Complex intervention modelling should capture the dynamics of adaptation.

BACKGROUND: Complexity has been linked to health interventions in two ways: first as a property of the intervention, and secondly as a property of the system into which the intervention is implemented. The former recognizes that interventions may consist of multiple components that act both independently and interdependently, making it difficult to identify the components or combinations of components (and their contexts) that are important mechanisms of change. The latter recognizes that interventions are implemented in complex adaptive systems comprised of intelligent agents who modify their behaviour (including any actions required to implement the intervention) in an effort to improve outcomes relative to their own perspective and objectives. Although an intervention may be intended to take a particular form, its implementation and impact within the system may deviate from its original intentions as a result of adaptation. Complexity highlights the challenge in developing interventions as effective health solutions. The UK Medical Research Council provides guidelines on the development and evaluation of complex interventions. While mathematical modelling is included in the guidelines, there is potential for mathematical modeling to play a greater role. DISCUSSION: The dynamic non-linear nature of complex adaptive systems makes mathematical modelling crucial. However, the tendency is for models of interventions to limit focus on the ecology of the system - the 'real-time' operation of the system and impacts of the intervention. These models are deficient by not modelling the way the system reacts to the intervention via agent adaptation. Complex intervention modelling needs to capture the consequences of adaptation through the inclusion of an evolutionary dynamic to describe the long-term emergent outcomes that result as agents respond to the ecological changes introduced by intervention in an effort to produce better outcomes for themselves. Mathematical approaches such as those found in economics in evolutionary game theory and mechanism design can inform the design and evaluation of health interventions. As an illustration, the introduction of a central screening clinic is modeled as an example of a health services delivery intervention. Complexity necessitates a greater role for mathematical models, especially those that capture the dynamics of human actions and interactions.

Responding to Young People's Health Risks in Primary Care: A Cluster Randomised Trial of Training Clinicians in Screening and Motivational Interviewing.

OBJECTIVE: To evaluate the effectiveness of a complex intervention implementing best practice guidelines recommending clinicians screen and counsel young people across multiple psychosocial risk factors, on clinicians' detection of health risks and patients' risk taking behaviour, compared to a didactic seminar on young people's health. DESIGN: Pragmatic cluster randomised trial where volunteer general practices were stratified by postcode advantage or disadvantage score and billing type (private, free national health, community health centre), then randomised into either intervention or comparison arms using a computer generated random sequence. Three months post-intervention, patients were recruited from all practices post-consultation for a Computer Assisted Telephone Interview and followed up three and 12 months later. Researchers recruiting, consenting and interviewing patients and patients themselves were masked to allocation status; clinicians were not. SETTING: General practices in metropolitan and rural Victoria, Australia. PARTICIPANTS: General practices with at least one interested clinician (general practitioner or nurse) and their 14-24 year old patients. INTERVENTION: This complex intervention was designed using evidence based practice in learning and change in clinician behaviour and general practice systems, and included best practice approaches to motivating change in adolescent risk taking behaviours. The intervention involved training clinicians (nine hours) in health risk screening, use of a screening tool and motivational interviewing; training all practice staff (receptionists and clinicians) in engaging youth; provision of feedback to clinicians of patients' risk data; and two practice visits to support new screening and referral resources. Comparison clinicians received one didactic educational seminar (three hours) on engaging youth and health risk screening. OUTCOME MEASURES: Primary outcomes were patient report of (1) clinician detection of at least one of six health risk behaviours (tobacco, alcohol and illicit drug use, risks for sexually transmitted infection, STI, unplanned pregnancy, and road risks); and (2) change in one or more of the six health risk behaviours, at three months or at 12 months. Secondary outcomes were likelihood of future visits, trust in the clinician after exit interview, clinician detection of emotional distress and fear and abuse in relationships, and emotional distress at three and 12 months. Patient acceptability of the screening tool was also described for the intervention arm. Analyses were adjusted for practice location and billing type, patients' sex, age, and recruitment method, and past health risks, where appropriate. An intention to treat analysis approach was used, which included multilevel multiple imputation for missing outcome data. RESULTS: 42 practices were randomly allocated to intervention or comparison arms. Two intervention practices withdrew post allocation, prior to training, leaving 19 intervention (53 clinicians, 377 patients) and 21 comparison (79 clinicians, 524 patients) practices. 69% of patients in both intervention (260) and comparison (360) arms completed the 12 month follow-up. Intervention clinicians discussed more health risks per patient (59.7%) than comparison clinicians (52.7%) and thus were more likely to detect a higher proportion of young people with at least one of the six health risk behaviours (38.4% vs 26.7%, risk difference [RD] 11.6%, Confidence Interval [CI] 2.93% to 20.3%; adjusted odds ratio [OR] 1.7, CI 1.1 to 2.5). Patients reported less illicit drug use (RD -6.0, CI -11 to -1.2; OR 0.52, CI 0.28 to 0.96), and less risk for STI (RD -5.4, CI -11 to 0.2; OR 0.66, CI 0.46 to 0.96) at three months in the intervention relative to the comparison arm, and for unplanned pregnancy at 12 months (RD -4.4; CI -8.7 to -0.1; OR 0.40, CI 0.20 to 0.80). No differences were detected between arms on other health risks. There were no differences on secondary outcomes, apart from a greater detection of abuse (OR 13.8, CI 1.71 to 111). There were no reports of harmful events and intervention arm youth had high acceptance of the screening tool. CONCLUSIONS: A complex intervention, compared to a simple educational seminar for practices, improved detection of health risk behaviours in young people. Impact on health outcomes was inconclusive. Technology enabling more efficient, systematic health-risk screening may allow providers to target counselling toward higher risk individuals. Further trials require more power to confirm health benefits. TRIAL REGISTRATION: ISRCTN.com ISRCTN16059206.

The association between sidewalk length and walking for different purposes in established neighborhoods.

BACKGROUND: Walking in neighborhood environments is undertaken for different purposes including for transportation and leisure. We examined whether sidewalk availability was associated with participation in, and minutes of neighborhood-based walking for transportation (NWT) and recreation (NWR) after controlling for neighborhood self-selection. METHOD: Baseline survey data from respondents (n = 1813) who participated in the RESIDential Environment (RESIDE) project (Perth, Western Australia) were used. Respondents were recruited based on their plans to move to another neighborhood in the following year. Usual weekly neighborhood-based walking, residential preferences, walking attitudes, and demographics were measured. Characteristics of the respondent's baseline neighborhood were measured including transportation-related walkability and sidewalk length. A Heckman two-stage modeling approach (multivariate Probit regression for walking participation, followed by a sample selection-bias corrected OLS regression for walking minutes) estimated the relative contribution of sidewalk length to NWT and NWR. RESULTS: After adjustment, neighborhood sidewalk length and walkability were positively associated with a 2.97 and 2.16 percentage point increase in the probability of NWT participation, respectively. For each 10 km increase in sidewalk length, NWT increased by 5.38 min/wk and overall neighborhood-based walking increased by 5.26 min/wk. Neighborhood walkability was not associated with NWT or NWR minutes. Moreover, sidewalk length was not associated with NWR minutes. CONCLUSIONS: Sidewalk availability in established neighborhoods may be differentially associated with walking for different purposes. Our findings suggest that large investments in sidewalk construction alone would yield small increases in walking.

The prevention access and risk taking in young people (PARTY) project protocol: a cluster randomised controlled trial of health risk screening and motivational interviewing for young people presenting to general practice.

BACKGROUND: There are growing worldwide concerns about the ability of primary health care systems to manage the major burden of illness in young people. Over two thirds of premature adult deaths result from risks that manifest in adolescence, including injury, neuropsychiatric problems and consequences of risky behaviours. One policy response is to better reorientate primary health services towards prevention and early intervention. Currently, however, there is insufficient evidence to support this recommendation for young people. This paper describes the design and implementation of a trial testing an intervention to promote psychosocial risk screening of all young people attending general practice and to respond to identified risks using motivational interviewing. MAIN OUTCOMES: clinicians' detection of risk-taking and emotional distress, young people's intention to change and reduction of risk taking. SECONDARY OUTCOMES: pathways to care, trust in the clinician and likelihood of returning for future visits. The design of the economic and process evaluation are not detailed in this protocol. METHODS: PARTY is a cluster randomised trial recruiting 42 general practices in Victoria, Australia. Baseline measures include: youth friendly practice characteristics; practice staff's self-perceived competency in young people's care and clinicians' detection and response to risk taking behaviours and emotional distress in 14-24 year olds, attending the practice. Practices are then stratified by a social disadvantage index and billing methods and randomised. Intervention practices receive: nine hours of training and tools; feedback of their baseline data and two practice visits over six weeks. Comparison practices receive a three hour seminar in youth friendly practice only. Six weeks post-intervention, 30 consecutive young people are interviewed post-consultation from each practice and followed-up for self-reported risk taking behaviour and emotional distress three and 12 months post consultation. DISCUSSION: The PARTY trial is the first to examine the effectiveness and efficiency of a psychosocial risk screening and counselling intervention for young people attending primary care. It will provide important data on health risk profiles of young people attending general practice and on the effects of the intervention on engagement with primary care and health outcomes over 12 months. TRIAL REGISTRATION: ISRCTN16059206.

In search of causality: a systematic review of the relationship between the built environment and physical activity among adults.

BACKGROUND: Empirical evidence suggests that an association between the built environment and physical activity exists. This evidence is mostly derived from cross-sectional studies that do not account for other causal explanations such as neighborhood self-selection. Experimental and quasi-experimental designs can be used to isolate the effect of the built environment on physical activity, but in their absence, statistical techniques that adjust for neighborhood self-selection can be used with cross-sectional data. Previous reviews examining the built environment-physical activity relationship have not differentiated among findings based on study design. To deal with self-selection, we synthesized evidence regarding the relationship between objective measures of the built environment and physical activity by including in our review: 1) cross-sectional studies that adjust for neighborhood self-selection and 2) quasi-experiments. METHOD: In September 2010, we searched for English-language studies on built environments and physical activity from all available years in health, leisure, transportation, social sciences, and geographical databases. Twenty cross-sectional and 13 quasi-experimental studies published between 1996 and 2010 were included in the review. RESULTS: Most associations between the built environment and physical activity were in the expected direction or null. Land use mix, connectivity and population density and overall neighborhood design were however, important determinants of physical activity. The built environment was more likely to be associated with transportation walking compared with other types of physical activity including recreational walking. Three studies found an attenuation in associations between built environment characteristics and physical activity after accounting for neighborhood self-selection. CONCLUSION: More quasi-experiments that examine a broader range of environmental attributes in relation to context-specific physical activity and that measure changes in the built environment, neighborhood preferences and their effect on physical activity are needed.

The danger in conservative framing of a complex, systems-level issue.

One's weight is the outcome of a complex interplay of factors within which the choices we make about diet and activity are constrained and shaped by systemic forces - biological, social and economic - that fall increasingly beyond our control. "Simple" solutions that ignore the complex, systems-level characteristics of the obesity epidemic will generally fail as counter-veiling forces act to negate and undermine whatever action is taken. Selling the prevention message is not enough if politicians can choose conservative options that give the appearance of action but fail to tackle the issue. They need instead to be convinced that there is no alternative other than the multi-sector, multi-level, whole-of-government approach that is being adopted by enlightened jurisdictions such as California and the United Kingdom. As Dr. Havala Hobbs argues, this requires transparency, public participation, accountability and politically astute leadership of the sort demonstrated in the fight against tobacco.

Convergent validity between a discrete choice experiment and a direct, open-ended method: comparison of preferred attribute levels and willingness to pay estimates.

The Discrete Choice Experiment (DCE) has become increasingly popular as a method for eliciting patient or population preferences. If DCE estimates are to inform health policy, it is crucial that the answers they provide are valid. Convergent validity is tested in this paper by comparing the results of a DCE exercise with the answers obtained from direct, open-ended questions. The two methods are compared in terms of preferred attribute levels and willingness to pay (WTP) values. Face-to-face interviews were held with 292 women in Calgary, Canada. Similar values were found between the two methods with respect to preferred levels for two out of three of the attributes examined. The DCE predicted less well for levels outside the range than for levels inside the range reaffirming the importance of extensive piloting to ensure appropriate level range in DCEs. The mean WTP derived from the open-ended question was substantially lower than the mean derived from the DCE. However, the two sets of willingness to pay estimates were consistent with each other in that individuals who were willing to pay more in the open-ended question were also willing to pay more in the DCE. The difference in mean WTP values between the two approaches (direct versus DCE) demonstrates the importance of continuing research into the different biases present across elicitation methods.

Participation in treatment decision-making by women with early stage breast cancer.

OBJECTIVE: This study aimed to assess the way women treated for early stage breast cancer perceived the treatment selection process. The purpose was to understand more fully patients' experiences of the decision process and their preferences for participation in treatment decisions. SETTING AND PARTICIPANTS: The study informants were 40 women, treated at a teaching hospital in Sydney Australia, who were interviewed face to face 1 year after their first treatment for stage I or stage II breast cancer. METHODS: This study used a qualitative approach, based on the analysis of interview transcripts. The main areas covered were how the informants' treatment decisions were made and their preferences for participation in treatment decisions. Content and thematic analyses were conducted with findings presented using verbatim quotations for illustration. RESULTS AND CONCLUSIONS: Many of the informants who preferred not to participate in decisions also failed to recognize the need for value judgements (as well as medical expertise) in the decision-making process. Some informants believed they ought to be responsible for the consequences whilst others did not. Difficulties were identified in patient utilization of medical information for treatment decision-making, and also in establishing preferences for the risks and benefits of treatments where few patients had prior experience of the potential outcomes. The findings indicate that patient participation in treatment decision-making is a more complex issue than simply giving patients information and choices. Ways of enhancing patients' involvement in the treatment selection process are discussed.