Guessability of U.S. pharmaceutical pictograms in Iranian prospective users
Main Article Content
Keywords
Audiovisual Aids, Patient Participation, Drug Labeling, Pamphlets, Semantics, Health Literacy, Communication, Pattern Recognition, Visual, Iran
Abstract
Objective: This study examined the gueassability of US pharmaceutical pictograms as well as associated demographic factors and cognitive design features among Iranian adults.
Methods: A total of 400 participants requested to guess the meaning of 53 US pharmaceutical pictograms using the open-ended method. Moreover, the participants were asked to rate the cognitive design features of each pictorial in terms of familiarity, concreteness, simplicity, meaningfulness and semantic closeness on a scale of 0-100.
Results: The average guessability score (standard deviation) was 66.30 (SD=24.59). Fifty-five percent of pharmaceutical pictograms understudy met the correctness criteria of 67% specified by ISO3864, while only 30% reached the criterion level of 85% set by ANSIz535.3. Low literate participants with only primary school education had substantial difficulty in the interpretation of pharmaceutical pictograms compared to those completed higher education levels. Younger adults of <30 years significantly performed better in the interpretation of pharmaceutical pictograms as compared to >31 years old participants. ‘Home patient care’ and ‘daily medication use’ had no effect on guessability performance. Concerning cognitive design features, meaningfulness better predict geussability score compared to the others.
Conclusions: Several USP pictograms fail to be correctly interpreted by Iranian users and need to be redesigned respecting cognitive design features. Interface designers are recommended to incorporate more familiar and concrete elements into their graphics in order to create more meaningful pictorial symbols and to avoid any misinterpretation by the user. Much effective medication use is expected to be achieved by means of this approach, through the improvement of the communication property of pharmaceutical pictograms.
References
2. Chan AH, Chan KW. Effects of prospective-user factors and sign design features on guessability of pharmaceutical pictograms. Patient Educ Couns. 2013;90(2):268-275. https://doi.org/10.1016/j.pec.2012.10.009
3. Fernandez-Lazaro CI, García-González JM, Adams DP, Fernandez-Lazaro D, Mielgo-Ayuso J, Caballero-Garcia A, et al. Adherence to treatment and related factors among patients with chronic conditions in primary care: a cross-sectional study. BMC Fam Pract. 2019;20(1):132. https://doi.org/10.1186/s12875-019-1019-3
4. Oori MJ, Mohammadi F, Norouzi-Tabrizi K, Fallahi-Khoshknab M, Ebadi A. Prevalence of medication adherence in patients with hypertension in Iran: A systematic review and meta-analysis of studies published in 2000-2018. ARYA Atheroscler. 2019;15(2):82-92. https://doi.org/10.22122/arya.v15i2.1807
5. Sarayani A, Jahangard-Rafsanjani Z, Hadjibabaie M, Ahmadvand A, Javadi M, Gholami K. A comprehensive review of adherence to diabetes and cardiovascular medications in Iran; implications for practice and research. J Diabetes Metab Disord. 2013;12(1):57. https://doi.org/10.1186/2251-6581-12-57
6. Benrazavy L, Khalooei A. Medication Adherence and its Predictors in Type 2 Diabetic Patients Referring to Urban Primary Health Care Centers in Kerman City, Southeastern Iran. Shiraz E-Med J. 2019;20(7):e84746. https://doi.org/10.5812/semj.84746
7. Sabaté E, Sabaté E. Adherence to long-term therapies: evidence for action. Geneve: World Health Organization; 2003.
8. Brown MT, Bussell JK. Medication adherence: WHO cares? Mayo Clin Proc. 2011;86(4):304-314. https://doi.org/10.4065/mcp.2010.0575
9. Aflakseir A. Role of illness and medication perceptions on adherence to medication in a group of Iranian patients with type 2 diabetes. J Diabetes. 2012;4(3):243-247. https://doi.org/10.1111/j.1753-0407.2012.00183.x
10. Rezaei M, Valiee S, Tahan M, Ebtekar F, Gheshlagh RG. Barriers of medication adherence in patients with type-2 diabetes: a pilot qualitative study. Diabetes Metab Syndr Obes. 2019;12:589-599. https://doi.org/10.2147/DMSO.S197159
11. Farsaei S, Sabzghabaee AM, Zargarzadeh AH, Amini M. Adherence to glyburide and metformin and associated factors in type 2 diabetes in Isfahan, Iran. Iran J Pharm Res. 2011;10(4):933-939.
12. Williams MV, Parker RM, Baker DW, Parikh NS, Pitkin K, Coates WC, Nurss JR. Inadequate functional health literacy among patients at two public hospitals. JAMA. 1995;274(21):1677-1682. https://doi.org/10.1001/jama.1995.03530210031026
13. Gazmararian JA, Baker DW, Williams MV, Parker RM, Scott TL, Green DC, Fehrenbach SN, Ren J, Koplan JP. Health literacy among Medicare enrollees in a managed care organization. JAMA. 1999;281(6):545-551. https://doi.org/10.1001/jama.281.6.545
14. Yazdan Nasab M, Babahoseinpour E, Kheirvari Khezerlo J, Tabasi M, Mavalizadeh F, Barzegar A, Ghadirzadeh MR, Akbarzadeh I, Radmanesh A. Prevalence of self-administered drug use among population of Tehran, Iran. Asia Pacific J Med Toxicol. 2019;8(1):14-8. https://doi.org/10.22038/apjmt.2019.12400
15. Nakhaee M, Vatankhah S. Prevalence and Cause of Self-Medication in Iran: A Systematic Review and Meta-Analysis on Health Center Based Studies. J Biochem Tech. 2019;Special Issue (2):90-105.
16. Azami-Aghdash S, Mohseni M, Etemadi M, Royani S, Moosavi A, Nakhaee M. Prevalence and Cause of Self-Medication in Iran: A Systematic Review and Meta-Analysis Article. Iran J Public Health. 2015;44(12):1580-1593.
17. Norman DA. The psychology of everyday things: Basic books; 1988. ISBN: 978-0465067091.
18. Kolers PA. Some formal characteristics of pictograms. Am Sci. 1969;57(3):348-363.
19. Merks P, Świeczkowski D, Balcerzak M, Drelich E, Białoszewska K, Cwalina N, Krysinski J, Jaguszewski M, Pouliot A, Vaillancourt R. The evaluation of pharmaceutical pictograms among elderly patients in community pharmacy settings–a multicenter pilot study. Patient Prefer Adherence. 2018;12:257-266. https://doi.org/10.2147/PPA.S150113
20. Katz MG, Kripalani S, Weiss BD. Use of pictorial aids in medication instructions: a review of the literature. Am J Health Syst Pharm. 2006;63(23):2391-2397. https://doi.org/10.1016/j.pec.2004.06.012
21. Dowse R, Ehlers M. Medicine labels incorporating pictograms: do they influence understanding and adherence? Patient Educ Couns. 2005;58(1):63-70. https://doi.org/10.1016/j.pec.2004.06.012
22. United State Pharmacopeia. USP Pictograms. Available at: https://www.usp.org/health-quality-safety/usp-pictograms (acessed Oct 3, 2019).
23. Taheri F, Kavusi A, Faghihnia Torshozi Y, Farshad AA, Saremi M. Assessment of validity and reliability of Persian version of System Usability Scale (SUS) for traffic signs. Iran Occup Health. 2017;14(1):12-22.
24. Mcdougall SJ, Curry MB, de Bruijn O. Measuring symbol and icon characteristics: Norms for concreteness, complexity, meaningfulness, familiarity, and semantic distance for 239 symbols. Behav Res Methods Instrum Comput. 1999;31(3):487-519. https://doi.org/10.3758/bf03200730
25. Mok G, Vaillancourt R, Irwin D, Wong A, Zemek R, Alqurashi W. Design and validation of pictograms in a pediatric anaphylaxis action plan. Pediatr Allergy Immunol. 2015;26(3):223-233. https://doi.org/10.1111/pai.12349
26. Roberts NJ, Mohamed Z, Wong P-S, Johnson M, Loh L-C, Partridge MR. The development and comprehensibility of a pictorial asthma action plan. Patient Educ Couns. 2009;74(1):12-18. https://doi.org/10.1016/j.pec.2008.07.049
27. Chan AH, Ng AW. The guessing of mine safety signs meaning: effects of user factors and cognitive sign features. Int J Occup Saf Ergon. 2012;18(2):195-208. https://doi.org/10.1080/10803548.2012.11076928
28. Handcock HE, Rogers WA, Schroeder D, Fisk AD. Safety symbol comprehension: Effects of symbol type, familiarity, and age. Hum Factors. 2004;46(2):183-195. https://doi.org/10.1518/hfes.46.2.183.37344
29. Dowse R, Ehlers MS. The influence of education on the interpretation of pharmaceutical pictograms for communicating medicine instructions. Int J Phar Pract. 2003;11(1):11-18. https://doi.org/10.1211/002235702810
30. Prada M, Rodrigues D, Silva RR, Garrido MV. Lisbon symbol database (LSD): subjective norms for 600 symbols. Behav Res Methods. 2016;48(4):1370-1382. https://doi.org/10.3758/s13428-015-0643-7
31. Trotter M, Burton J, Jones C, Frith B, Thomas J. Drivers’ understanding of temporary and permanent slippery road signage. NZ Transport Agency research report 2017.
32. Ng A, Chan A. Re-usability of traffic signs for inactive divers with consideration of personal characteristics and sign features. Int J Hum Capital Urban Manage. 2016;1(1):1-8. https://doi.org/10.7508/ijhcum.2016.01.001
33. Taheri F, Saremi M, Faghihnia Torshizi Y. The validity and reliability of the Persian version of cognitive features questionnaire of symbolic signs (with the use of traffic signs). Iran Occup Health. 2018;15(2):21-30.
34. Rosner B. Fundamentals of biostatistics, 29 ed. Boston: Nelson Education; 2015.
35. Knapp P, Raynor DK, Jebar AH, Price SJ. Interpretation of medication pictograms by adults in the UK. Ann Pharmacother. 2005;39(7-8):1227-1233. https://doi.org/10.1345/aph.1E483
36. Wolpin SE, Nguyen JK, Parks JJ, Lam AY, Morisky DE, Fernando L, Chu A, Berry DL. Redesigning pictographs for patients with low health literacy and establishing preliminary steps for delivery via smart phones. Pharm Pract (Granada). 2016;14(2):686. https://doi.org/10.18549/PharmPract.2016.02.686
37. Ng AW, Chan AH. The guessability of traffic signs: effects of prospective-user factors and sign design features. Accid Anal Prev. 2007;39(6):1245-1257. https://doi.org/10.1016/j.aap.2007.03.018
38. Ng AW, Chan AH. The effects of driver factors and sign design features on the comprehensibility of traffic signs. J Safety Res. 2008;39(3):321-328. https://doi.org/10.1016/j.jsr.2008.02.031
39. Chan AH, Ng AW. Investigation of guessability of industrial safety signs: effects of prospective-user factors and cognitive sign features. Int J Industr Ergonom. 2010;40(6):689-697. https://doi.org/10.1016/j.ergon.2010.05.002
40. Montagne M. Pharmaceutical pictograms: a model for development and testing for comprehension and utility. Res Social Adm Pharm. 2013;9(5):609-620. https://doi.org/10.1016/j.sapharm.2013.04.003
41. Byrne MD, editor Using icons to find documents: simplicity is critical. Proceedings of the INTERACT'93 and CHI'93 conference on Human factors in computing systems. Amsterdam 1993. https://doi.org/10.1145/169059.169369
42. Marcus A, ed. Icon and symbol design issues for graphical user interfaces. International users interface; New York: John Wiley & Sons; 1996
43. Dewar R. Design and evaluation of public information symbols. In: Visual information for everyday use - Design and research perspectives. London: Taylor & Francis; 1999.
44. Blijlevens J, Creusen ME, Schoormans JP. How consumers perceive product appearance: The identification of three product appearance attributes. Int J Design. 2009;3(3):27-35.
45. Ou YK, Liu YC. Effects of sign design features and training on comprehension of traffic signs in Taiwanese and Vietnamese user groups. Int J Industr Ergonom. 2012;42(1):1-7.
46. Sternberg RJ. Styles of thinking and learning. Language Testing. 1995;12(3):265-291.
47. Emamipour S, Esfandabad HS. Developmental study of thinking styles in Iranian students university. Procedia Soc Behavior Sci. 2013;84:1736-9. https://doi.org/10.1016/j.sbspro.2013.07.023
48. Preece J, Rogers Y, Sharp H, Benyon D, Holland S, Carey T. Human-computer interaction. Boston, MA: Addison-Wesley Longman; 1994. ISBN: 978-0201627695
49. Brigham F. International standardisation of graphical symbols for consumer products. In: Hanson MA. Contemporary Ergonomics. London: Taylor & Francis; 1998.