The role of illness perceptions and treatment beliefs in explaining adherence to pharmacological treatment of chronic pain...
Plan <ul><li>Demographics </li></ul><ul><li>Background theory </li></ul><ul><li>Research/statistics </li></ul><ul><li>Clin...
The Glasgow Picture <ul><li>Participants from Stobhill and GRI: </li></ul><ul><li>Gender (% female) 65 </li></ul><ul><li>M...
The Glasgow Picture
The Glasgow Picture <ul><ul><li>Duration of pain (yrs) 9.5 (8.5) </li></ul></ul><ul><ul><li>Pain rating 8 (6.5) </li></ul>...
The Glasgow picture <ul><li>No of pain medications 2.8(1.8) </li></ul><ul><li>Type of pain medication: </li></ul><ul><li>5...
Chronic Pain and Non-Adherence <ul><li>Conditions such as chronic low back pain are increasing in prevalence and are consi...
Psychological factors and non-adherence <ul><li>Various models have been proposed to explain the psychological factors aff...
The self regulatory model (SRM) <ul><li>Suggests that patients’ cognitive and emotional representations of their illness a...
The extended SRM <ul><li>Horne and Weinman (2002) suggested that the strength of the SRM to explain adherence could be imp...
Aims <ul><li>This study used Leventhals’ self regulatory model to investigate the degree to which illness perceptions and ...
Design and method <ul><li>A cross-sectional design included 217 patients attending chronic pain clinics completing validat...
The illness perceptions questionnaire - revised  <ul><li>Patients perceptions of their illness are measured on 6 coherent ...
The beliefs about medicines questionnaire <ul><li>An 18-item questionnaire designed to assess the views a person has about...
The medication adherence rating scale <ul><li>The MARS assesses the degree of adherence to prescribed medications.  </li><...
The pain numerical rating scale <ul><li>Numerical rating scales have been recommended to measure pain in chronic pain tria...
Results – rates of non-adherence <ul><li>25% participants admitted to non-adherence (sometimes, often, always) </li></ul><...
Beliefs about medicines <ul><li>64% agreed or strongly agreed that their medicines were necessary </li></ul><ul><li>42% ag...
Statistics <ul><li>Pearson correlation coefficients were employed to examine the relationship between demographic, clinica...
Results – simple correlation <ul><li>Older and better educated patients were more adherent. </li></ul><ul><li>Gender was n...
Perceptions, beliefs and adherence <ul><li>Perceptions of illness (pain) as chronic, uncontrollable and unremitting (not c...
Background to SEM <ul><li>SEM is used to test path models </li></ul><ul><li>In such models, you might propose that variabl...
Background to SEM - 2 <ul><li>You might also want to test whether your overall model is a good fit to the data </li></ul><...
Results of SEM <ul><li>Structural equation modelling supports an extended SRM for chronic pain but not the Horne and Weinm...
SEM of adherence to chronic pain medication IPQ consequences IPQ emotion BMQ necessity BMQ concerns Reported adherence (MA...
Conclusions <ul><li>The results of the study can be used to improve practice by providing a model for understanding non-ad...
Conclusions <ul><li>Secondly, challenging the illness representations that influence medication beliefs may also improve a...
Questions <ul><li>Should we think about the SRM more in our clinical practice?  </li></ul><ul><li>Could we use it to devel...
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The role of illness perceptions and medicine beliefs in adherence to chronic pain medication

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Presentation given by Dr Leanne Ramsay & Dr Martin Dunbar to the West of Scotland Pain Group on 7th October 2008 at the Royal College of Physicians and Surgeons of Glasgow.

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The role of illness perceptions and medicine beliefs in adherence to chronic pain medication

  1. 1. The role of illness perceptions and treatment beliefs in explaining adherence to pharmacological treatment of chronic pain October 2008
  2. 2. Plan <ul><li>Demographics </li></ul><ul><li>Background theory </li></ul><ul><li>Research/statistics </li></ul><ul><li>Clinical applications </li></ul>
  3. 3. The Glasgow Picture <ul><li>Participants from Stobhill and GRI: </li></ul><ul><li>Gender (% female) 65 </li></ul><ul><li>Mean Age (SD) 50.6 (14.1) </li></ul><ul><li>Age range 19-86 </li></ul>
  4. 4. The Glasgow Picture
  5. 5. The Glasgow Picture <ul><ul><li>Duration of pain (yrs) 9.5 (8.5) </li></ul></ul><ul><ul><li>Pain rating 8 (6.5) </li></ul></ul><ul><ul><li>Most frequent pain locations (%): </li></ul></ul><ul><ul><ul><li>Lower back 44 </li></ul></ul></ul><ul><ul><ul><li>Legs 22 </li></ul></ul></ul><ul><ul><ul><li>Neck 12 </li></ul></ul></ul>
  6. 6. The Glasgow picture <ul><li>No of pain medications 2.8(1.8) </li></ul><ul><li>Type of pain medication: </li></ul><ul><li>5 most common </li></ul><ul><ul><li>Tramadol </li></ul></ul><ul><ul><li>Amitriptyline </li></ul></ul><ul><ul><li>Paracetamol </li></ul></ul><ul><ul><li>Gabapentin </li></ul></ul><ul><ul><li>Co-codamol </li></ul></ul>
  7. 7. Chronic Pain and Non-Adherence <ul><li>Conditions such as chronic low back pain are increasing in prevalence and are considered to be a major source of lost income due to disability (Karjalainen et al, 2004). </li></ul><ul><li>Chronic pain is resistant to treatment (Guzman et al, 2004). </li></ul><ul><li>A significant problem with non-adherence to prescribed medication has been identified (Kendrew et al, 2001). </li></ul><ul><li>The literature examining non-adherence in chronic pain is underdeveloped (Turk and Rudy, 1991). </li></ul>
  8. 8. Psychological factors and non-adherence <ul><li>Various models have been proposed to explain the psychological factors affecting non-adherence. </li></ul><ul><li>Leventhal’s (1980) self-regulatory model has been frequently applied to explain adherence in chronic illness populations but has not been applied to explore adherence in chronic pain. </li></ul>
  9. 9. The self regulatory model (SRM) <ul><li>Suggests that patients’ cognitive and emotional representations of their illness are used as a framework to help them make sense of their symptoms and make decisions regarding treatment. </li></ul><ul><li>Research has confirmed (MA of 45 studies) that there is an empirical basis for the proposed relationships between illness perceptions, coping and health outcomes. </li></ul>
  10. 10. The extended SRM <ul><li>Horne and Weinman (2002) suggested that the strength of the SRM to explain adherence could be improved by extending it to include medication beliefs. </li></ul><ul><li>This was tested empirically using structural equation modelling (SEM). </li></ul><ul><li>SEM enables formal testing of mediating relationships and the extent to which the data fit the predicted relations between illness perceptions and adherence. </li></ul>
  11. 11. Aims <ul><li>This study used Leventhals’ self regulatory model to investigate the degree to which illness perceptions and medication beliefs explain variations in reported adherence to chronic pain medication. </li></ul><ul><li>The central aim of this study was to test the applicability of the extended SRM model using structural equation modelling, in this sample of patients with chronic pain. </li></ul>
  12. 12. Design and method <ul><li>A cross-sectional design included 217 patients attending chronic pain clinics completing validated questionnaires assessing their illness perceptions, medication beliefs and reported adherence to medication. </li></ul>
  13. 13. The illness perceptions questionnaire - revised <ul><li>Patients perceptions of their illness are measured on 6 coherent themes: </li></ul><ul><li>Identity - the label the individual places on the problem and the symptoms associated with it. </li></ul><ul><li>Cause – personal ideas about aetiology </li></ul><ul><li>Consequence – expected effects and outcome </li></ul><ul><li>Timeline – the perceived duration of the problem </li></ul><ul><li>Controllability/Cure – how one controls or recovers from the illness </li></ul><ul><li>Emotions – emotional response to illness </li></ul>
  14. 14. The beliefs about medicines questionnaire <ul><li>An 18-item questionnaire designed to assess the views a person has about their medicines. It has 2 sections: </li></ul><ul><li>The ‘specific’ section measures: </li></ul><ul><li>i) the concerns one has with specific medication </li></ul><ul><li>ii) the perceived necessity of medicines prescribed for a particular condition. </li></ul><ul><li> An example from the necessity scale is: “My health, at present, depends on my medications”. An example from the concerns scale is: “I sometimes worry about the long-term effects of my medicines”. </li></ul><ul><li>The ‘general’ section measures general views about medicines as a whole. It measures beliefs about the harm associated with medications and beliefs that doctors overuse medicines. </li></ul><ul><li>Only the specific section was used in this study. </li></ul>
  15. 15. The medication adherence rating scale <ul><li>The MARS assesses the degree of adherence to prescribed medications. </li></ul><ul><li>The frequency of 5 non-adherent behaviours (deciding to miss a dose, forgetting to take a dose, altering the dose, stopping taking doses for a while and taking less than instructed) is measured on a 5-point Likert-type scale. </li></ul><ul><li>A sixth item (‘I take more than instructed’) was added following discussion with the authors to capture an additional element of non-adherence relevant to the pain population. </li></ul>
  16. 16. The pain numerical rating scale <ul><li>Numerical rating scales have been recommended to measure pain in chronic pain trials by a leading international group of pain researchers (McQuay, 2005). </li></ul><ul><li>The PNRS provides a measure of the severity of the patient’s pain by asking them to rate their pain on a scale of 0 to 10, where ten indicates the most severe pain. </li></ul>
  17. 17. Results – rates of non-adherence <ul><li>25% participants admitted to non-adherence (sometimes, often, always) </li></ul><ul><li>Is this non-adherence intentional or non-intentional? </li></ul><ul><li>19% state ‘I forget to take a dose’ </li></ul><ul><li>26% state ‘I decide to miss a dose’ </li></ul><ul><li>What about non-adherence by taking more than prescribed? </li></ul><ul><li>26% state ‘I take more than instructed’ </li></ul>
  18. 18. Beliefs about medicines <ul><li>64% agreed or strongly agreed that their medicines were necessary </li></ul><ul><li>42% agreed or strongly agreed that they had concerns about their medicines </li></ul><ul><li>22% believed both that their medicines were necessary and were concerned about them </li></ul>
  19. 19. Statistics <ul><li>Pearson correlation coefficients were employed to examine the relationship between demographic, clinical, illness perceptions and medication belief variables with adherence. </li></ul><ul><li>The extended SRM model proposed in a previous chronic illness sample (Horne & Weinman, 2002) was then tested using Structural Equation Modelling. </li></ul>
  20. 20. Results – simple correlation <ul><li>Older and better educated patients were more adherent. </li></ul><ul><li>Gender was not related to adherence </li></ul><ul><li>Of all the clinical variables, only pain ratings were significantly related to adherence (+0.22) </li></ul>
  21. 21. Perceptions, beliefs and adherence <ul><li>Perceptions of illness (pain) as chronic, uncontrollable and unremitting (not cyclical) were associated with greater adherence to medication. </li></ul><ul><li>The consequences and emotional reaction subscales were not related to adherence. </li></ul><ul><li>Those who were adherent had fewer concerns about medication and a stronger belief that treatment was necessary. </li></ul>
  22. 22. Background to SEM <ul><li>SEM is used to test path models </li></ul><ul><li>In such models, you might propose that variable A, affects variable B, and that goes on to affect the outcome </li></ul><ul><li>E.g. you might suggest that alcohol (variable A) reduces risk perception (variable B) and that causes drinkers to have more accidents (outcome). In this model, risk perception is said to mediate the effects of alcohol on accident risk </li></ul><ul><li>Other methods, such as regression, don’t make it easy to examine these ‘mediated’ pathways </li></ul>
  23. 23. Background to SEM - 2 <ul><li>You might also want to test whether your overall model is a good fit to the data </li></ul><ul><li>Regression analyses tests itself against the perfect model, where everything is explained, and assumes there is no error in your measures </li></ul><ul><li>SEM compares your model to the data (allowing for error) and tells you how much of a mismatch there is </li></ul>
  24. 24. Results of SEM <ul><li>Structural equation modelling supports an extended SRM for chronic pain but not the Horne and Weinman model. </li></ul><ul><li>It suggests that patients holding perceptions of serious consequences of pain and high levels of emotion have more concerns about medication and are consequently less adherent. </li></ul><ul><li>Perceptions of serious consequences of illness are also associated with stronger beliefs about the necessity of medicines and greater adherence. </li></ul>
  25. 25. SEM of adherence to chronic pain medication IPQ consequences IPQ emotion BMQ necessity BMQ concerns Reported adherence (MARS) 0.48** 0.17** 0.29** 0.59** -0.26** 0.20**
  26. 26. Conclusions <ul><li>The results of the study can be used to improve practice by providing a model for understanding non-adherence. </li></ul><ul><li>Firstly, the study demonstrates that medication beliefs have a salient and direct effect on chronic pain patients’ adherence. </li></ul><ul><ul><li>Clinicians could use the BMQ to detect problematic medication beliefs in patients with poor adherence and then challenge these beliefs through discussion </li></ul></ul>
  27. 27. Conclusions <ul><li>Secondly, challenging the illness representations that influence medication beliefs may also improve adherence. </li></ul><ul><ul><li>for example, highlighting the relationship between good adherence and fewer consequences of pain (e.g. better able to perform activities of daily living), may increase the perceived need for medicines and improve adherence. </li></ul></ul>
  28. 28. Questions <ul><li>Should we think about the SRM more in our clinical practice? </li></ul><ul><li>Could we use it to develop our understanding of patients adherence to treatments? </li></ul>

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