The PHEM-B toolbox of methods for incorporating the influences on Behaviour into Public Health Economic Models.
Behaviour
Complexity
Economic
Maintenance
Methods
Psychology
Public health
Simulation
Sociology
Theory
Journal
BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562
Informations de publication
Date de publication:
12 Oct 2024
12 Oct 2024
Historique:
received:
20
10
2023
accepted:
30
09
2024
medline:
13
10
2024
pubmed:
13
10
2024
entrez:
12
10
2024
Statut:
epublish
Résumé
It is challenging to predict long-term outcomes of interventions without understanding how they work. Health economic models of public health interventions often do not incorporate the many determinants of individual and population behaviours that influence long term effectiveness. The aim of this paper is to draw on psychology, sociology, behavioural economics, complexity science and health economics to: (a) develop a toolbox of methods for incorporating the influences on behaviour into public health economic models (PHEM-B); and (b) set out a research agenda for health economic modellers and behavioural/ social scientists to further advance methods to better inform public health policy decisions. A core multidisciplinary group developed a preliminary toolbox from a published review of the literature and tested this conceptually using a case study of a diabetes prevention simulation. The core group was augmented by a much wider group that covered a broader range of multidisciplinary expertise. We used a consensus method to gain agreement of the PHEM-B toolbox. This included a one-day workshop and subsequent reviews of the toolbox. The PHEM-B toolbox sets out 12 methods which can be used in different combinations to incorporate influences on behaviours into public health economic models: collaborations between modellers and behavioural scientists, literature reviewing, application of the Behaviour Change Intervention Ontology, systems mapping, agent-based modelling, differential equation modelling, social network analysis, geographical information systems, discrete event simulation, theory-informed statistical and econometric analyses, expert elicitation, and qualitative research/process tracing. For each method, we provide a description with key references, an expert consensus on the circumstances when they could be used, and the resources required. This is the first attempt to rigorously and coherently propose methods to incorporate the influences on behaviour into health economic models of public health interventions. It may not always be feasible or necessary to model the influences on behaviour explicitly, but it is essential to develop an understanding of the key influences. Changing behaviour and maintaining that behaviour change could have different influences; thus, there could be benefits in modelling these separately. Future research is needed to develop, collaboratively with behavioural scientists, a suite of more robust health economic models of health-related behaviours, reported transparently, including coding, which would allow model reuse and adaptation.
Sections du résumé
BACKGROUND
BACKGROUND
It is challenging to predict long-term outcomes of interventions without understanding how they work. Health economic models of public health interventions often do not incorporate the many determinants of individual and population behaviours that influence long term effectiveness. The aim of this paper is to draw on psychology, sociology, behavioural economics, complexity science and health economics to: (a) develop a toolbox of methods for incorporating the influences on behaviour into public health economic models (PHEM-B); and (b) set out a research agenda for health economic modellers and behavioural/ social scientists to further advance methods to better inform public health policy decisions.
METHODS
METHODS
A core multidisciplinary group developed a preliminary toolbox from a published review of the literature and tested this conceptually using a case study of a diabetes prevention simulation. The core group was augmented by a much wider group that covered a broader range of multidisciplinary expertise. We used a consensus method to gain agreement of the PHEM-B toolbox. This included a one-day workshop and subsequent reviews of the toolbox.
RESULTS
RESULTS
The PHEM-B toolbox sets out 12 methods which can be used in different combinations to incorporate influences on behaviours into public health economic models: collaborations between modellers and behavioural scientists, literature reviewing, application of the Behaviour Change Intervention Ontology, systems mapping, agent-based modelling, differential equation modelling, social network analysis, geographical information systems, discrete event simulation, theory-informed statistical and econometric analyses, expert elicitation, and qualitative research/process tracing. For each method, we provide a description with key references, an expert consensus on the circumstances when they could be used, and the resources required.
CONCLUSIONS
CONCLUSIONS
This is the first attempt to rigorously and coherently propose methods to incorporate the influences on behaviour into health economic models of public health interventions. It may not always be feasible or necessary to model the influences on behaviour explicitly, but it is essential to develop an understanding of the key influences. Changing behaviour and maintaining that behaviour change could have different influences; thus, there could be benefits in modelling these separately. Future research is needed to develop, collaboratively with behavioural scientists, a suite of more robust health economic models of health-related behaviours, reported transparently, including coding, which would allow model reuse and adaptation.
Identifiants
pubmed: 39395958
doi: 10.1186/s12889-024-20225-1
pii: 10.1186/s12889-024-20225-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2794Subventions
Organisme : National Institute for Health and Care Research
ID : NIHR301406
Organisme : Economic and Social Research Council
ID : ES/Y001907/1
Organisme : Economic and Social Research Council
ID : ES/L011921/1
Organisme : NIAAA NIH HHS
ID : R01AA024443
Pays : United States
Organisme : Cancer Research UK
ID : PRCRPG-Nov21\100002
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 218462/Z/19/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 218462/Z/19/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 218462/Z/19/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 218462/Z/19/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S037578/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC\_UU\_00022/5
Pays : United Kingdom
Informations de copyright
© 2024. The Author(s).
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