Development of the SPUR tool: a profiling instrument for patient treatment behavior.
Cognitive test
Compliance
Health beliefs
Interview
Literature review
Translation
Journal
Journal of patient-reported outcomes
ISSN: 2509-8020
Titre abrégé: J Patient Rep Outcomes
Pays: Germany
ID NLM: 101722688
Informations de publication
Date de publication:
06 Jun 2022
06 Jun 2022
Historique:
received:
19
11
2021
accepted:
24
05
2022
entrez:
6
6
2022
pubmed:
7
6
2022
medline:
7
6
2022
Statut:
epublish
Résumé
Long-term treatment adherence is a worldwide concern, with nonadherence resulting from a complex interplay of behaviors and health beliefs. Determining an individual's risk of nonadherence and identifying the drivers of that risk are crucial for the development of successful interventions for improving adherence. Here, we describe the development of a new tool assessing a comprehensive set of characteristics predictive of patients' treatment adherence based on the Social, Psychological, Usage and Rational (SPUR) adherence framework. Concepts from existing self-reporting tools of adherence-related behaviors were identified following a targeted MEDLINE literature review and a subset of these concepts were then selected for inclusion in the new tool. SPUR tool items, simultaneously generated in US English and in French, were tested iteratively through two rounds of cognitive interviews with US and French patients taking long-term treatments for chronic diseases. The pilot SPUR tool, resulting from the qualitative analysis of patients' responses, was then adapted to other cultural settings (China and the UK) and subjected to further rounds of cognitive testing. The literature review identified 27 relevant instruments, from which 49 concepts were included in the SPUR tool (Social: 6, Psychological: 13, Usage: 11, Rational: 19). Feedback from US and French patients suffering from diabetes, multiple sclerosis, or breast cancer (n = 14 for the first round; n = 16 for the second round) indicated that the SPUR tool was well accepted and consistently understood. Minor modifications were implemented, resulting in the retention of 45 items (Social: 5, Psychological: 14, Usage: 10, Rational: 16). Results from the cognitive interviews conducted in China (15 patients per round suffering from diabetes, breast cancer or chronic obstructive pulmonary disease) and the UK (15 patients suffering from diabetes) confirmed the validity of the tool content, with no notable differences being identified across countries or chronic conditions. Our qualitative analyses indicated that the pilot SPUR tool is a promising model that may help clinicians and health systems to predict patient treatment behavior. Further steps using quantitative methods are needed to confirm its predictive validity and other psychometric properties.
Sections du résumé
BACKGROUND
BACKGROUND
Long-term treatment adherence is a worldwide concern, with nonadherence resulting from a complex interplay of behaviors and health beliefs. Determining an individual's risk of nonadherence and identifying the drivers of that risk are crucial for the development of successful interventions for improving adherence. Here, we describe the development of a new tool assessing a comprehensive set of characteristics predictive of patients' treatment adherence based on the Social, Psychological, Usage and Rational (SPUR) adherence framework. Concepts from existing self-reporting tools of adherence-related behaviors were identified following a targeted MEDLINE literature review and a subset of these concepts were then selected for inclusion in the new tool. SPUR tool items, simultaneously generated in US English and in French, were tested iteratively through two rounds of cognitive interviews with US and French patients taking long-term treatments for chronic diseases. The pilot SPUR tool, resulting from the qualitative analysis of patients' responses, was then adapted to other cultural settings (China and the UK) and subjected to further rounds of cognitive testing.
RESULTS
RESULTS
The literature review identified 27 relevant instruments, from which 49 concepts were included in the SPUR tool (Social: 6, Psychological: 13, Usage: 11, Rational: 19). Feedback from US and French patients suffering from diabetes, multiple sclerosis, or breast cancer (n = 14 for the first round; n = 16 for the second round) indicated that the SPUR tool was well accepted and consistently understood. Minor modifications were implemented, resulting in the retention of 45 items (Social: 5, Psychological: 14, Usage: 10, Rational: 16). Results from the cognitive interviews conducted in China (15 patients per round suffering from diabetes, breast cancer or chronic obstructive pulmonary disease) and the UK (15 patients suffering from diabetes) confirmed the validity of the tool content, with no notable differences being identified across countries or chronic conditions.
CONCLUSION
CONCLUSIONS
Our qualitative analyses indicated that the pilot SPUR tool is a promising model that may help clinicians and health systems to predict patient treatment behavior. Further steps using quantitative methods are needed to confirm its predictive validity and other psychometric properties.
Identifiants
pubmed: 35666405
doi: 10.1186/s41687-022-00470-x
pii: 10.1186/s41687-022-00470-x
pmc: PMC9170867
doi:
Types de publication
Journal Article
Langues
eng
Pagination
61Informations de copyright
© 2022. The Author(s).
Références
Sabaté E (2003) Adherence to long-term therapies: evidence for action. World Health Organization, Geneva. Available from https://apps.who.int/iris/bitstream/handle/10665/42682/9241545992.pdf
Khan R, Socha-Dietrich K (2018) Investing in medication adherence improves health outcomes and health system efficiency: adherence to medicines for diabetes, hypertension, and hyperlipidaemia. OECD health working papers: OECD Paris, France
Weinman J, Petrie KJ, Moss-morris R, Horne R (1996) The illness perception questionnaire: a new method for assessing the cognitive representation of illness. Psychol Health 11(3):431–445
doi: 10.1080/08870449608400270
Glombiewski JA, Nestoriuc Y, Rief W, Glaesmer H, Braehler E (2012) Medication adherence in the general population. PLoS ONE 7(12):e50537
doi: 10.1371/journal.pone.0050537
Piette JD (2018) Addressing VAST needs. Am J Public Health 108(6):709
doi: 10.2105/AJPH.2018.304429
Michie S, van Stralen MM, West R (2011) The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci 6:42
doi: 10.1186/1748-5908-6-42
Ajzen I (1991) The theory of planned behavior. Organ Behav Hum Decis Process 50(2):179–211
doi: 10.1016/0749-5978(91)90020-T
Rosenstock IM (1966) Why people use health services. Milbank Mem Fund Q 44(3, Suppl):94–127
doi: 10.2307/3348967
McEachan R, Taylor N, Harrison R, Lawton R, Gardner P, Conner M (2016) Meta-analysis of the reasoned action approach (RAA) to understanding health behaviors. Ann Behav Med 50(4):592–612
doi: 10.1007/s12160-016-9798-4
McEachan RRC, Conner M, Taylor NJ, Lawton RJ (2011) Prospective prediction of health-related behaviours with the Theory of Planned Behaviour: a meta-analysis. Health Psychol Rev 5(2):97–144
doi: 10.1080/17437199.2010.521684
Sibeoni J, Picard C, Orri M, Labey M, Bousquet G, Verneuil L et al (2018) Patients’ quality of life during active cancer treatment: a qualitative study. BMC Cancer 18(1):951
doi: 10.1186/s12885-018-4868-6
Dolgin K (2020) The SPUR model: a framework for considering patient behavior. Patient Prefer Adherence 14:97–105
doi: 10.2147/PPA.S237778
Willis GB, Royston P, Bercini D (1991) The use of verbal report methods in the development and testing of survey questionnaires. Appl Cogn Psychol 5(3):251–267
doi: 10.1002/acp.2350050307
Beaton DE, Bombardier C, Guillemin F, Ferraz MB (2000) Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976) 25(24):3186–3191
doi: 10.1097/00007632-200012150-00014
Guillemin F, Bombardier C, Beaton D (1993) Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol 46(12):1417–1432
doi: 10.1016/0895-4356(93)90142-N
Regnault A, Herdman M (2015) Using quantitative methods within the Universalist model framework to explore the cross-cultural equivalence of patient-reported outcome instruments. Qual Life Res 24(1):115–124
doi: 10.1007/s11136-014-0722-8
Morisky DE, Ang A, Krousel-Wood M, Ward HJ (2008) Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich) 10(5):348–354
doi: 10.1111/j.1751-7176.2008.07572.x
Arnould B, Gilet H, Patrick DL, Acquadro C (2017) Item reduction, scoring, and first validation of the ACCEPTance by the patients of their treatment (ACCEPT(c)) questionnaire. Patient 10(1):81–92
doi: 10.1007/s40271-016-0187-7
Fisher RJ (1993) Social desirability bias and the validity of indirect questioning. J Consum Res 20(2):303–315
doi: 10.1086/209351
Van de Mortel TF (2008) Faking it: social desirability response bias in self-report research. Aust J Adv Nurs 25(4):40
Kvarnström K, Westerholm A, Airaksinen M, Liira H (2021) Factors contributing to medication adherence in patients with a chronic condition: a scoping review of qualitative research. Pharmaceutics 13(7):1100
doi: 10.3390/pharmaceutics13071100