Background: Usability - the extent to which an intervention can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction - may be a key determinant of implementation success. However, few instruments have been developed to measure the design quality of complex health interventions (i.e., those with several interacting components). This study evaluated the structural validity of the Intervention Usability Scale (IUS), an adapted version of the well-established System Usability Scale (SUS) for digital technologies, to measure the usability of a leading complex psychosocial intervention, Motivational Interviewing (MI), for behavioral health service delivery in primary care. Prior SUS studies have found both one- and two-factor solutions, both of which were examined in the current study of the IUS. Method: A survey administered to 136 medical professionals from 11 primary care sites collected demographic information and IUS ratings for MI, the evidence-based psychosocial intervention that primary care providers reported using most often for behavioral health service delivery. Factor analyses replicated procedures used in prior research on the SUS. Results: Analyses indicated that a two-factor solution (with "usable" and "learnable" subscales) best fit the data, accounting for 54.1% of the variance. Inter-item reliabilities for the total score, usable subscale, and learnable subscale were α = .83, α = .84, and α = .67, respectively. Conclusions: This study provides evidence for a two-factor IUS structure consistent with some prior research, as well as acceptable reliability. Implications for implementation research evaluating the usability of complex health interventions are discussed, including the potential for future comparisons across multiple interventions and provider types, as well as the use of the IUS to evaluate the relationship between usability and implementation outcomes such as feasibility.
Background: Usability - the extent to which an intervention can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction - may be a key determinant of implementation success. However, few instruments have been developed to measure the design quality of complex health interventions (i.e., those with several interacting components). This study evaluated the structural validity of the Intervention Usability Scale (IUS), an adapted version of the well-established System Usability Scale (SUS) for digital technologies, to measure the usability of a leading complex psychosocial intervention, Motivational Interviewing (MI), for behavioral health service delivery in primary care. Prior SUS studies have found both one- and two-factor solutions, both of which were examined in the current study of the IUS. Method: A survey administered to 136 medical professionals from 11 primary care sites collected demographic information and IUS ratings for MI, the evidence-based psychosocial intervention that primary care providers reported using most often for behavioral health service delivery. Factor analyses replicated procedures used in prior research on the SUS. Results: Analyses indicated that a two-factor solution (with "usable" and "learnable" subscales) best fit the data, accounting for 54.1% of the variance. Inter-item reliabilities for the total score, usable subscale, and learnable subscale were α = .83, α = .84, and α = .67, respectively. Conclusions: This study provides evidence for a two-factor IUS structure consistent with some prior research, as well as acceptable reliability. Implications for implementation research evaluating the usability of complex health interventions are discussed, including the potential for future comparisons across multiple interventions and provider types, as well as the use of the IUS to evaluate the relationship between usability and implementation outcomes such as feasibility.
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Authors: M Claire Greene; Annie Bonz; Maria Cristobal; Carolina Vega; Lena S Andersen; Alejandra Angulo; Andrea Armijos; María Esther Guevara; Lucia Benavides; Alejandra de la Cruz; Maria Jose Lopez; Arianna Moyano; Andrea Murcia; Maria Jose Noboa; Abhimeleck Rodriguez; Jenifer Solis; Daniela Vergara; Jodi Scharf; Priya Dutt; Milton Wainberg; Wietse A Tol Journal: Pilot Feasibility Stud Date: 2022-06-15
Authors: Sean A Munson; Emily C Friedman; Katie Osterhage; Ryan Allred; Michael D Pullmann; Patricia A Areán; Aaron R Lyon Journal: J Med Internet Res Date: 2022-06-14 Impact factor: 7.076