ArticlePatient preference and adherence2020
The SPUR Model: A Framework for Considering Patient Behavior.
Article in Patient preference and adherence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Predicting and understanding non-adherence in chronic disease: cross-cohort validation and structural equation modeling of the SPUR 6/24 tool.Scientific reports · 2025Article
- Evaluating the effect of mobile applications "My A:Care" and "Smart Coach" on adherence to lipid-lowering treatment in patients with dyslipidemia: a prospective, randomized, open-label clinical study.Frontiers in digital health · 2025Article
- Mapping the Cardiometabolic Patient Experience and Self-Care Behaviors to Inform Design, Implementation, and Persistent Use of Digital Health Care Solutions: Mixed Methods Study.JMIR formative research · 2024Article
- Improving Type 2 Diabetes Care with Extended-Release Metformin: Real-Life Insights from a Physician Educational Program.Endocrine, metabolic & immune disorders drug targets · 2024Article
- How is Patient Adherence Possible? A Novel Mechanistic Model of Adherence Based on Humanities.Patient preference and adherence · 2023Review
- SPUR-27 - Psychometric Properties of a Patient-Reported Outcome Measure of Medication Adherence in Chronic Obstructive Pulmonary Disease.Patient preference and adherence · 2023Article
- SPUR: A Patient-Reported Medication Adherence Model as a Predictor of Admission and Early Readmission in Patients Living with Type 2 Diabetes.Patient preference and adherence · 2023Article
- SPUR: psychometric properties of a patient-reported outcome measure of medication adherence in type 2 diabetes.BMJ open · 2022Article
- Finalization and Validation of Questionnaire and Algorithm of SPUR, a New Adherence Profiling Tool.Patient preference and adherence · 2022Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMedication 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.
objectiveThe 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.
resultsBuilding 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.
conclusionAn 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.