Advertisement

Predicting Self-Management Behaviors in Familial Hypercholesterolemia Using an Integrated Theoretical Model: the Impact of Beliefs About Illnesses and Beliefs About Behaviors

  • Martin S. Hagger
  • Sarah J. Hardcastle
  • Catherine Hingley
  • Ella Strickland
  • Jing Pang
  • Gerald F. Watts
Article

Abstract

Purpose

Patients with familial hypercholesterolemia (FH) are at markedly increased risk of coronary artery disease. Regular participation in three self-management behaviors, physical activity, healthy eating, and adherence to medication, can significantly reduce this risk in FH patients. We aimed to predict intentions to engage in these self-management behaviors in FH patients using a multi-theory, integrated model that makes the distinction between beliefs about illness and beliefs about self-management behaviors.

Methods

Using a cross-sectional, correlational design, patients (N = 110) diagnosed with FH from a clinic in Perth, Western Australia, self-completed a questionnaire that measured constructs from three health behavior theories: the common sense model of illness representations (serious consequences, timeline, personal control, treatment control, illness coherence, emotional representations); theory of planned behavior (attitudes, subjective norms, perceived behavioral control); and social cognitive theory (self-efficacy).

Results

Structural equation models for each self-management behavior revealed consistent and statistically significant effects of attitudes on intentions across the three behaviors. Subjective norms predicted intentions for health eating only and self-efficacy predicted intentions for physical activity only. There were no effects for the perceived behavioral control and common sense model constructs in any model.

Conclusions

Attitudes feature prominently in determining intentions to engage in self-management behaviors in FH patients. The prominence of these attitudinal beliefs about self-management behaviors, as opposed to illness beliefs, suggest that addressing these beliefs may be a priority in the management of FH.

Keywords

Illness perceptions Hyperlipidemia Theoretical integration Common sense model Theory of planned behavior Social cognitive theory Attitudes 

Notes

Acknowledgments

This research was supported by a grant from the International Atherosclerosis Society and Pfizer (grant #10839501).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no competing interests.

References

  1. 1.
    Watts GF, Sullivan DR, Poplawski N, Van Bockxmeer F, Hamilton-Craig I, Clifton PM, et al. Familial hypercholesterolemia: a model of care for Australia. Atheroscler Suppl. 2011;12:221–63. doi: 10.1016/j.atherosclerosissup.2011.06.001.CrossRefPubMedGoogle Scholar
  2. 2.
    Hopkins PN, Toth PP, Ballantyne CM, Rader DJ. Familial hypercholesterolemias: prevalence, genetics, diagnosis and screening recommendations from the National Lipid Association Expert Panel on Familial Hypercholesterolemia. J Clin Lipidol. 2011;5:S9–17. doi: 10.1016/j.jacl.2011.03.452.CrossRefPubMedGoogle Scholar
  3. 3.
    Umans-Eckenhausen MA, Defesche JC, Sijbrands EJ, Scheerder RL, Kastelein JJ. Review of the first 5 years of screening for familial hypercholesterolemia in the Netherlands. Lancet. 2001;357:165–8.CrossRefPubMedGoogle Scholar
  4. 4.
    Ose L. Familial hypercholesterolemia from children to adults. Cardiovasc Drugs Ther. 2002;16:289–93. doi: 10.1023/A:1021773724477.CrossRefPubMedGoogle Scholar
  5. 5.
    Hardcastle SJ, Legge E, Laundy CS, Egan SJ, French R, Watts GF, et al. Patients’ perceptions and experiences of familial hypercholesterolemia, cascade genetic screening and treatment. Int J Behav Med. 2015;22:92–100. doi: 10.1007/s12529-014-9402-x.CrossRefPubMedGoogle Scholar
  6. 6.
    Hollman G, Olsson AG, Ek AC. Disease knowledge and adherence to treatment in patients with familial hypercholesterolemia. J Cardiovasc Nurs. 2006;21:103–8.CrossRefPubMedGoogle Scholar
  7. 7.
    van Maarle MC, Stouthard ME, Bonsel GJ. Risk perceptions of participants in a family-based genetic screening programme for familial hypercholesterolemia. Am J Med Genet. 2003;116A:136–43. doi: 10.1002/ajmg.a.10061.CrossRefPubMedGoogle Scholar
  8. 8.
    Claassen L, Henneman L, van der Weijden T, Marteau TM, Timmermans DRM. Being at risk for cardiovascular disease: perceptions and preventive behavior in people with and without a known genetic predisposition. Psychol Health Med. 2012;17:511–21. doi: 10.1080/13548506.2011.644246.CrossRefPubMedGoogle Scholar
  9. 9.
    Michie S, West R. Behaviour change theory and evidence: a presentation to government. Health Psychol Rev. 2013;7:1–22. doi: 10.1080/17437199.2011.649445.CrossRefGoogle Scholar
  10. 10.
    Michie S. What works and how? Designing more effective interventions needs answers to both questions. Addiction. 2008;103:886–7. doi: 10.1111/j.1360-0443.2007.02112.x.CrossRefGoogle Scholar
  11. 11.
    Conner MT, Norman P. Predicting and changing health behaviour: research and practice with social cognition models. 3rd ed. Maidenhead: Open University Press; 2015.Google Scholar
  12. 12.
    Leventhal H, Meyer D, Nerenz D. The common sense model of illness danger. In: Rachman S, editor. Medical psychology. New York: Pergamon Press; 1980. p. 7–30.Google Scholar
  13. 13.
    Fishbein M, Ajzen I. Predicting and changing behavior: the reasoned action approach. New York: Psychology Press; 2009.Google Scholar
  14. 14.
    Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31:143–64.CrossRefPubMedGoogle Scholar
  15. 15.
    Leventhal H, Breland JY, Mora PA, Leventhal E. Lay representations of illness and treatment: a framework for action. In: Steptoe A, editor. Handbook of behavioral medicine. Springer; 2010. p. 137–54.Google Scholar
  16. 16.
    Henderson CJ, Hagger MS, Orbell S. Does priming a specific illness schema result in an attentional information-processing bias for specific illnesses? Health Psychol. 2007;26:165–73. doi: 10.1037/0278-6133.26.2.165.CrossRefPubMedGoogle Scholar
  17. 17.
    Hagger MS, Orbell S. A meta-analytic review of the common-sense model of illness representations. Psychol Health. 2003;18:141–84. doi: 10.1080/088704403100081321.CrossRefGoogle Scholar
  18. 18.
    French DP, Cooper A, Weinman J. Illness perceptions predict attendance at cardiac rehabilitation following acute myocardial infarction: a systematic review with meta-analysis. J Psychosom Res. 2006;61:757–67. doi: 10.1016/j.jpsychores.2006.07.029.CrossRefPubMedGoogle Scholar
  19. 19.
    Mc Sharry J, Moss-Morris R, Kendrick T. Illness perceptions and glycaemic control in diabetes: a systematic review with meta-analysis. Diabet Med. 2011;28:1300–10. doi: 10.1111/j.1464-5491.2011.03298.x.CrossRefPubMedGoogle Scholar
  20. 20.
    Brandes K, Mullan BA. Can the common-sense model predict adherence in chronically ill patients? A meta-analysis. Health Psychol Rev. 2014;8:129–53. doi: 10.1080/17437199.2013.820986.CrossRefPubMedGoogle Scholar
  21. 21.
    Petrie KJ, Cameron L, Ellis CJ, Buick D, Weinman J. Changing illness perceptions after myocardial infarction: an early intervention randomized controlled trial. Psychosom Med. 2002;64:580–6. doi: 10.1097/00006842-200207000-00007.CrossRefPubMedGoogle Scholar
  22. 22.
    Wearden A, Peters S. Therapeutic techniques for interventions based on Leventhal’s common sense model. Br J Health Psychol. 2008;13:189–93. doi: 10.1348/135910708X295613.CrossRefPubMedGoogle Scholar
  23. 23.
    Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50:179–211. doi: 10.1016/0749-5978(91)90020-T.CrossRefGoogle Scholar
  24. 24.
    Bandura A. Social foundations of thought and action: a social-cognitive theory. Englewood Cliffs: Prentice-Hall; 1986.Google Scholar
  25. 25.
    Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84:191–215. doi: 10.1037/0033-295X.84.2.191.CrossRefPubMedGoogle Scholar
  26. 26.
    Hagger MS, Chatzisarantis NLD, Biddle SJH. A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: predictive validity and the contribution of additional variables. J Sport Exerc Psychol. 2002;24:3–32.Google Scholar
  27. 27.
    Armitage CJ, Conner M. Efficacy of the theory of planned behaviour: a meta-analytic review. Br J Soc Psychol. 2001;40:471–99. doi: 10.1348/014466601164939.CrossRefPubMedGoogle Scholar
  28. 28.
    Rich A, Brandes K, Mullan BA, Hagger MS. Theory of planned behavior and adherence in chronic illness: a meta-analysis. J Behav Med. 2015;38:673–88. doi: 10.1007/s10865-015-9644-3.CrossRefPubMedGoogle Scholar
  29. 29.
    Orbell S, Hagger MS, Brown V, Tidy J. Comparing two theories of health behavior: a prospective study of non-completion of treatment following cervical cancer screening. Health Psychol. 2006;25:604–15. doi: 10.1037/0278-6133.25.5.604.CrossRefPubMedGoogle Scholar
  30. 30.
    Head KJ, Noar SM. Facilitating progress in health behaviour theory development and modification: the reasoned action approach as a case study. Health Psychol Rev. 2014;8:34–52. doi: 10.1080/17437199.2013.778165.CrossRefPubMedGoogle Scholar
  31. 31.
    Montaño DE, Kasprzyk D. Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In: Glanz K, Rimer BK, Viswanath K, editors. Health behavior and health education: theory, research, and practice. 4th ed. San Francisco: Jossey-Bass; 2008. p. 67–96.Google Scholar
  32. 32.
    Hagger MS. Self-regulation: an important construct in health psychology research and practice. Health Psychol Rev. 2010;4:57–65. doi: 10.1080/17437199.2010.503594.CrossRefGoogle Scholar
  33. 33.
    Hagger MS, Chatzisarantis NLD. Transferring motivation from educational to extramural contexts: a review of the trans-contextual model. Eur J Psychol Educ. 2012;27:195–212. doi: 10.1007/s10212-011-0082-5.CrossRefGoogle Scholar
  34. 34.
    Hagger MS, Wood C, Stiff C, Chatzisarantis NLD. Self-regulation and self-control in exercise: the strength-energy model. Int Rev Sport Exerc Psychol. 2010;3:62–86. doi: 10.1080/17509840903322815.CrossRefGoogle Scholar
  35. 35.
    Barkoukis V, Hagger MS, Lambropoulos G, Torbatzoudis H. Extending the trans-contextual model in physical education and leisure-time contexts: examining the role of basic psychological need satisfaction. Br J Educ Psychol. 2010;80:647–70. doi: 10.1348/000709910X487023.CrossRefPubMedGoogle Scholar
  36. 36.
    Hagger MS, Chatzisarantis NLD. The trans-contextual model of autonomous motivation in education: conceptual and empirical issues and meta-analysis. Rev Educ Res. 2015. doi: 10.3102/0034654315585005.Google Scholar
  37. 37.
    Hamilton K, Cox S, White KM. Testing a model of physical activity among mothers and fathers of young children: integrating self-determined motivation, planning, and theory of planned behavior. J Sport Exerc Psychol. 2012;34:124–45.PubMedGoogle Scholar
  38. 38.
    Chan DKC, Hagger MS. Theoretical integration and the psychology of sport injury prevention. Sports Med. 2012;42:725–32. doi: 10.2165/11633040-000000000-00000.PubMedGoogle Scholar
  39. 39.
    Orbell S, Henderson CJ, Hagger MS. Illness schema activation and the effects of illness seasonality on accessibility of implicit illness-related information. Ann Behav Med 2015;49:918–23. doi: 10.1007/s12160-015-9719-y.
  40. 40.
    Henderson CJ, Orbell S, Hagger MS. Illness schema activation and attentional bias to coping procedures. Heallth Psychol 2009;28:101–7. doi: 10.1037/a0013690.
  41. 41.
    Hagger MS. Current issues and new directions in psychology and health: physical activity research showcasing theory into practice. Psychol Health. 2010;25:1–5. doi: 10.1080/08870440903268637.CrossRefPubMedGoogle Scholar
  42. 42.
    Chan DKC, Hardcastle SJ, Dimmock JA, Lentillon-Kaestner V, Donovan RJ, Burgin M, et al. Modal salient belief and social cognitive variables of anti-doping behaviors in sport: examining an extended model of the theory of planned behavior. Psychol Sport Exerc. 2015;16:164–74. doi: 10.1016/j.psychsport.2014.03.002.CrossRefGoogle Scholar
  43. 43.
    Biddle SJH, Hagger MS, Chatzisarantis NLD, Lippke S. Theoretical frameworks in exercise psychology. In: Tenenbaum G, Eklund RC, editors. Handbook of sport psychology. 3rd ed. New York: Wiley; 2007. p. 537–59.Google Scholar
  44. 44.
    McEachan RRC, Conner MT, Taylor N, Lawton RJ. Prospective prediction of health-related behaviors with the theory of planned behavior: a meta-analysis. Health Psychol Rev. 2012;5:97–144. doi: 10.1080/17437199.2010.521684.CrossRefGoogle Scholar
  45. 45.
    Broadbent E, Wilkes C, Koschwanez H, Weinman J, Norton S, Petrie KJ. A systematic review and meta-analysis of the brief illness perception questionnaire. Psychol Health. 2015:1361–85. doi: 10.1080/08870446.2015.1070851.
  46. 46.
    Ajzen I. Residual effects of past on later behavior: habituation and reasoned action perspectives. Personal Soc Psychol Rev. 2002;6:107–22. doi: 10.1207/S15327957PSPR0602_02.CrossRefGoogle Scholar
  47. 47.
    Ouellette JA, Wood W. Habit and intention in everyday life: the multiple processes by which past behavior predicts future behavior. Psychol Bull. 1998;124:54–74. doi: 10.1037//0033-2909.124.1.54.CrossRefGoogle Scholar
  48. 48.
    Albarracín D, Wyer RS. The cognitive impact of past behavior: influences on beliefs, intentions, and future behavioral decisions. J Pers Soc Psychol. 2000;79:5–22. doi: 10.1037/0022-3514.79.1.5.CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Ajzen I. Constructing a TPB questionnaire: conceptual and methodological considerations. 2003;2003. http://www-unix.oit.umass.edu/∼aizen.
  50. 50.
    Hagger MS, Chatzisarantis NLD. Self-identity and the theory of planned behaviour: between-and within-participants analyses. Br J Soc Psychol. 2006;45:731–57. doi: 10.1348/014466605X85654.CrossRefPubMedGoogle Scholar
  51. 51.
    Terry DJ, O’Leary JE. The theory of planned behaviour: the effects of perceived behavioural control and self-efficacy. Br J Soc Psychol. 1995;34:199–220. doi: 10.1111/j.2044-8309.1995.tb01058.x.CrossRefPubMedGoogle Scholar
  52. 52.
    Jacobs DRJ, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc. 1993;25:92–8.CrossRefPubMedGoogle Scholar
  53. 53.
    Cale L. Recommendations and new directions for the future development of children’s self-report measures of physical activity. Health Educ J. 1994;53:439–53.CrossRefGoogle Scholar
  54. 54.
    Hagger MS, Chatzisarantis NLD. First- and higher-order models of attitudes, normative influence, and perceived behavioural control in the theory of planned behaviour. Br J Soc Psychol. 2005;44:513–35. doi: 10.1348/014466604X16219.CrossRefPubMedGoogle Scholar
  55. 55.
    Kock N. WarpPLS 5.0 user manual. Laredo: ScriptWarp Systems; 2015.Google Scholar
  56. 56.
    Diamantopoulos A, Sigauw JA. Introducing LISREL. Introducing statistical methods. Thousand Oaks: Sage; 2000.Google Scholar
  57. 57.
    Tenenhaus M, Vinzi VE, Chatelin Y-M, Lauro C. PLS path modeling. Comput Stat Data Anal. 2005;48:159–205. doi: 10.1016/j.csda.2004.03.005.CrossRefGoogle Scholar
  58. 58.
    Ferguson E. Personality is of central concern to understand health: towards a theoretical model for health psychology. Health Psychol Rev. 2013;7:S32–70. doi: 10.1080/17437199.2010.547985.CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Ajzen I, Fishbein F. Scaling and testing multiplicative combinations in the expectancy-value model of attitudes. J Appl Soc Psychol. 2008;38:2222–47.CrossRefGoogle Scholar
  60. 60.
    Erblich J, Montgomery GH, Valdimarsdottir HB, Cloitre M, Bovbjerg D. Biased cognitive processing of cancer-related information among women with family histories of breast cancer: evidence from a cancer Stroop task. Health Psychol. 2003;22:235–44.CrossRefPubMedGoogle Scholar
  61. 61.
    Keatley DA, Clarke DD, Hagger MS. Investigating the predictive validity of implicit and explicit measures of motivation on condom use, physical activity, and healthy eating. Psychol Health. 2012;27:550–69. doi: 10.1080/08870446.2011.605451.CrossRefPubMedGoogle Scholar
  62. 62.
    Sheeran P, Gollwitzer PM, Bargh JA. Nonconscious processes and health. Health Psychol. 2013;32:460–73. doi: 10.1037/a0029203.CrossRefPubMedGoogle Scholar
  63. 63.
    Bandura A. Self-efficacy: the exercise of control. New York: Freeman; 1997.Google Scholar
  64. 64.
    Schwarzer R. Modeling health behaviour change: how to predict and modify the adoption and maintenance of health behaviors. Appl Psychol Int Rev. 2008;57:1–29. doi: 10.1111/j.1464-0597.2007.00325.x.Google Scholar
  65. 65.
    Zhou G, Gan Y, Miao M, Hamilton K, Knoll N, Schwarzer R. The role of action control and action planning on fruit and vegetable consumption. Appetite. 2015;91:64–8. doi: 10.1016/j.appet.2015.03.022.CrossRefPubMedGoogle Scholar
  66. 66.
    Zhou G, Sun C, Knoll N, Hamilton K, Schwarzer R. Self-efficacy, planning and action control in an oral self-care intervention. Health Educ Res. 2015;30:671–81. doi: 10.1093/her/cyv032.CrossRefPubMedGoogle Scholar
  67. 67.
    Gardner B. A review and analysis of the use of ‘habit’ in understanding, predicting and influencing health-related behaviour. Health Psychol Rev. 2015. doi: 10.1080/17437199.2013.876238.Google Scholar
  68. 68.
    Hardcastle SJ, Chan DKC, Caudwell KM, Sultan S, Cranwell J, Chatzisarantis NLD, et al. Larger and more prominent graphic health warnings on plain-packaged tobacco products and avoidant responses in current smokers: a qualitative study. Int J Behav Med. 2015. doi: 10.1007/s12529-015-9487-x.PubMedGoogle Scholar
  69. 69.
    Liska AE. A critical examination of the causal structure of the Fishbein/Ajzen attitude-behavior model. Soc Psychol Q. 1984;47:61–74.CrossRefGoogle Scholar
  70. 70.
    Hagger MS, Luszczynska A. Implementation intention and action planning interventions in health contexts: state of the research and proposals for the way forward. Appl Psychol Health Well Being. 2014;6:1–47. doi: 10.1111/aphw.12017.CrossRefPubMedGoogle Scholar
  71. 71.
    Stamatakis E, Wardle J, Cole TJ. Childhood obesity and overweight prevalence trends in England: evidence for growing socioeconomic disparities. Int J Obes. 2010;34:41–7. doi: 10.1038/ijo.2009.217.CrossRefGoogle Scholar
  72. 72.
    Solmi F, Von Wagner C, Kobayashi LC, Raine R, Wardle J, Morris S. Decomposing socio-economic inequality in colorectal cancer screening uptake in England. Soc Sci Med. 2015;134:76–86. doi: 10.1016/j.socscimed.2015.04.010.CrossRefPubMedGoogle Scholar

Copyright information

© International Society of Behavioral Medicine 2016

Authors and Affiliations

  1. 1.Health Psychology and Behavioural Medicine Research Group, School of Psychology and Speech Pathology, Faculty of Health ScienceCurtin UniversityPerthAustralia
  2. 2.The Metabolic Research Centre and Lipid Disorders Clinic, Cardiovascular Medicine, Royal Perth Hospital and the School of Medicine and PharmacologyThe University of Western AustraliaPerthAustralia
  3. 3.Faculty of Sport and Health SciencesUniversity of JyväskyläJyväskyläFinland
  4. 4.School of Applied Psychology and Menzies Health Institute, QueenslandGriffith UniversityBrisbaneAustralia

Personalised recommendations