Abstract
The biomedical model is the dominant model of mental health care in Australia, explaining mental illness as arising from physical causes, and treating it through physical interventions. This essay explores the validity and utility of this model predominantly in the context of the Australia and the Northern Territory (NT). It finds that the biomedical model has made significant contributions to our understanding of the physical mechanisms of mental illness but has failed to account for the multiple non-biological factors involved, including personal, social, environmental and cultural factors. It points to some flawed basic assumptions of the model including the ‘chemical imbalance’ theory, and significant recent evidence of publication and research bias supporting biomedical interventions, and systemic overstatements of its efficacy, and understatements of its harm. In terms of utility in Australia, there has been no improvement in mental wellbeing and in fact a decline, particularly in the NTs Aboriginal population, who continue to have some of the highest incidence of mental illness and whose needs continue to be unmet. Failure to consider these more critical and complex non-endogenous factors amounts to a flawed paradigm of care. Emerging evidence from Australia suggests the biopsychosocial model is a more effective model for addressing mental illness and for Indigenous populations, augmented with culturally and spiritually appropriate ‘ways of knowing and being’.
Keywords: biomedical model, mental illness, mental health, Australia, Northern Territory, psychological distress, PTSD, depression
The Biomedical Model and Mental Health in Australia: A Flawed Paradigm of Care?
The biomedical-model is the dominant model of mental-illness, which sees it as having a physical basis like other diseases, and therefore treats through physical interventions (Dworkin, 2011). The biomedical-model explains psychopathology as anomalies in brain structure and functioning, biochemistry, or genetics, and treatment addresses relevant biological mechanisms (Farre & Rapley, 2017). Depression, for example, speculated in the 1950s to result from an imbalance of serotonin (Stellar, 1957), is treated pharmacologically by increasing serotonin availability in the brain. There is a growing trend towards biomedical diagnosis through neuroimaging and other recent technologies (Lilienfeld & Treadway, 2016), with the search for ‘biomarkers’ and ‘precision-psychiatry’ being heralded as a new financial frontier, attracting an estimated $15 billion in research over a five-year period (Insel, 2014). With such activity and investment, this essay explores the utility and validity of the biomedical-model with focus on the Northern Territory (NT), whose 30% Aboriginal population have some of the highest prevalence of mental-illness in Australia (Black, et-al., 2015). Far from progressing towards the precision psychiatry envisioned by Insel (2014), it finds little convincing evidence to support an exclusively biomedical approach. Further, it finds considerable, concerning evidence of a flawed paradigm of care, and calls for a wider approach that encompasses somatic, personal, social, environmental and cultural factors.
Since as early as 1845 when Edward Daniel wrote of the role of a diseased brain in “Impulsive Insanity” (Daniel, 1845), the biomedical-model has conceptualised psychopathology as having physical causes and, given suitable technology, physical treatments (Dworkin, 2011). Early successes from the biomedical approach include discovering that two disorders previously thought to be entirely psychogenic—general paresis, and pellagra—are of organic origin: syphilis, and Vitamin B deficiency respectively (Tsay, 2013), undoubtedly saving many lives. Subsequent advances through neuroscience, genetics, and biology have expanded our knowledge of the human body in ways previously unimagined: fMRI and other imaging techniques show not only the structure of the brain but its intricate functioning, to the point of “neural mind-reading” (Goldstein, 2015, pp.145-149). We understand in detail how the brains of people with mental disorders differ: for example, people suffering post-traumatic stress disorder (PTSD) have distinct irregularities in their anterior cingulate, hippocampus, and amygdala (Baldaçara, et-al., 2014; Akiki, et-al., 2017; Logue, et-al., 2018); auditory hallucinations—the hearing of voices common in schizophrenia— are typified by increased activity the auditory cortex, a general pattern of reduced connectivity/plasticity in grey matter, and cortical thinning in white matter (Bohlken, Hugdahl, & Sommer, 2017); geneticists have discovered that people with a particular variation of the 5-HTT gene are more prone to developing depression (Kring, 2018). Discoveries such as these have helped target treatments and diagnoses. In the past decade biomarker research has intensified, with over 32,000 patent applications for diagnosis and prognosis of bipolar disorder being lodged; 47,000 for schizophrenia; and over 100,000 for depression (Stellrink & Meisenzahl, 2017).
Such advances could intuitively be expected to deliver, over time, an improvement in societal mental wellbeing, and a decline in the impact and burden of mental-illness. Yet relevant literature shows that, to date, such developments are far from generally impactful. For example, whilst biomedical explanations can decrease suffering through reducing shame, self-blame, and stigma associated with mental-illness, they also lead to increased feelings of helplessness and pessimism, greater perceived dangerousness of people with mental-illness; and decreased empathy from others (Gershkovich, Deacon, & Wheaton, 2018; Haslam & Kvaale, 2015)
Of concern is that certain basic assumptions of the biomedical model appear flawed. For example, the chemical imbalance theory of depression, and subsequent research supporting the claimed action of SSRIs has been firmly debunked (Lacasse & Leo, 2015; Moncrieff, 2015; Gotzsche, 2015; Cipriani, et-al., 2018; Hengartner M. , 2017; Hengartner, Angst, & Wulf, 2018). Some research suggests that SSRI efficacy—albeit just slightly better than placebo—may be due instead to its action of neurogenesis on the hippocampus (Boldrini, Underwood, Hen, Rosoklija, & Dwork, 2009). However, more recent research attributes it to patient expectations (Faria, et-al., 2017). Yet the chemical imbalance legacy is pervasive: for example, an Australian guide for consumers and carers states, “Depression involves changes in brain chemistry [..]. Antidepressant medicines can correct the imbalance of chemicals in the brain until such time as the natural balance is restored” (RANZCP, 2005, p.5); and SSRIs continue to be the first-line treatment for depression (Malhi, et-al., 2015).
The RANZCP stance might be one reason why Australia’s antidepressant use increased almost 400% from 1990 to 2007 (Mant, et-al., 2004; Hollingworth, Burgess, & Whiteford, 2010); however, there appears to be minimal corresponding benefit. Australians’ psychological distress has not improved (Atlantis, Sullivan, Sartorius, & Almeida, 2012; ABS, 2015a) and is considerably higher for NT young indigenous people (32% versus 11%) (Davidson, Nagel, & Singh, 2017). Psychological disability has increased (ABS, 2015b) and anxiety has increased (Reavley, Jorm, Cvetkovski, & Mackinnon, 2011), as has the prevalence of depression (Goldney, Eckert, Hawthorne, & Taylor, 2010). Moreover, these increases are not related to greater public awareness or willingness to disclose (Jorm, Patten, Brugha, & Mojtabai, 2017).
Worldwide, prevalence of mental-illness and symptoms has increased, despite substantially greater use of psychiatric medicine, particularly antidepressants (Jorm, et-al., 2017; Kessler, et-al., 2005). Depression is now the leading cause of disability around the world and increasing annually; while depressive disorders are the single largest contributor to nonfatal health loss globally (WHO, 2017; Friedrich, 2017). Chronicity of depression—life-long episodes of relapse—previously thought to occur in approximately 50% of patients (Whitaker, 2015), is now the norm at 83%, as is the likelihood of switching to other psychiatric disorders (Verhoeven, et-al., 2017). Evidence from as far back as 1994 suggests antidepressant use increases chronicity (Fava G. , 1994; Fava & Offidani, 2011; Coupland, et-al., 2018; Hengartner M. , 2017; Hengartner, Angst, & Wulf, 2018).
If people are taking more drugs without getting better and, in many cases, getting worse, for longer, what are the drugs doing? Fava & Offidani (2011) find that antidepressants are effective to some extent in treating first depressive episodes, but not effective in preventing relapse, and can trigger symptomatic worsening and, in some cases, bipolar mania. They explain this by the “oppositional model of tolerance”, which suggests that SSRIs sensitise the brain’s natural serotonergic system: presynaptic neurons put out less serotonin, and post-synaptic neurons decrease the density of their receptors, resulting in a long-lasting “low serotonin” state, which can increase symptoms and likelihood of relapse when medication is withdrawn. The oppositional model of tolerance suggests that, rather than fixing known problems, long-term use of psychiatric drugs may worsen or create them. This has been verified by a recent longitudinal study into depression that followed 4,547 people over 30 years through seven assessment waves, finding that antidepressant use correlated strongly to poorer long-term outcomes, and that “a neurobiological mechanism that may causally explain these findings is the oppositional model of tolerance by Fava” (Hengartner, Angst, & Wulf, 2018).
Adverse outcomes are not limited to depression: antidepressants almost double the risk for developing bipolar disorder (Patel, et-al., 2015) and, for those with bipolar, can worsen symptoms, mood swings, and chronicity (Beyer, 2018). Antidepressant use is associated with significantly increased risk of fracture, falls, traffic accidents, bleeding, and unexplained death (Coupland, et-al., 2018). SSRIs, used to treat a wide range of disorders in addition to depression, carry an increased risk of severe bleeding of at least 32% (Laporte, et-al., 2017). Of particular relevance to the NT, this risk increases to 800% in patients with chronic kidney disease (Iwagami, et-al., 2018)[1]. SSRI use can also lead to increased suicidality (Nischal, Pripatha, Nischal, & Trivedi, 2012) and completed suicide (Larsson, 2017).
Nor are adverse outcomes limited to antidepressants. Litrell (2017) cites several longitudinal studies confirming that long-term use of antipsychotics in people with schizophrenia leads to poorer long-term outcomes, higher likelihood of relapse, and higher likelihood of psychotic symptoms than those who discontinue medication. Gotzsche (2015) cites numerous studies that lead him to conclude “psychiatric drugs are so harmful that they kill more than half a million people every year …. [and are] the third leading cause of death, after heart disease and cancer.” Certainly there is clear evidence Australians’ mental-health has not improved under the biomedical-model, and particularly not for Indigenous Australians (Black, et-al., 2015; Nasir, et al., 2018).
Threads of explanation for this from the literature point to potential biases in research and publication, correlation not causality, biomedical reductionism, and conflicts of interest. Cipriani and colleagues (2018) found, in a meta-analysis of 522 clinical trials of SSRIs, that 81% had moderate to high bias. Similarly, of 131 clinical trials reviewed by Jakobsen and colleagues (2017) all had high risk of bias. Turner and colleagues (2012; 2008) found strong evidence of publication bias, although the magnitude of bias for antipsychotics was less than that for antidepressants. Bias has also emerged in biomarker research for bipolar disorder (Carvalho, et-al., 2016) and schizophrenia (Belbasis, et-al., 2018). Methodological issues and bias have been found in imaging and genetics studies of mental disorders (Pereira, et-al., 2018). Hengartner (2017) finds that reliance on industry-funding has led to uncritical approval of drugs, unblinding of outcome assessors, reporting flaws, publication and reporting bias, concealment and recoding of serious adverse events, a systematic overstatement of efficacy, and understatement of harm.
A critical analysis might suggest that the biomedical industry may have mistaken correlations for causations: for example, the brain characteristics of a person with PTSD (anomalies in anterior cingulate, hippocampus, and amygdala) could just as much result from PTSD, as cause it. Assuming people have PTSD because they have the markers of PTSD points to circular reasoning. Biomedical reductionism does not satisfactorily explain, for example, why prevalence of PTSD in some Aboriginal populations is 32% to 55%; nor why the overall rates of mental-illness are so alarmingly high (Heffernan, et-al., 2015; Black, et-al., 2015; Nasir, et-al., 2018). For PTSD, the name itself—post-traumatic stress disorder—is a clue: biomedical explanations fail to account for the key aetiological factor of traumatic stress. Nor do biomedical explanations account for suicide in young NT Aboriginal men being five times higher than non-Aboriginal; nor the NT child suicide rate being 23 times higher than the rest of Australia (Robinson, Silburn, & Leckning, 2011). These imbalances are not biochemical, and are not reducible to biological causes. Alternative explanations are needed.
As psychiatrist Dr. Allen Frances points out in “Saving Normal” (2013), the ‘fight against cancer’ was relatively futile until we started making it the ‘fight against smoking’, that is, against the leading cause of cancer. Similarly, the fight against mental-illness is liable to be relatively futile without treating causes rather than symptoms. Mental-illness is influenced by many more factors than somatic anomalies, including personal, social, environmental and cultural factors (Kring, 2018). Personal determinants include self-esteem, sense of agency, positive experiences of early bonding, attachment, relationships, communication, and feelings of acceptance (WHO, 2004). Social determinants include living conditions, poverty, education, employment, and experiences with racism and power relationships (WHO, 2014). The biomedical-model reduces mental-illness to somatic symptoms, and this possibly amounts to a flawed paradigm of care that neglects these more critical, complex, and causal factors.
An alternative model that offers a more holistic view of mental-health is the biopsychosocial model proposed by George Engel (1977), although this has been criticised for having “Western” bias (Dudgeon & Bray, 2018), for being conceptually confused, and presenting difficulties in clinical application (Ghaemi, 2009). Although the biopsychosocial model may not adequately account for the spiritual and cultural dimensions of Aboriginal Australia, when augmented with Indigenous ‘ways of knowing and being’, it has shown promise in improving Aboriginal mental-health (Vance, et-al., 2017; Dudgeon & Bray, 2018).
In conclusion, evidence that the biomedical-model has substantial validity or utility in improving mental-health in Australia is not convincing, and particularly in the NT Aboriginal population where mental-health needs remain unmet (Gopalkrishnan, 2018). Recent evidence suggests that continuing to rely on a fundamentally biomedical approach will result in even poorer outcomes in the long term (Hengartner, Angst, & Wulf, 2018; Littrell, 2017). Emerging evidence from Australia shows promise that, by combing culturally and spiritually appropriate interventions with the biopsychosocial model, significantly improved mental-health amongst Aboriginal people is feasible (Vance, et-al., 2017; Dudgeon & Bray, 2018).
References
ABS. (2015a). 4364.0.55.001 – National Health Survey: First Results, 2014-15. Canberra: Australian Bureau of Statistics. Retrieved from http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by%20Subject/4364.0.55.001
ABS. (2015b). Psychological Disability, 2012 – 4433.0.55.004. Canberra: Australian Bureau of Statistics. Retrieved from http://www.abs.gov.au/AUSSTATS/abs@.nsf/Latestproducts/4433.0.55.004
Akiki, T. J., Averill, C. L., Wrocklage, K. M., Schweinsburg, B., Scott, J. C., Martini, B., . . . Abdallah, C. G. (2017, Aug). The Association of PTSD Symptom Severity With Localized Hippocampus and Amygdala Abnormalities. Chronic Stress, 1(10). doi:https://doi.org/10.1177/2470547017724069
Atlantis, E., Sullivan, T., Sartorius, N., & Almeida, O. (2012). Changes in the prevalence of psychological distress and use of antidepressants or anti-anxiety medications associated with comorbid chronic diseases in the adult Australian population, 2001-2008. Australian & New Zealand Journal of Psychiatry, 46(5), 445-456. doi:doi.org/10.1177%2F0004867411433218
Baldaçara, L., Zugman, A., Araújo, C., Cogo-Moreira, H., Lacerda, A. L., Schoedl, A., . . . Jackowski, A. P. (2014). Reduction of anterior cingulate in adults with urban violence- related PTSD. Journal of Affective Disorders, 168, 13-20. doi:https://doi.org/10.1016/j.jad.2014.06.036
Belbasis, L., Köhler, C., Stefanis, N., Stubbs, B., van Os, J., Vieta, E., . . . Evangelou, E. (2018, Feb). Risk factors and peripheral biomarkers for schizophrenia spectrum disorders: an umbrella review of meta-analyses. Acta Psychiatrica Scandinavica, 137(2), 88-97. doi:doi-org.ezproxy.cdu.edu.au/10.1111/acps.12847
Beyer, J. (2018). The Use of Antidepressants in Bipolar Depression. In Handbook of Experimental Parmacology. Berlin: Springer. doi:doi.org/10.1007/164_2018_155
Black, E. B., Ranmuthugala, G., Kondalsamy-Chennakesavan, S., Toombs, M. R., Nicholson, G. C., & Kisely, S. (2015). A systematic review: Identifying the prevalence rates of psychiatric disorder in Australia’s Indigenous populations. Australian and New Zealand Journal of Psychiatry, 49(5), 412-429. doi:10.1177/0004867415569802
Bohlken, M., Hugdahl, K., & Sommer, I. (2017). Auditory verbal hallucinations: neuroimaging and treatment. Psychological Medicine, 47, 199-208. doi:10.1017/S003329171600115X
Boldrini, M., Underwood, M. D., Hen, R., Rosoklija, G. B., & Dwork, A. (2009). Antidepressants increase neural progenitor cells in the human hippocampus. Neuropsychopharmacology, 34(11), 2376–2389. doi:10.1038/npp.2009
Carvalho, A. F., Köhler, C. A., Fernandes, B. S., Quevedo, J., Miskowiak, K. W., Brunoni, A. R., . . . Berk, M. (2016). Bias in emerging biomarkers for bipolar disorder. Psychological Medicine, 46(11), 2287-2297. doi:10.1017/S0033291716000957
Cipriani, A., Furukawa, T. A., Salanti, G., Chaimani, A., Atkinson, L. Z., Ogawa, Y., . . . Higgins, J. P. (2018, Apr). Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. The Lancet, 391(10128), 1357-1366. doi: 10.1016/S0140-6736(17)32802-7
Coupland, C., Hill, T., Morriss, R., Moore, M., Arthur, A., & Hippisley-Cox, J. (2018, Mar). Antidepressant use and risk of adverse outcomes in people aged 20-64 years: Cohort study using a primary care database. BMC Medicine, 16(1). doi:10.1186/s12916-018-1022-x
Daniel, E. (1845). On Impulsive Insanity. Provincial Medical & Surgical Journal. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559244/pdf/provmedsurgj00254-0001.pdf
Davidson, B., Nagel, T., & Singh, G. (2017). Life, lifestyle and location: examining the complexities of psychological distress in young adult Indigenous and non-Indigenous Australians. Journal of Developmental Origins of Health and Disease, 8(5), 541-549. doi:10.1017/S2040174417000162
Dudgeon, P., & Bray, A. (2018, Apr). Indigenous Healing Practices in Australia. Women & Therapy, 97-113. doi: 10.1080/02703149.2017.1324191
Dworkin, R. J. (2011). Applying Theory to the Study of Mentally Ill Persons. In Researching Persons With Mental Illness (pp. 11-24). Thousand Oaks: Sage. doi:dx.doi.org/10.4135/93781412985741
Engel, G. L. (1977, Apr). The Need For A New Medical Model: A Challenge for Biomedicine. Science, 196, 129-197.
Faria, V., Gingnell, M., Hoppe, J. M., Hjorth, O., Alaie, I., Frick, A., . . . Larsson, E.-M. (2017). Do You Believe It? Verbal Suggestions Influence the Clinical and Neural Effects of Escitalopram in Social Anxiety Disorder: A Randomized Trial. EBioMedicine, 24, 179-188. doi:10.1016/j.ebiom.2017.09.031
Farre, A., & Rapley, T. (2017). The New Old (and Old New Medical Model: Four Decades Navigating the Biomedical and Psychosocial Understandings of Health and Illness. Healthcare, 5(88). doi:10.3390/healthcare5040088
Fava, G. (1994). Do Antidepressant and Antianxiety Drugs Increase Chronicity in Affective Disorders? Psychotherapty and Psychosomatics, 61, 125-131. doi:doi.org/10.1159/000288880
Fava, G. A., & Offidani, E. (2011). The mechanisms of tolerance in antidepressant action. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 35, 1593-102. doi:10.1016/j.pnpbp.2010.07.026
Frances, A. (2013). Saving Normal: An Insider’s Revolt Against Out-of-Control Psychiatric Diagnosis, DSM-5, Big Pharma, and the Medicalization of Ordinary Life. William Morrow Paperbacks.
Friedrich, M. (2017, Apr). Depression is the Leading Cause of Disability Around the World. Global Health, 317(15), 1517. doi:10.1001/jama.2017.3826
Gershkovich, M., Deacon, B. J., & Wheaton, M. G. (2018, Mar). Biomedical causal attributions for obsessive-compulsive disorder: Associations with patient perceptions of prognosis and treatment expectancy. Journal of Obsessive-Compulsive and Related Disorders, 18, 81-85. doi:doi.org/10.1016/j.jocrd.2018.03.001
Ghaemi, N. (2009, Jul). The rise and fall of the bio-psychosocial model. British Journal of Psychiatry, 195(1), 3-4. doi:10.1192/bjp.bp.109.063859
Goldney, R., Eckert, K., Hawthorne, G., & Taylor, A. (2010, Oct). Changes in the prevalence of major depression in an Australian community sample between 1998 and 2008. Australian & New Zealand Journal of Psychiatry, 44(10), 901-910. doi:10.3109/00048674.2010.490520
Goldstein, E. (2015). Cognitive Psychology: Connecting Mind, Research and Everyday Experience (4th ed.). Cengage Learning.
Gopalkrishnan, N. (2018). Cultural Diversity and Mental Health: Considerations for Policy and Practice. Frontiers in Public Health. doi:doi.org/10.3389/fpubh.2018.00179
Gotzsche, P. (2015). Deadly Psychiatry and Organized Denial. Copenhagen: People’s Press. Retrieved from http://www.deadlymedicines.dk/wp-content/uploads/2014/10/G%C3%B8tzsche-Deadly-Psychiatry-chapter-1.pdf
Haslam, N., & Kvaale, E. P. (2015, Oct). Biogenetic Explanations of Mental Disorder: The Mixed-Blessings Model. Current Directions in Psychological Science, 24(5), 399-404. doi:10.1177/0963721415588082
Heffernan, E., Andersen, K., Davidson, F., & Kinner, S. A. (2015, Dec). PTSD Among Aboriginal and Torres Strait Islander People in Custody in Australia: Prevalence and Correlates. Journal of Traumatic Stress, 28(6), 523-530. doi:10.1002/jts.22051
Hengartner, M. (2017). Methodological Flaws, Conficts of interest, and Scientifc Fallacies: implications for the evaluation of Antidepressants’ efficacy and harm. Frontiers in Psychiatry, 8(275). doi: 10.3389/fpsyt.2017.00275
Hengartner, M., Angst, J., & Wulf, R. (2018, April). Antidepressant use prospectively realtes to a poorer long-term outcome of depression: Results from a Prospective Community Cohort Over 30 Years. Psychotherapy and Psychosomatics, 87(3), 181-183. doi:10.1159/000488802
Hollingworth, S. A., Burgess, P. M., & Whiteford, H. A. (2010, Jun). Affective and anxiety disorders: prevalence, treatment and antidepressant medication use. Australian & New Zealand Journal of Psychiatry, 44(6), 513-519. doi:10.3109/00048670903555138
Insel, T. R. (2014, Apr). The NIMH Research Domain Criteria (RDoC) Project: Precision Medicine for Psychiatry. American Journal of Psychiatry, 171(4), 395-397. doi:10.1176/appi.ajp.2014.14020138
Iwagami, M., Tomlinson, L. A., Mansfield, K. E., Douglas, I. J., Smeeth, L., & Nitsch, D. (2018, Sep). Gastrointestinal bleeding risk of selective serotonin reuptake inhibitors by level of kidney function: A population-based cohort study. British Journal of Clinical Pharmacology, 84(9), 2142-2152. doi:10.1111/bcp.13660
Jorm, A. F., Patten, S. B., Brugha, T. S., & Mojtabai, R. (2017, Feb). Has increased provision of treatment reduced the prevalence of common mental disorders? Review of the evidence from four countries. World Psychiatry, 16(1), 90-99. doi:10.1002/wps.20388
Kessler, R. C., Demler, O., Frank, R. G., Olfson, M., Pincus, H. A., Walters, E. E., . . . Zaslavsky, A. M. (2005, June). Prevalence and treatment of mental disorders, 1990 to 2003. New England Journal of Medicine, 352(24), 2515-2523. doi:10.1056/NEJMsa043266
Kring, A. (2018). Abnormal Psychology (First Australasian ed.). Hoboken, United States: John Wiley & Sons.
Lacasse, J. R., & Leo, J. (2015). Antidepressants and the Chemical Imbalance Theory of Depression: A Reflection and Update on the Discourse. The Behaviour Therapist, 38(7), 206-214.
Laporte, S., Chapelle, C., Caillet, P., Beyens, M.-N., Bellet, F., Delavenne, X., . . . Bertoletti, L. (2017, Apr). Bleeding risk under selective serotonin reuptake inhibitor (SSRI) antidepressants: A meta-analysis of observational studies. Pharmacological Research, 118, 19-32. doi:dx.doi.org/10.1016/j.phrs.2016.08.017
Larsson, J. (2017). Antidepressants and suicide among young women in Sweden 1999-2013. International Journal of Risk and Safety in Medicine, 29(1-2), 101-06. doi:10.3233/JRS-170739
Lilienfeld, S. O., & Treadway, M. T. (2016). Clashing Diagnostic Approaches: DSM-ICD Versus RDoC. Annual Review of Clinical Psychology, 12, 435-463. doi:10.1146/annurev-clinpsy-021815-093122
Littrell, J. (2017). Questioning the Medical Model of Mental Health. Journal of Constructivist Psychology, 30(4), 456-464. doi:10.1080/10720537.2016.1268080
Logue, M. W., van Rooij, S. J., Dennis, E. L., Davis, S. L., Hayes, J. P., Stevens, J. S., . . . Peverill. (2018, Feb). Smaller Hippocampal Volume in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study: Subcortical Volumetry Results From Posttraumatic Stress Disorder Consortia. Biological Psychiatry, 83(3), 244-253. doi: 10.1016/j.biopsych.2017.09.006
Malhi, G. S., Bassett, D., Boyce, P., Bryant, R., Fitzgerald, P. B., Fritz, K., . . . Singh, A. B. (2015, Dec). Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders. Australian and New Zealand Journal of Psychiatry, 49(12), 1087-1206. doi:10.1177/0004867415617657
Mant, A., Rendle, V. A., Hall, W. D., Mitchell, P. B., Montgomery, W. S., McManus, P. R., & Hickie, I. B. (2004). Making new choices about antidepressants in Australia: the long view 1975–2002. The Medical Journal of Australia, 181(7), S21-24. Retrieved from https://www.mja.com.au/journal/2004/181/7/making-new-choices-about-antidepressants-australia-long-view-1975-2002
Moncrieff, J. (2015, Oct). The Myths and Realities of Drug Treatment for Mental Disorders. The Behavior Therapist, 214-217.
Nasir, B. F., Toombs, M. R., Kondalsamy-Chennakesavan, S., Kisely, S., Gill, N. S., Black, E., . . . Nicholson, G. C. (2018). Common mental disorders among Indigenous people living in regional, remote and metropolitan Australia: a cross-sectional study. BMJ Open, 8(6). doi:10.1136/bmjopen-2017-020196
Nischal, A., Pripatha, A., Nischal, A., & Trivedi, J. (2012). Suicide and Antidepressants: What Current Evidence Indicates. Mes Sana Monographs, 10(1), 33-44. doi:10.4103/0973-1229.87287
Patel, R., Reiss, P., Shetty, H., Broadbent, M., Stewart, R., Mcguire, P., & Taylor, M. (2015). Do antidepressants increase the risk of mania and bipolar disorder in people with depression? A retrospective electronic case register cohort study. BMJ Open, 5(12), Dec. doi:10.1136/bmjopen-2015-008341
Pereira, L. P., Köhler, C. A., Stubbs, B., Miskowiak, K. W., Morris, G., de Freitas, B. P., . . . Carvalho, A. F. (2018). Imaging genetics paradigms in depression research: Systematic review and meta-analysis. Progress in Neuropsychopharmacology & Biological Psychiatry, 86, 102-113. doi:10.1016/j.pnpbp.2018.05.012
RANZCP. (2005). Coping With Depression: Australian treatment guide for consumers and carers. Melbourne: Royal Australian and New Zealand College of Psychiatrists. Retrieved Sep 21, 2018, from http://www.health.gov.au/internet/main/publishing.nsf/content/88FB535B0456C66FCA257BF0001CFB7E/$File/coping.pdf
Reavley, N., Jorm, A., Cvetkovski, S., & Mackinnon, A. (2011, Sep). National depression and anxiety indices for Australia. Australian & New Zealand Journal of Psychiatry, 45(9), 780 -787. doi:10.3109/00048674.2011.607130
Robinson, G., Silburn, S., & Leckning, B. (2011). Sucide of Children and Youth in the Northern Territory 2006 – 2010: Public Release Report – for the Child Deaths Review and Prevention Committ. Darwin: Menzies School of Health Research- Centre for Child Development and Education. Retrieved from https://occ.nt.gov.au/__data/assets/pdf_file/0009/440829/nt-youth-suicide-public-release-final-with-isbn.pdf
Stellar, E. (1957). Physiological Psychology. Annual Review of Psychology, 81(1), 415-436. doi:10.1146/annurev.ps.08.020157.002215
Stellrink, A., & Meisenzahl, E. (2017, Apr). Big data market analysis of e-health in medical neuroscience. European Psychiatry, 41, S39-S39. doi:10.1016/j.eurpsy.2017.01.178
Tsay, C. (2013, June). Julius Wagner-Jauregg and the legacy of malarial therapy for the treatment of general paresis. Yale Journal of Biological Medicine, 86(2), 245-254.
Turner, E. H., Knoepflmacher, D., & Shapley, L. (2012). Publication bias in antipsychotic trials: an analysis of efficacy comparing the published literature to the US Food and Drug Administration database. PLoS Medicine, 9(3). doi:10.1371/journal.pmed.1001189
Turner, E. H., Matthews, A. M., Linardatos, E., Tell, R. A., & Rosenthal, R. (2008). Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy. The New England Journal of Medicine, 358, 252-260. doi:10.1056/NEJMsa065779
Vance, A., Mcgaw, J., Winther, J., Rayner, M., White, S., & Smith, A. (2017, Apr). Mental health care for Indigenous young people: moving culture from the margins to the centre. Australasian Psychiatry, 25(2), 157-160. doi:10.1177/1039856216671655
Verhoeven, J., Verduijn, J., Milaneschi, Y., Beekman, A., & Penninx, B. (2017). The clinical course of depression: Chronicity is the rule rather than the exception. European Psychiatry, 41, S144. doi:10.1016/j.eurpsy.2017.01.1986
Whitaker, R. (2015, Oct). Anatomy of an Epidemic: The History and Science of a Failed Paradigm of Care. The Behaviour Therapist, 38(7), 192-198.
WHO. (2004). Promoting mental health : concepts, emerging evidence, practice : summary report / a report from the World. Department of Mental Health and Substance Abuse in collaboration with the Victorian Health Promotion Foundation (VicHealth) and the University of Melbourne. Melbourne: World Health Organization. Retrieved Sep 21, 2018, from http://www.who.int/mental_health/evidence/en/promoting_mhh.pdf
WHO. (2014). Social determinants of mental health. World Health Organization and Calouste Gulbenkian Foundation. Geneva: World Health Organisation. Retrieved from http://apps.who.int/iris/bitstream/handle/10665/112828/9789241506809_eng.pdf;jsessionid=3679C8F9DD61656E83435760AB723A1D?sequence=1
WHO. (2017). Depression and Other Common Mental Disodres: Global Health Estimates. World Health Organisation. Retrieved from http://apps.who.int/iris/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf
[1] This is particularly concerning given that the NT Aboriginal population has one of the highest rates of chronic kidney disease in the world (Lawton, et al., 2015), and alarmingly high rates of mental disorders (Heffernan, et al., 2015; Black, et al., 2015).
