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Psychiatry in public mental health: easy to say, but harder to achieve

Published online by Cambridge University Press:  02 January 2018

David M. Foreman*
Affiliation:
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Summary

Psychiatrists are currently ill equipped to exploit the growing interest in public mental health. Training, service infrastructure and organisational links are deficient, which will impede population-based interventions. However, the potential benefits make correcting this worthwhile.

Type
Editorials
Copyright
Copyright © Royal College of Psychiatrists, 2015 

Background

Although psychiatric engagement with public health issues is long-standing, explicit reference to public mental health is recent. In the UK, the Department of Health identified it as a key policy on their website in 2011, and the Royal College of Psychiatrists' Special Interest Group in Public Mental Health was founded in 2012. In the USA, despite governmental health policy being more fragmented, the first dedicated textbook on the topic Reference Eaton1 was published in the same year. Although psychiatry and public health share many mental health interests, public mental health cannot be assimilated, as with other psychiatric specialities, to an application of psychiatric principles in a different operating environment, and a survey by Public Health England in 2013 found that, of all specialties, psychiatry had the lowest overlap between its training and that of public health. Reference Boak and Moore2

The need for a different approach

The phenomenological approach underpinning the diagnosis and treatment of psychiatric disorders means that these diagnoses are identified in individuals, who are also the unit of treatment. This approach is maintained even when psychiatry is delivered in the community at large, for example, through primary care, although the delivery models may be described as ‘population-based’. Reference Cowley, Dunaway, Forstein, Frosch, Han and Joseph3 Public mental health, in contrast, concerns itself with the mental health and well-being of populations as a whole, and the difference this introduces cannot be overstated. It is now accepted that the proportions of different disorders, as well as severity, vary with progress through the mental healthcare system, so assessing the mental health of populations needs to capture distribution, as well as description, using an appropriate metric. Thus, questionnaire assessments, of secondary use in individual diagnosis, become the primary tool for assessing the mental health of populations. Psychiatric epidemiology has managed this difference by applying cut-offs to questionnaire scores to approximate patient groupings. However, when using scalar measures of physical or mental disorders, population mean scores predict associated disorder prevalences, Reference Goodman and Goodman4 suggesting either may be used to estimate population health. This gives public mental health a significant conceptual advantage. For most psychiatrists, the detection and treatment of patients is the only way to reduce morbidity: for a public mental health practitioner this is but one route among many that might affect the population mean.

Health impact assessments

There are two main dimensions along which public mental health can extend the reach of conventional psychiatry, given that mental illness and mental well-being seem coterminous, at least for common disorders. Reference Huppert and So5 The first is to address population-level influences on well-being through policy advice, which may be evaluated by health impact assessments. Public Health England has been developing a methodology to include mental health – mental health impact assessments (MHIAs). There have been promising results, but the author lists of published MHIAs 6 suggest that psychiatrists are not typically engaged in their selection, design, deployment or feedback into policy. For example, Appendix 1 lists several individual and macro-economic factors affecting mental well-being, Reference Rodríguez-Pose and Maslauskaite7 some of which might be adjusted by judicious policy choice.

Appendix 1 makes two key points: much policy affecting mental well-being involves sectors outside psychiatry; and excess, as well as inadequate expenditure may harm mental health. Part of public health involves achieving the most cost-effective deployment of available health interventions, which emphasises good health economics. Even with good economic measurement, difficulties may arise when, as is common in public health, a health-related intervention is not provided by a health-based organisation. Based on 2009 prices, social and emotional learning programmes in schools costs £132 per child, borne by education. After 10 years, total public savings resulting from improved behaviour are £10 164. However, the total savings to education after this time are £186, Reference Knapp, McDaid and Parsonage8 so there is little incentive for education to further develop the programme, as costs are barely covered in its current form. Perverse incentives such as these may have contributed to the failure of significant public mental health interventions. MHIAs that include an economic component, promoted in government by appropriately qualified advisors, could recommend that those departments that obtain most economic benefit from interventions are the ones to pay for them, reducing such risks.

Logical framework matrix

The second dimension in public mental health – interventions across the whole population – is currently best discussed in children, where associations between population mean scores and prevalence have been published: for them, a 0.6 standard deviation reduction in population mean predicts a 1 unit decline in log-odds prevalence of psychiatric disorders. Reference Huppert and So5 So, whole-population interventions with effect sizes too small for clinic use could still produce worthwhile reductions in population prevalence. For example, a randomised controlled trial of a whole-school intervention for aggressive behaviour estimated a parent-reported effect size of 0.26. Reference Malti, Ribeaud and Eisner9 Assuming a population prevalence for behaviour disorders of 6.5% for boys Reference Meltzer, Gatward, Goodman and Ford10 the intervention could reduce this prevalence to 4.3%, a reduction of nearly 34%.

Most psychiatrists practice without relevant local epidemiology, which public health calls ‘health intelligence’ and regards as essential for planning appropriate service delivery. Much can be extrapolated from national epidemiology and service activity data, but the impact of locally important changes (such as the loss of a major employer or service reconfiguration) on communities is not directly measured. The complex data-set linkages necessary to detect these routinely are still in development, Reference Hollis, Martin, Amani, Cotton, Denis, Lewis and Davies11 so public mental health interventions, especially local ones, are currently difficult to evaluate. These evaluations are often of a different form to either conventional audit or research. Frequently, the intervention is well-understood, but the unknown is whether the intervention's environment will permit success, and how it might be favourably modified. A structure appropriate for these evaluations, the logical framework matrix, is shown at Appendix 2. Its cells are populated using the logical framework approach, 12 which is commonly used in international health and development, but not taught in domestic mental health delivery or research.

Early intervention

Another subtle, but significant difference between public health and psychiatry is in the use of the term ‘early intervention’. In psychiatry, particularly in relation to psychosis, early intervention refers to intervention when at least some (psychotic) symptoms are present, but significant disability (or the full syndrome) has not yet had time to manifest. Public health would call this secondary prevention, reserving the first term for interventions occurring early in the natural history of the disorder. In public mental health, these would typically be primary prevention programmes, applied to young children. For example, interventions to reduce the prevalence and impact of early trauma might ameliorate the subsequent development of psychiatric disorders. Reference Green, McLaughlin, Berglund, Gruber, Sampson and Zaslavsky13 In the UK, this distinction became practically important between 2005 and 2009, when there was both a 16.5% reduction in children aged 0–4 and an increase of 27% in in-patients aged 15+ being seen by Child and Adolescent Mental Health Services (CAMHS), based on (respectively) CAMHS mapping and hospital episode statistics, in the context of increasing concern about early intervention. The public health definition is harder for psychiatry to implement, as the very low base rates inevitably associated with these interventions make adequate effect sizes hard to demonstrate, and the relevant proxy for outcome may not be a psychiatric disorder at all. Reference Hamre, Pianta, Mashburn and Downer14 Overall, however, the evidence overwhelmingly supports the value and cost-effectiveness of perinatal and preschool public mental health interventions, for physical as well as mental health difficulties, across the whole population. Reference Foreman and Hulne-Dickens15 Therefore, interpretation of the government's focus on early intervention in psychiatric terms was associated with a reduction in the total amount of early intervention provided by psychiatry.

Conclusions

Training should thus, at a minimum, empower psychiatrists to effectively collaborate with public health colleagues in delivering population-level interventions, engage in MHIAs and coordinate goals. This is demanding because, as inspection of the journals cited in the HIA (Health Impact Assessment) Gateway 6 shows there is little professional overlap. Effective population informatics is the medical examination of public health, but much mental-health related UK data have limited resolution through infrequent collection and/or large geographical scale, so are most suited to evaluate large-scale interventions. Without more informatics investment, local interventions are likely to require dedicated evaluations, of a type that psychiatrists are not usually trained to undertake. Delivering local or large-scale population-level interventions also requires much closer integration between psychiatry and other community and societal institutions than currently, with more policy engagement. However, public mental health offers the possibility of reducing population prevalence of, at least, common psychiatric disorders by means other than a practically unachievable rate of diagnosis and treatment of individual cases, while simultaneously contributing to improvements in physical health, as the same risk factors affect both. In the absence of a ‘disruptive’ technological advance, which radically reduces the cost and improves the benefit of what can be provided from psychiatric clinics, adopting a public mental health approach to mental health service delivery and goals might be the best option for achieving further significant advances in mental healthcare.

Appendix 1

Association between economic variables and mental well-being

Individual
Income Sigmoid curve of happiness v. income = relative
relationship
Age U-curve, uplift from 40s+
Health Strong +ve relationship
Education Strong +ve relationship
Employment Students, pensioners and self-employed happier.
Long-term unemployed happier than short-term
unemployed
Gender Women happier
Marital status Married higher (very strong)
Number of children Not significant
Macroeconomic
Gross domestic product
per capita Higher is better, with some ceiling
Inequality of income Less is better, although may be tolerated
if stimulates growth
Inflation Less is better
Corruption Less better
Government spending Overall spend correlates negatively,
individual departmental spend (e.g. health)
positively
Decentralisation Less central control is better

Appendix 2

Logical framework matrix 12

Project description Objectively verifiable indicators
of achievement
Sources and means of verification Assumptions
Goal: what is the overall broader
impact to which the action will
contribute?
What are the key indicators related
to the overall goal?
What are the sources of information
for these indicators?
What are the external factors necessary
to sustain objectives in the long term?
Purpose: what is the immediate
development outcome at the end
of the project?
Which indicators clearly show that
the objective of the action has been
achieved?
What are the sources of information
that exist or can be collected?
What are the methods required to
get this information?
Which factors and conditions are
necessary to achieve that objective
(external conditions)?
Outputs: what are the specifically
deliverable results envisaged to
achieve the specific objectives?
What are the indicators to measure
whether and to what extent the
action achieves the expected results?
What are the sources of information
for these indicators?
What external conditions must be met
to obtain the expected results on
schedule?
Activities: what are the key activities
to be carried out and in what
sequence in order to produce the
expected results?
Means: what are the means required
to implement these activities,
e.g. personnel, equipment, supplies?
What are the sources of information
about action progress?
Costs: what are the action costs?
What preconditions are required before
the action starts?

References

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