<p>The SPUR Model: A Framework for Considering Patient Behavior</p>

Abstract

Background: Medication nonadherence is a global problem that requires urgent attention. Roughly half of all drugs that are prescribed for chronic treatments are not taken by the patients in question. Initiatives designed to support patients and help them modify their behavior are enhanced by personalization, and a number of profiling tools exist to help customize such interventions. Most of these tools were originally designed as paper-based questionnaires, but the growth of digital adherence technologies (DATs) illuminate the need for the development of digital profiling systems that can interact with fully automated patient interfaces. Objective: The objective of this study was to examine existing frameworks from medicine, psychology, sociology, consumer behavior, and economics to elaborate a comprehensive, quantitative profiling approach that can be used to drive the customization of patient support initiatives. Results: Building primarily on Icek Ajzen's Theory of Planned Behavior (TPB), the Health Belief Model (HBM) was used to inform the beliefs about behavior posited in the TPB, while incorporating established factors regarding self-efficacy in the "control" elements of the TPB and selected social and psychological factors in the other constituents of the model. The resulting SPUR (Social, Psychological, Usage, Rational) framework represents a holistic, profiling tool with detailed, quantitative outputs that describe a patient's behavioral risks and the drivers of that risk. Conclusion: An interactive, digital questionnaire built around SPUR represents a potentially useful tool for those desirous of building interactive digital support programs for patients with chronic diseases.

SPUR: psychometric properties of a patient-reported outcome measure of medication adherence in type 2 diabetes

“…The SPUR-27 factors mapped to seven of the 13 previously hypothesised drivers of MA within each major domain as previously highlighted by Dolgin. 19 SPUR-27 reported high internal consistency (α=0.900) with fewer items compared with SPUR-45. 26 …”

“…A literature review was conducted to identify existing PROMs that explore MA. From the selected questionnaires (n=27), four key domains of MA that constitute the SPUR model, as previously reported by Dolgin, 19 were identified. Each domain covered a specific set of hypothesised drivers of MA behaviours, with 13 drivers extracted in total that were believed to individually and collectively predict MA as an outcome: ► Social: subjective norms, interpersonal relationships.…”

Finalization and Validation of Questionnaire and Algorithm of SPUR, a New Adherence Profiling Tool

“…SPUR’s underlying framework is based on a categorization of previously studied drivers of non-adherence for patients with chronic disease. 2 SPUR categorizes drivers for adherence to chronic treatments into four broad dimensions: Social which includes both how the patient perceives the support of those close to them as well as the patient’s perceptions of how the treatment affects their place in society; Psychological which includes items referring to the patient’s sense of identity, their degree of reactance and the discounting of future benefits; Usage which corresponds to unintentional non-adherence, namely practical elements such as financial burden, forgetfulness, complexity of administration and perceived self-efficacy; and Rational which focuses on perceptions of the treatment’s benefits, the seriousness of the illness, and the individual’s perceived risk for bad outcomes, including fear of side effects, as per the Health Belief Model. 3 …”

“… 6 Our goal was to develop an algorithm for calculating summary adherence measures accurately even in the context of missing data on some of the items. 2 To reach this goal, CTT and Rasch modelling were used together for the finalization of the SPUR questionnaire and algorithm and its validation in order to combine the assets of both approaches in a complementary way.…”

Development of the SPUR tool: a profiling instrument for patient treatment behavior

“…In order to provide clinicians and health systems with a reliable, comprehensive, but practical tool for measuring the drivers of treatment nonadherence, we developed a multidimensional questionnaire, taking into account the features of the main theoretical frameworks in the literature, while maintaining a level of simplicity allowing providers to easily administer an assessment based on patient-reported information. This tool was developed to provide a measure of risk of nonadherence while grouping the drivers of adherence into four categories and providing measures for each of these categories [ 12 ]: Social: Social factors include both the impact of those close to the patient and the role of society as a whole (e.g., the influence of sociocultural expectations). Psychological: Psychological factors include three nonclinical psychological factors: self-concept (tendency to deny the existence or extent of the illness), reactance (tendency to resist authority) and the discounting of future values (degree to which asymmetrical valuing of short-term effects over long-term effects affects behavior).…”