Individual studies performed throughout this project have highlighted poor knowledge of primary stroke risk factors and secondary stroke risk and stroke signs and symptoms. BP awareness in a low risk general population was poor as well as among high risk stroke survivors. Stroke survivors had poor risk awareness and were unaffected by large scale, media information campaigns to improve knowledge of stroke signs and symptoms. Although surveys suggest the campaigns are effective for members of the general public, impact on current presentation to emergency department figures still suggests stroke patients are slow to present to hospital despite decades of research and public awareness campaigns (Moser et al 2006). The delay for stroke patients is 2-3 times longer than for patients with acute coronary syndromes (Libman et al 2001) and of the stroke deaths that occur each
year almost half occur before the patient reaches hospital (Ayala et al 2003). Therefore knowledge of signs and symptoms influence stroke occurrence at every stage and the need to improve public awareness is of paramount importance.
Low levels of knowledge of stroke warning signs and risk factor awareness have been identified for decades (Samsa et al 1997, Nicol and Thrift 2005, Dearborn et al 2009). Many patients described symptoms they themselves had been affected by but which are not commonly associated with stroke such as pain at onset and loss of consciousness, this does not suggest the patient was not affected by those symptoms but does inform us that patients knowledge of general, well known signs and symptoms of stroke is poor in this context. The observational study identified low knowledge of risk factors for stroke similar to the Nicol and Thrift study (2005) when a third of patients could not name a single risk factor using free-recall in both high and low risk populations, the observational study found 45% of patients self-reported a well-known stroke risk factor and then later in the questionnaire denied having any risk factors for stroke, this highlights a lack of awareness of established stroke risk factors. The same results were found initially in the RCT, as at baseline prior to any intervention, risk factor knowledge was poor and increased in the intervention group at follow-up but nevertheless it suggests generally knowledge of risk factors for stroke specifically, is poor in the stroke population.
6.5 Risk perception
Risk perception is a subjective judgement made on a background of previous personal, social, geographic, ethnic and cultural experiences (Slovic 1987). Theory of risk perception has been identified and categorised into 3 main domains as the degree to which risk is understood, the degree to which the risk evokes a feeling of dread and the number of people exposed to the risk (Slovic 1987). Risk interventions to influence behaviour can be directed by knowledge of the relevant risk (the disease), what constitutes a ‘risky’ behaviour (smoking in the presence of a stroke), how the patient responds to the risk information (whether they think they should stop smoking since suffering a stroke) and having an understanding of what happens when they respond to the risk information (giving up smoking reduces the risk of stroke recurrence) (Slovic 1987). Therefore perception of risk clearly influences decision making regarding health behaviour and patient’s responses to the consequences of their decisions.
The Social Amplification of Risk Framework’s (SARF) theory states that risk events interact with individual’s psychological, social and cultural factors to either increase or decrease a populations perception of risk (Kasperson 1988). According to the theory, different groups may react differently to a single risk event. As health professionals, knowledge of this theory is useful when trying to influence reactions at the initial stages of communication during transfer of information about risk. The response mechanism of the patients has already been influenced by that individual’s psychological, social and cultural make-up and background, however by individualising risk at the time of the acute, often life-changing event, may be useful for influencing the patient’s response to their risk.
Risk perception is key to understanding how a person becomes motivated to change health behaviours. Studies have shown high risk groups perceive to be at the same level of risk as their low risk peers (Dearborn et al 2009) and that has been mirrored in the control group of the IRAIS study. However, the risk awareness intervention in this study effectively increased risk perception which in turn increased the amount of health behaviour changes made.
The Health Belief Model (HBM) (Lewin 1951, Glanz 2002), the theory of planned behaviour (Azjen and Fishbein 1980), the theory of social behaviour (Bandura 1986) and the transtheoretical model of behaviour change (Prochaska and Velicer 1997) emphasise the perceived value of a patients’ response to a consequence. The transtheoretical model (Pochaska and Velicer 1997) with its “stages of change” is another model in which interpretation of the likelihood of behaviour change is understood in terms of an individual’s readiness to change, and interventions may be targeted accordingly. Readiness to change (Pochaska et al 1983) was not measured throughout this project, however it would be a useful tool to understand and interpret a patients likelihood of change in response to their stroke in order to plan further programmes of education. These theoretical models have been discussed extensively throughout this project and were used as the basis of the theoretical framework for planning the risk communication intervention. In general, the models seek to provide an understanding of how individuals perceive risk and how this influences their behaviour and may go some way to developing a way of predicting behaviour change. These models frequently attribute consequences in behaviour change to two underlying dimensions: an individual’s perception of the value of an outcome presented in a health recommendation and the perceived threat presented
of the risk awareness intervention as a way of increasing a patients understanding of the threat to their health so that the health recommendation had an increased value by reducing the risk of a recurrence of the unwanted event i.e. another stroke. The observational study identified stroke survivor’s strong sense of consequence following their stroke (90%) and two thirds said they felt their stroke had had a major consequence on their life, this may certainly impact on perception, however this study also highlighted many of the participants believed their stroke happened by chance and suggests a lack of control over their condition which compared with cardiac studies suggesting patients who feel in control have better adherence (Townend 2006) this may be one reason for the differences in stroke and cardiac patient behaviours.
6.6 Risk awareness
Important factors which reflect individual risk awareness have been identified as adherence, behaviour and lifestyle modification. The theoretical models of understanding risk perception and influences on health behaviours have been investigated to identify how the intervention in the RCT could improve health behaviours to reduce risks that have been discussed. Improving adherence to secondary prevention strategies by increasing both health literacy and self-efficacy in targeted patient populations are recognised in the literature, however interventions to achieve this have been lacking in stroke.
Understanding the concept of ‘risk’ has been key to developing the theoretical frameworks required to develop the risk awareness intervention and the potential impact on patient’s perception and behaviours. ‘Risk’ has many definitions which mainly consist of the concept of a potential loss or undesirable outcome. The notion implies, a choice can have an influence on the outcome and this is true of risk in health care and secondary stroke prevention as the patient makes a choice or a decision to perform a health behaviour action to reduce risk. Patients with an awareness of risk have behaved differently compared to controls as part of this thesis, an observational study of stroke survivors up to 5 years later identified those with a greater understanding of their risk being more likely to make more healthy lifestyle choices compared to those who had no risk awareness. In the RCT study in the first 3 months following discharge from hospital, those who had greater risk awareness made more lifestyle changes in direct response to their stroke compared with those with a low risk awareness.
6.7 Medication taking
Results from the two studies investigating behaviours of stroke survivors identified differences in medication taking. Adherence for secondary stroke prevention was poor in the observational study with only 66% taking antiplatelet appropriately and 45% taking statins. These results differed from the RCT data where medication taking was very well reported with 89% taking an antiplatelet and 87% taking a statin appropriately. The major difference between the two populations is length of time since stroke. Therefore these results support the concept of adherence dropping off over time and should be an argument for long-term follow-up with a focus on medication taking. Interestingly behaviour was not influenced by time since stroke in the observational study which would suggest once health behaviour is in place, it remains so in the long-term, however, a possible explanation might be changes in medication prescriptions’ disrupt a pattern of adherence as a change in routine might interrupt lifestyle behaviour. Also the identification of a small reduction in medication taking at follow-up in the RCT is noteworthy as the reduction was seen in all four of the major secondary prevention medications prescribed at discharge. It would be very interesting to investigate if this group continued to reduce medication taking over time and a follow-up at one year would be most useful.
It is also important to highlight, it has been documented that patient compliance with treatment is usually substantially better in closely monitored and motivated research trial populations than in routine clinical practice (Sappok 2001), this suggests either all patients participate in a clinical research trial, which is unrealistic, or all patients receive better, more closely monitored follow-up at discharge from hospital.