The SPUR adherence profiling tool: preliminary results of algorithm development.

Digital questionnaire Rasch adherence drivers of non-adherence partial credit model psychometric validation

Journal

Current medical research and opinion
ISSN: 1473-4877
Titre abrégé: Curr Med Res Opin
Pays: England
ID NLM: 0351014

Informations de publication

Date de publication:
Feb 2022
Historique:
pubmed: 9 12 2021
medline: 21 4 2022
entrez: 8 12 2021
Statut: ppublish

Résumé

The SPUR (Social, Psychological, Usage, and Rational) Adherence Profiling Tool is a recently developed adaptive instrument for measuring key patient-level risk factors for adherence problems. This study describes the SPUR questionnaire's psychometric refinement and evaluation. Data were collected through an online survey among individuals with type 2 diabetes in the United States. 501 participants completed multiple questionnaires, including SPUR and several validated adherence measures. A Partial Credit Model (PCM) analysis was performed to evaluate the structure of the SPUR tool and verify the assumption of a single underlying latent variable reflecting adherence. Partial least-squares discriminant analyses (PLS-DA) were conducted to identify which hierarchically-defined items within each dimension needed to be answered by a given patient. Lastly, correlations were calculated between the latent trait of SPUR adherence and other patient-reported adherence measures. Of the 45 candidate SPUR items, 39 proved to fit well to the PCM confirming that SPUR responses reflected one underlying latent trait hypothesized as non-adherence. Correlations between the latent trait of the SPUR tool and other adherence measures were positive, statistically significant, and ranged from 0.32 to 0.48 ( The SPUR tool represents a promising new adaptive instrument for measuring adherence accurately and efficiently using the digital behavioral diagnostic tool.

Identifiants

pubmed: 34878967
doi: 10.1080/03007995.2021.2010437
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

171-179

Auteurs

Elodie de Bock (E)

Patient Centred Outcomes, ICON plc, Lyon, France.

Kevin Dolgin (K)

Observia, Paris, France.

Benoit Arnould (B)

Patient Centred Outcomes, ICON plc, Lyon, France.

Guillaume Hubert (G)

Observia, Paris, France.

Aaron Lee (A)

Department of Psychology, University of Mississippi, Oxford, MS, USA.

John D Piette (JD)

Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, MI, USA.

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