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International Journal of Clinical Pharmacy

, Volume 41, Issue 3, pp 804–812 | Cite as

Perceived sensitivity to medicines: a study among chronic medicine users in Norway

  • Karin Svensberg
  • Hedvig Nordeng
  • Sahar Gaffari
  • Kate Faasse
  • Rob Horne
  • Angela LupattelliEmail author
Research Article
  • 91 Downloads

Abstract

Background Little is known about patients’ Perceived Sensitivity to Medicines (PSM), “the belief that one is especially sensitive to the actions and side effects of medicines”. Objective (i) To explore the extent of and factors associated with high Perceived Sensitivity to Medicines in a Norwegian population of chronic medicine users; (ii) to assess the psychometric characteristics of the tool to measure PSM. Setting Community pharmacies in the Oslo area, Norway. Method A cross-sectional, questionnaire-based study was conducted between October 2015 and January 2016. Patients filling prescriptions for chronic disorders were recruited. Main outcome measure Perceived sensitivity to medicines. Results The study population included 214 patients (response rate 36.7%). In total 20.1% of the patients reported low, 61.7% moderate and 18.2% high perceived sensitivity to medicines. Factors positively associated with high perceived sensitivity were female gender (Adjusted Odds Ratio (aOR) 5.33, 95% CI 1.52 to 18.72, p < 0.001) and having a non-native language (aOR 4.76, 95% CI 1.48 to 15.30, p < 0.001); lower educational level (aOR 0.43, 95% CI 0.17 to 1.07, p < 0.001) and using generic medicines (aOR 0.12, 95% CI 0.03 to 0.57, p < 0.001) were negatively associated with high perceived sensitivity to medicines. There was no association between the perceived sensitivity and the number of prescription medicines taken. The Norwegian version of the Perceived Sensitivity to Medicines tool demonstrated good psychometric characteristics. Conclusion Almost one out of five patients in this study reported high sensitivity to medicines. Female gender, having a non-native language, lower educational level and using generic medicines were important factors related to the perceived sensitivity. Health care providers should be aware of the impact negative expectations about medicines can have on health behaviors and treatment outcomes, and seek to elicit and address patients’ beliefs about their personal sensitivity to medicines.

Keywords

Beliefs about medicines Generic substitution Nocebo Norway Perceived sensitivity to medicines Side effects 

Notes

Acknowledgements

The authors would like to express our gratitude to all patients participating in the study and to the three pharmacies for their invaluable help in data collection.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflicts of interest

No conflict of interest.

Supplementary material

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References

  1. 1.
    Nestoriuc Y, Orav EJ, Liang MH, Horne R, Barsky AJ. Prediction of nonspecific side effects in rheumatoid arthritis patients by beliefs about medicines. Arthritis Care Res (Hoboken). 2010;62(6):791–9.CrossRefGoogle Scholar
  2. 2.
    Horne R, Faasse K, Cooper V, Diefenbach MA, Leventhal H, Leventhal E, et al. The perceived sensitivity to medicines (PSM) scale: an evaluation of validity and reliability. Br J Health Psychol. 2013;18(1):18–30.CrossRefGoogle Scholar
  3. 3.
    Espay AJ, Norris MM, Eliassen JC, Dwivedi A, Smith MS, Banks C, et al. Placebo effect of medication cost in Parkinson disease: a randomized double-blind study. Neurology. 2015;84(8):794–802.CrossRefGoogle Scholar
  4. 4.
    Andersson Sundell K, Jonsson AK. Beliefs about medicines are strongly associated with medicine-use patterns among the general population. Int J Clin Pract. 2016;70(3):277–85.CrossRefGoogle Scholar
  5. 5.
    Faasse K, Grey A, Horne R, Petrie KJ. High perceived sensitivity to medicines is associated with higher medical care utilisation, increased symptom reporting and greater information-seeking about medication. Pharmacoepidemiol Drug Saf. 2015;24(6):592–9.CrossRefGoogle Scholar
  6. 6.
    Faasse K, Petrie KJ. The nocebo effect: patient expectations and medication side effects. Postgrad Med J. 2013;89(1055):540–6.CrossRefGoogle Scholar
  7. 7.
    Stewart-Williams S, Podd J. The placebo effect: dissolving the expectancy versus conditioning debate. Psychol Bull. 2004;130(2):324–40.CrossRefGoogle Scholar
  8. 8.
    Colagiuri B, Zachariae R. Patient expectancy and post-chemotherapy nausea: a meta-analysis. Ann Behav Med. 2010;40(1):3–14.CrossRefGoogle Scholar
  9. 9.
    Nestoriuc Y, von Blanckenburg P, Schuricht F, Barsky AJ, Hadji P, Albert US, et al. Is it best to expect the worst? Influence of patients’ side-effect expectations on endocrine treatment outcome in a 2-year prospective clinical cohort study. Ann Oncol. 2016;27(10):1909–15.CrossRefGoogle Scholar
  10. 10.
    Horne R, Weinman J, Hankins M. The beliefs about medicines questionnaire: the development and evaluation of a new method for assessing the cognitive representation of medication. Psychol Health. 1999;14(1):1–24.CrossRefGoogle Scholar
  11. 11.
    Wei L, Champman S, Li X, Li X, Li S, Chen R, et al. Beliefs about medicines and non-adherence in patients with stroke, diabetes mellitus and rheumatoid arthritis: a cross-sectional study in China. BMJ Open. 2017;7(10):e017293.CrossRefGoogle Scholar
  12. 12.
    Jonsdottir H, Friis S, Horne R, Pettersen KI, Reikvam A, Andreassen OA. Beliefs about medications: measurement and relationship to adherence in patients with severe mental disorders. Acta Psychiatr Scand. 2009;119(1):78–84.CrossRefGoogle Scholar
  13. 13.
    The Norwegian Medicines Agency (NoMA). NoMA medicine database («legemiddelsøk»). 2016. https://www.legemiddelsok.no/sider/Default.aspx?pane=2&f=Han%3bVir%3bRef%3bMar%3bAvr%3bpar%3bgen. Accessed 30 March 2016.
  14. 14.
    WHO Collaborating Centre for Drugs Statistics Methodology. ATC/DDD index 2012. http://www.whocc.no/atc_ddd_index/. Accessed 17 March 2016.
  15. 15.
    Tan K, Petrie KJ, Faasse K, Bolland MJ, Grey A. Unhelpful information about adverse drug reactions. BMJ. 2014;349:g5019.CrossRefGoogle Scholar
  16. 16.
    Kirkwood BR, Sterne JAC. Essential medical statistics. 2nd ed. Malden: Blackwell; 2003.Google Scholar
  17. 17.
    Hosmer DW, Lemeshow S, Sturdivant RX. Applied logistic regression. 3rd ed. Hoboken: Wiley; 2013.CrossRefGoogle Scholar
  18. 18.
    Chapman SCE, Horne R, Chater A, Hukins D, Smithson WH. Patients’ perspectives on antiepileptic medication: relationships between beliefs about medicines and adherence among patients with epilepsy in UK primary care. Epilepsy Behav. 2014;31:312–20.CrossRefGoogle Scholar
  19. 19.
    Laferton JA, Kube T, Salzmann S, Auer CJ, Shedden-Mora MC. Patients’ expectations regarding medical treatment: a critical review of concepts and their assessment. Front Psychol. 2017;8:233.CrossRefGoogle Scholar
  20. 20.
    Gupta A, Thompson D, Whitehouse A, Collier T, Dahlof B, Poulter N, et al. Adverse events associated with unblinded, but not with blinded, statin therapy in the anglo-scandinavian cardiac outcomes trial—lipid-lowering arm (ASCOT–LLA): a randomised double-blind placebo-controlled trial and its non-randomised non-blind extension phase. Lancet. 2017;389(10088):2473–81.CrossRefGoogle Scholar
  21. 21.
    Preston RA, Materson BJ, Reda DJ, Williams DW. Placebo-associated blood pressure response and adverse effects in the treatment of hypertension: observations from a department of veterans affairs cooperative study. Arch Intern Med. 2000;160(10):1449–54.CrossRefGoogle Scholar
  22. 22.
    Heller MK, Chapman SCE, Horne R. No blank slates: pre-existing schemas about pharmaceuticals predict memory for side effects. Psychol Health. 2017;32(4):402–21.CrossRefGoogle Scholar
  23. 23.
    Horne R. Treatment perceptions and self-regulation. In: Leventhal H, Cameron LD, editors. The self-regulation of health and illness behaviour. London: Routledge; 2003.Google Scholar
  24. 24.
    Kjoenniksen I, Lindbaek M, Granas AG. Patients’ attitudes towards and experiences of generic drug substitution in Norway. Pharm World Sci. 2006;28(5):284–9.CrossRefGoogle Scholar
  25. 25.
    Chandler J, Owen M. Pharmaceuticals: the new brand arena. Int J Market Res. 2002;44(4):385–404.Google Scholar
  26. 26.
    Dunne SS, Dunne CP. What do people really think of generic medicines? A systematic review and critical appraisal of literature on stakeholder perceptions of generic drugs. BMC Med. 2015;13:173.CrossRefGoogle Scholar
  27. 27.
    Gandhi M, Aweeka F, Greenblatt RM, Blaschke TF. Sex differences in pharmacokinetics and pharmacodynamics. Annu Rev Pharmacol Toxicol. 2004;44:499–523.CrossRefGoogle Scholar
  28. 28.
    Schwartz JB. The current state of knowledge on age, sex, and their interactions on clinical pharmacology. Clin Pharmacol Ther. 2007;82(1):87–96.CrossRefGoogle Scholar
  29. 29.
    Petrie KJ, Faasse K, Crichton F, Grey A. How common are symptoms? Evidence from a New Zealand national telephone survey. BMJ Open. 2014;4(6):e005374.CrossRefGoogle Scholar
  30. 30.
    Nolke L, Mensing M, Kramer A, Hornberg C. Sociodemographic and health-(care-)related characteristics of online health information seekers: a cross-sectional German study. BMC Public Health. 2015;15:31.CrossRefGoogle Scholar
  31. 31.
    Manierre MJ. Gaps in knowledge: tracking and explaining gender differences in health information seeking. Soc Sci Med. 2015;128:151–8.CrossRefGoogle Scholar
  32. 32.
    Hallyburton A, Evarts LA. Gender and online health information seeking: a five survey meta-analysis. J Consum Health Internet. 2014;18(2):128–42.CrossRefGoogle Scholar
  33. 33.
    Swedish Medical Product Agency. Årsrapporter, biverkningsarbetet. Årsrapprt for biverkningar 2016. https://lakemedelsverket.se/biverkningsrapporter. Accessed 21 Oct 2017.
  34. 34.
    Richardson A, Allen JA, Xiao H, Vallone D. Effects of race/ethnicity and socioeconomic status on health information-seeking, confidence, and trust. J Health Care Poor Underserved. 2012;23(4):1477–93.CrossRefGoogle Scholar
  35. 35.
    Street LR, Gordon SH, Ward MM, Krupat LE, Kravitz LR. Patient participation in medical consultations: why some patients are more involved than others. Med Care. 2005;43(10):960–9.CrossRefGoogle Scholar
  36. 36.
    Brewer NT, Fazekas KI. Predictors of HPV vaccine acceptability: a theory-informed, systematic review. Prev Med. 2007;45(2–3):107–14.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural SciencesUniversity of OsloOsloNorway
  2. 2.Department of Child Health and DevelopmentNorwegian Institute of Public HealthOsloNorway
  3. 3.School of PsychologyUniversity of New South Wales (UNSW)SydneyAustralia
  4. 4.Research Department of Practice and PolicyUniversity College London School of PharmacyLondonUK

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