Understanding the collaborative-participatory design

Scariot, Cristiele A.; Heemann, Adriano; Padovani, Stephania

doi:10.3233/wor-2012-0656-2701

Cited by 66 publications

(49 citation statements)

References 9 publications

(7 reference statements)

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“…In order to refine the algorithm content and the simulated SAMI-Self-Care tool display and function iteratively, we used a collaborative-participatory approach. This approach engaged stakeholders in a shared co-designing process and helped ensure that the product will meet real-life needs and be adopted [ 32 , 33 ]. The team formulated a scenario for a symptom management dilemma that would allow patient users to traverse the self-care management algorithms so that self-management recommendations could be generated.…”

Section: Methodsmentioning

confidence: 99%

Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing

Cooley

Abrahm

Berry

et al. 2018

BMC Med Inform Decis Mak

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BackgroundIt is essential that cancer patients understand anticipated symptoms, how to self-manage these symptoms, and when to call their clinicians. However, patients are often ill-prepared to manage symptoms at home. Clinical decision support (CDS) is a potentially innovative way to provide information to patients where and when they need it. The purpose of this project was to design and evaluate a simulated model of an algorithm-based CDS program for self-management of cancer symptoms.MethodsThis study consisted of three phases; development of computable algorithms for self-management of cancer symptoms using a modified ADAPTE process, evaluation of a simulated model of the CDS program, and identification of design objectives and lessons learned from the evaluation of patient-centered CDS. In phase 1, algorithms for pain, constipation and nausea/vomiting were developed by an expert panel. In phase 2, we conducted usability testing of a simulated symptom assessment and management intervention for self-care (SAMI-Self-Care) CDS program involving focus groups, interviews and surveys with cancer patients, their caregivers and clinicians. The Acceptability E-scale measured acceptability of the program. In phase 3, we developed design objectives and identified barriers to uptake of patient-centered CDS based on the data gathered from stakeholders.ResultsIn phase 1, algorithms were reviewed and approved through a consensus meeting and majority vote. In phase 2, 24 patients & caregivers and 13 clinicians participated in the formative evaluation. Iterative changes were made in a simulated SAMI-Self-Care CDS program. Acceptability scores were high among patients, caregivers and clinicians. In phase 3, we formulated CDS design objectives, which included: 1) ensure patient safety, 2) communicate clinical concepts effectively, 3) promote communication with clinicians, 4) support patient activation, and 5) facilitate navigation and use. We identified patient barriers and clinician concerns to using CDS for symptom self-management, which were consistent with the chronic care model, a theoretical framework used to enhance patient-clinician communication and patient self-management.ConclusionPatient safety and tool navigation were critical features of CDS for patient self-management. Insights gleaned from this study may be used to inform the development of CDS resources for symptom self-management in patients with other chronic conditions.

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Section: Methodsmentioning

confidence: 99%

Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing

Cooley

Abrahm

Berry

et al. 2018

BMC Med Inform Decis Mak

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“…Drivers could tend to focus on a single interaction element and not adopt a holistic vision. Moreover,Scariot, Heemann, and Padovani (2012) highlighted the potential for social desirability bias, i.e. users tend to direct answers to what they believe the researcher wants to hear or what is more socially accepted.…”

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confidence: 99%

Automotive HMI design and participatory user involvement: review and perspectives

et al. 2016

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Automotive human-machine interface (HMI) design is facing new challenges due to the technological advances of the last decades. The design process has to be adapted in order to address human factors and road safety challenges. It is now widely accepted that user involvement in the HMI design process is valuable. However, the current form of user involvement in industry remains at the stages of concept assessment and usability tests. Moreover, the literature in other fields (e.g. information systems) promotes a broader user involvement with participatory design (i.e. the user is fully involved in the development process). This article reviews the established benefits of participatory design and reveals perspectives for automotive HMI quality improvement in a cognitive ergonomic framework. Practitioner Summary: Automotive HMI quality determines, in part, drivers' ability to perform primary driving tasks while using in-vehicle devices. User involvement in the design process is a key point to contribute to HMI quality. This article reports the potential benefits of a broad involvement from drivers to meet automotive HMI design challenges.

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“…Iterative focus groups have been used successfully in model generation 35 and healthcare end-user prototyping, 36 and to some extent our chosen method draws parallels to user-based usability methods 37 and collaborative participatory design. 38 Nevertheless, our focus group mainly included CI fellows at the start of their informatics careers. As such, this model should be juxtaposed with the domains, tasks, and KS statements from Silverman's 2019 DoP analysis, in which respondents were more broadly distributed across age groups (35- 8 with the recent DoP analysis may add value to our subspecialty as we continue to define and refine the breadth of CI practice.…”

Section: Discussionmentioning

confidence: 99%

KOI Pond: The “Elevator Pitch” that Adapts to Describe the Breadth and Variety of Clinical Informatics Practice

et al. 2020

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Background The practice of clinical informatics (CI) is diverse and frequently tailored to individual skills and interests or to organizational/departmental needs. Prior studies have sought to define core content areas, educational milestones, and practice patterns within the clinical informatics subspecialty (CIS). Unfortunately, no single tool or framework currently exists that can succinctly define an informatician's role regardless of setting. The diversity of informatics practice makes it difficult to have one “pitch” that describes all possible domains, tasks, knowledge, and skills available to an informatician. Objective Using qualitative data from multiple informaticians, provide a succinct framework to describe and compartmentalize the various functions an informatician can contribute to the healthcare field. Methods We created an iterative focus group of five CIS fellows enrolled in different fellowship programs nationwide, one CIS program director, and an MD-PhD candidate in biomedical informatics. After much discussion, iteration, and consideration of career options within a young and burgeoning subspecialty, a dual-axis model was created that describes CIS practice in terms of settings (internal, external, and policy) and focus areas (knowledge, operations, and innovation). Results and Conclusion By combining both axes into a single “KOI pond” and then prioritizing sections by interest/resource investment, we are able to generate a unique snapshot for each informatician. These snapshots can be used (1) by informaticians to characterize their own practice succinctly as a pitch, (2) by CIS fellows who are considering career options, and (3) by those unfamiliar with CIS who want to learn more.

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Understanding the collaborative-participatory design

Cited by 66 publications

References 9 publications

Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing

Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing

Automotive HMI design and participatory user involvement: review and perspectives

KOI Pond: The “Elevator Pitch” that Adapts to Describe the Breadth and Variety of Clinical Informatics Practice

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