symptoms in an Australian primary care cohort." Soc Psychiatry Psychiatr Epidemiol 47(2): 175-184. DOI: 10.1007/s00127-010-0330-z

Depression is rarely stand-alone condition

The prevalence of probable depression increased with increasing number of chronic physical conditions

1 condition: 23%
2 conditions: 27%
3 conditions: 30%
4 conditions: 31%
5 or more conditions: 41%

Only 16% of those with no listed physical conditions recorded CES-D scores of 16 or above.

A dose–response relationship exists between the number of chronic physical problems and depressive symptoms.

Primary care practitioners will identify more cases of depression if they focus on those with more than one chronic physical condition.

Depression trajectories

Gunn, J. Elliott, P. Densley, K. Middleton, A. Ambresin, G. Dowrick, C. Herrman, H. Hegarty, K. Gilchrist, G. Griffiths, F. (2013). "A trajectory-based approach to understand the factors associated with persistent depressive symptoms in primary care." J Affect Disord 148(2–3): 338-346. DOI: 10.1016/j.jad.2012.12.021

Five depression trajectories were identified:

Three static (mild [67%], moderate [18%], and severe [9%])
Two fluctuating (decreasing severity [4%] and increasing severity [2%]).

People with static mild (or sub-syndromal) depression symptoms are the most common presentation in primary care. The much smaller proportion of people with severe and moderate depression have extremely high levels of disadvantage, abuse, morbidity and disability.

Depression and self-rated health

Ambresin, G., Chondros, P. Dowrick, C. Herrman, C. Gunn, J. (2014). "Self-Rated Health and Long-Term Prognosis of Depression." The Annals of Family Medicine 12(1): 57-65. DOI: 10.1370/afm.1562

Self-rated health was a strong and consistent predictor of risk of major depressive syndrome (MDS) during the 5 years of follow-up.

There was a twofold increase in the risk of MDS for patients rating their health as poor to fair (compared with those rating good to excellent)

Depression and long-term antidepressant use

Ambresin, G. V. Palmer, K. Densley, C. Dowrick, Gilchrist, G. Gunn J. (2015). "What factors influence long-term antidepressant use in primary care? Findings from the Australian diamond cohort study." J Affect Disord 176(0): 125-132. DOI: 10.1016/j.jad.2015.01.055

Worldwide there is a rise in antidepressant prescribing that cannot be explained by an increase in psychiatric need.

The increase is largely due to long term prescribing, which is common in primary care.
There is a significant opportunity in primary care to improve the timely discontinuation of antidepressants.

Depression clinical risk prediction

Chondros, P. Davidson, S. Wolfe, R. Gilchrist, G. Dowrick, C. Griffiths, F. Hegarty, K. Herrman, H. Gunn, J. (2018) “Development of a prognostic model for predicting depression severity in adult primary patients with depressive symptoms using the diamond longitudinal study.” Journal of Affective Disorders. DOI: 10.1016/j.jad.2017.11.042

A risk prediction tool for patients with current depressive symptoms that estimates their likely course of depression.

The tool has been designed to link an individual’s predicted course of depression with an appropriate level of treatment.
This tool has been designed to be feasible for use in a GP consultation.

The prognostic model predicting depression severity trajectory at 3 months included eight baseline predictors: sex, depressive symptoms, anxiety, history of depression, self-rated health, chronic physical illness, living alone, and perceived ability to manage on available income.

Innovative analysis techniques

Method: Growth Mixed-Modelling

Growth Mixed-Modelling (GMM) is a statistical technique used to identify how individuals or sub-groups within a larger population change over time, particularly when the patterns of change are not the same due to complexity.
Data from participants were classified into depression severity sub-groups based upon the outcomes of a number of biopsychosocial variables over time. Understanding the different patterns or trajectories of individuals and sub-groups within a population can lead to more tailored interventions.

Complex systems analysis

Method: Generalised information entropy, maximum entropy estimates and numerical simulation

Feng, Q. Griffiths, F. Parsons, N. Gunn, J. (2013). "An exploratory statistical approach to depression pattern identification." Physica A 392(4): 889-901. DOI: 10.1016/j.physa.2012.10.025

Generalised Information Entropy was used to quantify uncertainty, heterogeneity, and structural change in the symptom patterns of depressed individuals over time.

Maximum Entropy Estimates infers the most unbiased structure of symptom interaction consistent with observed trends.

Numerical Simulation then explores how these interactions evolve over time and usual care.
Together these provided a novel way to visualise and quantitatively measure the depression pattern of the depressed individual, allowing for pattern categorisation.

Outcomes

Individual depression patterns were developed from 14 major factors related to depression: employment status, live alone status, income management, money meets needs, environmental score, social relationship, psychological score, physical score, somatic symptoms, absent days because of physical symptoms, total exercise, community participation, recent life positive impacts, recent life negative impacts, total childhood sexual abuse, and total childhood physical abuse.

Suggests that the depressed individual can be considered as subsystems of an open complex system.

Method: Case-based computer modelling

Castellani, B. Griffiths, F. Rajaram, R. Gunn, J. (2018). “Exploring comorbid depression and physical health trajectories: A case‐based computational modelling approach.” Journal of Evaluation in Clinical Practice. DOI: 10.1111/jep.13042

Case-based complexity examines cases in complex systems terms. A SACS Toolkit framework was used. Longitudinal clusters were created, based on theory, an expected number of cluster trends were assumed. The SOM Toolkit was then used to identify the optimal cluster solution from quantisation error and topographical error. The SOM cluster solution was then graphed onto a multidimensional surface (u-matrix), and a final exploratory cluster solution was confirmed through expert consensus.

Outcomes

Eleven trajectories (health, okay vacillating, okay same, okay improving, moderate depression improving, episodic depression 1, episodic depression 2, moderate depression poor health, chronic, unhealthy, oscillators) & two large-scale collective dynamics were identified. Childhood abuse, partner violence, and negative life events were greater amongst unhealthy trends.

Genetic factors

Bousman, C. Potiriadis, M. Everall, I. Gunn, J. (2014). "G-protein β3 subunit genetic variation moderates five-year depressive symptom trajectories of primary care attendees." J Affect Disord 165(0): 64-68. DOI: doi.org/10.1016/j.jad.2014.04.044

Five-year depressive symptom trajectories were moderated by the G-protein β3 subunit (GNB3) rs5440 genotype. Carriers of the rs5440 GG genotype had more favourable depressive symptom trajectories compared to AG or AA genotype carriers. Evidence suggests genetic variation in the 5-prime region of GNB3 moderates’ patients’ depressive symptom trajectories.

Bousman, C. Potiriadis, M. Everall, I. Gunn, J. (2013). "Methylenetetrahydrofolate reductase (MTHFR) genetic variation and major depressive disorder prognosis: A five‐year prospective cohort study of primary care attendees." American Journal of Medical Genetics Part B: Neuropsychiatric Genetics. DOI: 10.1002/ajmg.b.32209

MTHFR genetic variation and depression prognosis: Preliminary research suggests that among people with depressive symptoms, those with a certain genotype (677CC), have an increased likelihood of experiencing persistent depression.

Bousman, C. Potiriadis, M. Everall, I. Gunn, J. (2013). “Effects of Neuregulin-1 Genetic Variation and Depression Symptom Severity on Longitudinal Patterns of Psychotic Symptoms in Primary Care Attendees.” American Journal of Medical Genetics Part B: Neuropsychiatric Genetics. DOI: 10.1002/ajmg.b.32206

Depression symptom severity had less effect on longitudinal psychotic symptoms among carriers of the Neuregulin-1 (NRG1) genetic variation rs6994992TT genotype, compared to CC and CT carriers. Suggests a curvilinear association between depression symptom severity and longitudinal patterns of psychotic symptoms which is moderated by NRG1 genotype.

Nguyen T, Gunn J, Potiriadis M, Everall, I. Bousman C. (2015). "Serotonin transporter polymorphism (5HTTLPR), severe childhood abuse and depressive symptom trajectories in adulthood." British Journal of Psychiatry Open 1(1): 104-109.

DOI: 10.1192/bjpo.bp.115.000380

The effect of severe childhood abuse on depressive symptoms was moderated by 5HTTLPR genotype. s/s genotype carriers with a history of child abuse had greater baseline depressive symptom severity compared with those without a history of child abuse and this effect persisted throughout the 5-year observation period. The l/s or l/l genotype had similar depressive symptom trajectories regardless of childhood abuse history.

Webb, C. Gunn J. Potiriadis M, Everall, I. Bousman C. (2016). "The Brain-Derived Neurotrophic Factor Val66Met Polymorphism Moderates the Effects of Childhood Abuse on Severity of Depressive symptoms in a Time-Dependent Manner." Front. Psychiatry 7(151). DOI: 10.3389/fpsyt.2016.00151

The presence of the interaction between BDNF rs6265 and severe childhood abuse was dependent on the time at which it was assessed. At baseline, Met allele carriers reported fewer depressive symptoms in the absence of severe childhood abuse and greater depressive symptoms in the presence of a history of severe childhood abuse (compared to Val/Val individuals). Over the course of the 5 years this interaction was gradually attenuated.

Bousman, C. Gunn, J. Potiriadis, M. Everall, IP. (2017). “Polygenic phenotypic plasticity moderates the effects of severe childhood abuse on depressive symptom severity in adulthood: A 5-year prospective cohort study. The World Journal of Biological Psychiatry. DOI: 10.3109/15622975.2016.1153710

The differential susceptibility framework. Higher phenotypic plasticity allelic load (PAL) was associated with greater depressive symptom severity among those with a history of severe childhood abuse but significantly lower symptom severity among those without this history. These findings suggest that an individual’s PAL may serve as a trait marker of sensitivity to negative and positive environmental influences.

Jessel, CD. Mostafa, S. Potiriadis, M. Everall, IP. Gunn, J. Bousman, C. (2020). “Use of antidepressants with pharmacogenetic prescribing guidelines in a 10-year depression cohort of adult primary care patients.” Pharmacogenetics and Genomics. DOI: 10.1097/FPC.0000000000000406

One-quarter of primary care patients used an antidepressant that was not recommended for them based on CYP2D6- and CYP2C19 genotype-predicted metaboliser status prescribing guidelines.

Other depression outcomes

Depression recovery

Johnson, C. Gunn, J. Kokanovic, R. (2009). "Depression recovery from the primary care patient's perspective: 'hear it in my voice and see it in my eyes'." Mental Health in Family Medicine 6(1): 49-55. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2777597/

Recovery means different things to different people. Understanding what recovery looks like for each individual is part of treatment planning.

Recommended more patient-centred approaches to setting goals for depression recovery, taking into account the patients’ views on recovery.

Depression and intimate partner violence

Gilchrist, G. Hegarty, K. Chondros, P. Herrman, H. Gunn, J. (2010). "The association between intimate partner violence, alcohol and depression in family practice." BMC Fam Pract 11(1): 72.DOI: 10.1186/1471-2296-11-72

Approximately one fifth of women with depressive symptoms report having experienced some level of intimate partner violence during their lifetime.

More females than males (20.8% versus 7.6%) reported ever being afraid of a partner during their lifetime.
Being afraid of a partner was more strongly associated with depression symptoms than hazardous drinking.
Approximately one quarter of men with depressive symptoms drink alcohol at hazardous levels.

Depression recovery and written plans

Palmer, V. Johnson, C. Furler, J. Densley, K. Potiriadis, M. Gunn, J. (2013). "Written plans: an overlooked mechanism to develop recovery-oriented primary care for depression?" Australian Journal of Primary Health. DOI: 10.1071/PY12128

People reported having a written plan was beneficial for recovery from depression.

Personal resilience in depression management

Dowrick, C. Kokanovic, R. Hegarty, K. Griffiths, F. Gunn, J. (2008). "Resilience and depression: perspectives from primary care." Health (London) 12(4): 439-452. DOI: 10.1177/1363459308094419

Two elements of personal resilience were identified: ordinary magic – drawing on existing social support and affectional bonds; and personal medicine – building on personal strengths and expanding positive emotions.

Patients viewed personal resilience as an important strategy for depression management and had a strong preference for personal over professional approaches when dealing with mental health issues

Boardman, F. Griffiths, F. Kokanovic, R. Potiriadis, M. Dowrick, C. Gunn, J. (2011). "Resilience as a response to the stigma of depression: A mixed methods analysis." J Affect Disord 135 (1-3): 267-276. DOI: 10.1016/j.jad.2011.08.007

Approximately one third of patients referred to drawing on some form of personal resilience to manage and recover from depression.

By drawing on both ‘ordinary magic’ and ‘personal medicine’, participants empowered themselves by reclaiming positive identities and avoiding negative consequences of stigma in ways that drew on their own strengths and resources.

Griffiths, F. Boardman, F. Chondros, C. Dowrick, C. Densley, K. Hegarty, K and Gunn, J. (2014). "The effect of strategies of personal resilience on depression recovery in an Australian cohort: A mixed methods study." Health DOI: 10.1177/1363459314539774

Those who used personal resilience strategies had improved depression outcomes

56% of patients were primarily users of personal resilience strategies, drawing on expanding their own inner resources or pre-existing relationships. Of these 61% reported expanding their inner resources, 25% drawing on relationships, and 14% were users of both. There was no association between drawing on relationships and depression outcome. Study showed improved outcomes for depression for those who reported the use of personal resilience strategies as helpful.

General Practitioner and mental health interventions

Davidson, S. Harris, M, Dowrick, C. Wachtler, C. Pirkis, J. Gunn J. (2015). "Mental health interventions and future major depression among primary care patients with subthreshold depression." Journal of Affective Disorders 177: 65-73.DOI: 10.1016/j.jad.2015.02.014

80.8% of patients received a mental health intervention.

GPs deliver mental health interventions to most subthreshold depression patients, however, it seems that current interventions are not averting MDD.

Depression and smoking

Gilchrist, G. Davidson, S. Middleton, A. Herrman, H. Hegarty, K. Gunn, J. (2015). "Factors associated with smoking and smoking cessation among primary care patients with depression: a naturalistic cohort study." Advances in Dual Diagnosis 8(1): 18-28. DOI: 10.1108/ADD-10-2014-0036

People with depressive symptoms are significantly more likely to smoke than other people, thus further complicating their physical health and, in many cases, compromising their ability to manage on their available income.

Depression and social relationships

Davidson, S. Dowrick, C. Gunn, J. (2016). "Impact of functional and structural social relationships on two year depression outcomes: A multivariate analysis." Journal of Affective Disorders 193: 274-281. DOI: 10.1016/j.jad.2015.12.025

People with poor functional social relationships were risk of experiencing persistent depression.