IU Indianapolis ScholarWorks :: Browsing by Author "Miller, Andrew D."

Browsing by Author "Miller, Andrew D."

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A multi-site pilot study of a parent-centered tool to promote shared decision-making in hypospadias care
(Elsevier, 2023) Binion, Kelsey E.; Rode, Akash Uday; Nortey, Gabrielle; Miller, Andrew D.; Misseri, Rosalia; Kaefer, Martin; Ross, Sherry; Preisser, John S.; Hu, Di; Chan, Katherine H.; Communication Studies, School of Liberal Arts
Background: Using a user-centered design approach, we conducted a two-site pilot study to evaluate a decision aid (DA) website, the Hypospadias Hub, for parents of hypospadias patients. Objectives: The objectives were to assess the Hub's acceptability, remote usability, and feasibility of study procedures, and to evaluate its preliminary efficacy. Methods: From June 2021-February 2022, we recruited English-speaking parents (≥18 years old) of hypospadias patients (≤5 years) and delivered the Hub electronically ≤2 months before their hypospadias consultation. We collected website analytic data using an ad tracker plug-in. We inquired about treatment preference, hypospadias knowledge, and decisional conflict (Decisional Conflict Scale) at baseline, after viewing the Hub (pre-consultation), and post-consultation. We administered the Decision Aid Acceptability Questionnaire (DAAQ) and the Preparation for Decision-Making Scale (PrepDM) which assessed how well the Hub prepared parents for decision-making with the urologist. Post-consultation, we assessed participants' perception of involvement in decision-making with the Shared Decision-making Questionnaire (SDM-Q-9) and the Decision Regret Scale (DRS). A bivariate analysis compared participants' baseline and pre/post-consultation hypospadias knowledge, decisional conflict, and treatment preference. Using a thematic analysis, we analyzed our semi-structured interviews to uncover how the Hub impacted the consultation and what influenced participants' decisions. Results: Of 148 parents contacted, 134 were eligible and 65/134 (48.5%) enrolled: mean age 29.2, 96.9% female, 76.6% White (Extended Summary Figure). Pre/post-viewing the Hub, there was a statistically significant increase in hypospadias knowledge (54.3 vs. 75.6, p < 0.001) and decrease in decisional conflict (36.0 vs. 21.9, p < 0.001). Most participants (83.3%) thought Hub's length and amount of information (70.4%) was "about right", and 93.0% found most or everything was clear. Pre/post-consultation, there was a statistically significant decrease in decisional conflict (21.9 vs. 8.8, p < 0.001). PrepDM's mean score was 82.6/100 (SD = 14.1); SDM-Q-9's mean score was 82.5/100 (SD = 16.7). DCS's mean score was 25.0/100 (SD = 47.03). Each participant spent an average of 25.75 min reviewing the Hub. Based on thematic analysis, the Hub helped participants feel prepared for the consultation. Discussion: Participants engaged extensively with the Hub and demonstrated improved hypospadias knowledge and decision quality. They felt prepared for the consultation and perceived a high degree of involvement in decision-making. Conclusion: As the first pilot test of a pediatric urology DA, the Hub was acceptable and study procedures were feasible. We plan to conduct a randomized controlled trial of the Hub versus usual care to test its efficacy to improve the quality of shared decision-making and reduce long-term decisional regret.
An mHealth App to Support Caregivers in the Medical Management of Their Child With Cancer: Co-design and User Testing Study
(JMIR, 2022-03-16) Mueller, Emily L.; Cochrane, Anneli R.; Campbell, Madison E.; Nikkhah, Sarah; Miller, Andrew D.; Pediatrics, School of Medicine
Background: Caregivers face new challenges and tasks when their child is diagnosed with cancer, which can be overwhelming. Mobile technology has the capacity to provide immediate support at their fingertips to aid in tracking symptoms, managing medication, and planning for emergencies. Objective: The objective of this study is to engage directly with end users and proxies to co-design and create a mobile technology app to support caregivers in the medical management of their child with cancer. Methods: We engaged directly with caregivers of children with cancer and pediatric oncology nurse coordinators (proxy end users) to co-design and create the prototype of the Cope 360 mobile health app. Alpha testing was accomplished by walking the users through a series of predetermined tasks that encompassed all aspects of the app including tracking symptoms, managing medications, and planning or practicing for a medical emergency that required seeking care in the emergency department. Evaluation was accomplished through recorded semistructured interviews and quantitative surveys to capture demographic information and measure the system usability score. Interviews were transcribed and analyzed iteratively using NVivo (version 12; QSR International). Results: This study included 8 caregivers (aged 33-50 years) of children with cancer, with most children receiving chemotherapy, and 6 nurse coordinators, with 3 (50%) of them having 11 to 20 years of nursing experience. The mean system usability score given by caregivers was 89.4 (95% CI 80-98.8). Results were grouped by app function assessed with focus on specific attributes that were well received and those that required refinement. The major issues requiring refinement included clarity in the medical information and terminology, improvement in design of tasks, tracking of symptoms including adjusting the look and feel of certain buttons, and changing the visual graph used to monitor symptoms to include date anchors. Conclusions: The Cope 360 app was well received by caregivers of children with cancer but requires further refinement for clarity and visual representation. After refinement, testing among caregivers in a real-world environment is needed to finalize the Cope 360 app before its implementation in a randomized controlled trial.
Assessing Demand for Transparency in Intelligent Systems Using Machine Learning
(IEEE, 2018-07) Vorm, Eric S.; Miller, Andrew D.; Human-Centered Computing, School of Informatics and Computing
Intelligent systems offering decision support can lessen cognitive load and improve the efficiency of decision making in a variety of contexts. These systems assist users by evaluating multiple courses of action and recommending the right action at the right time. Modern intelligent systems using machine learning introduce new capabilities in decision support, but they can come at a cost. Machine learning models provide little explanation of their outputs or reasoning process, making it difficult to determine when it is appropriate to trust, or if not, what went wrong. In order to improve trust and ensure appropriate reliance on these systems, users must be afforded increased transparency, enabling an understanding of the systems reasoning, and an explanation of its predictions or classifications. Here we discuss the salient factors in designing transparent intelligent systems using machine learning, and present the results of a user-centered design study. We propose design guidelines derived from our study, and discuss next steps for designing for intelligent system transparency.
Assessing the Value of Transparency in Recommender Systems: An End-User Perspective
(ACM, 2018-10) Vorm, Eric S.; Miller, Andrew D.; Human-Centered Computing, School of Informatics and Computing
Recommender systems, especially those built on machine learning, are increasing in popularity, as well as complexity and scope. Systems that cannot explain their reasoning to end-users risk losing trust with users and failing to achieve acceptance. Users demand interfaces that afford them insights into internal workings, allowing them to build appropriate mental models and calibrated trust. Building interfaces that provide this level of transparency, however, is a significant design challenge, with many design features that compete, and little empirical research to guide implementation. We investigated how end-users of recommender systems value different categories of information to help in determining what to do with computer-generated recommendations in contexts involving high risk to themselves or others. Findings will inform future design of decision support in high-criticality contexts.
Coming to America: Iranians' use of Telegram for immigration information seeking
(Emerald, 2020) Nikkhah, Sarah; Murillo, Angela P.; Young, Alyson Leigh; Miller, Andrew D.; Human-Centered Computing, School of Informatics and Computing
Purpose This study examines Iran-US migrants' use of the most popular messaging application in Iran—Telegram—and shows how they use it to manage their migration information practices. Design/methodology/approach This study took a qualitative observation approach. Over the course of six months, over 80 h of observations were conducted on Iran-US migration-related settings within Telegram. Findings This work identifies the information practices that emerge as users seek and share information related to Iran-US migration. Telegram plays a vital role across the immigration stages, predominantly in the pre-migration stage. This work also shows how the constraints and features of Telegram influence users' information sharing and seeking practices. Practical implications The findings support the implication that a social media platform that provides multiple ways to interact is likely to better support niche or unanticipated uses. Originality/value This study is the first of its kind to explore Iranian Immigrants information practices in the US. The immigration information practices observed during this study represent a valuable example of end-user appropriation within extraordinary constraints, which may be of use in other information-seeking contexts where dedicated or bespoke tools are impractical or ill-advised.
Family Resiliance Technologies: Designing Collaborative Technologies for Caregiving Coordination in the Children's Hospital
(2023-03) Nikkhah, Sarah; Miller, Andrew D.; Bolchini, Davide; Martin-Hammond, Aqueasha M.; Murillo, Angela P.; Pratt, Wanda
Each year, the parents of approximately 15,300 kids will hear the words “Your child has cancer.” Families with hospitalized children must process a lot of stress and play a vital role in their child’s care. Hospitalized children need care and assistance processing medical information and going through their treatment. Therefore, their families must take on new responsibilities such as providing care, processing medical information, getting ready for the extensive and sometimes painful treatments, and facing the fear of losing their child. They must also adjust their daily duties, chores, and jobs to provide care to their hospitalized child. Previous research on families with hospitalized children shows that a lower level of stress and a higher level of communication among family members are significant predictors of long-term health outcomes after hospitalization. Social work and family therapy studies researched family resilience as these families’ ability to process and handle stress as a system. However, few technologies are designed to increase family resilience and support the family’s communication and collaboration when a child is hospitalized. My aim in this dissertation is to understand how collaborative technologies can help family members of hospitalized children (family caregivers) collaborate and coordinate with each other during the stressful extended hospitalization period. Through qualitative interviews and elicitation activities followed by iterative cycles of design, I showed that Family Resilience can be used as a lens to understand families’ collaborative processes and guide the design of collaborative technologies to support these families in adapting when they are under stress, and their usual routines as a family are constantly changing due to their child’s hospitalization. Therefore, there is an opportunity for HCI and CSCW to design collaborative technology that supports family resilience processes for families facing a crisis, such as having a hospitalized child with cancer.
Family-Based Sleep Technologies: Opportunities and Challenges
(ACM, 2019-05) Cherenshchykova, Anna; Miller, Andrew D.; Human-Centered Computing, School of Informatics and Computing
Sleep is a critical component of overall wellness, and pervasive and ubiquitous computing technologies have shown promise for allowing individuals to track and manage their sleep quality. However, sleep quality is also affected by interpersonal factors, especially for families with young children. In this study, we adopted a family informatics approach to understand opportunities and challenges for sleep technologies at the family level. We conducted home-based interviews with 10 families with young children, asking them about their current practices, values, and perceived role for technology. We describe challenges across three phases: bedtime, nighttime, and waking. We show that family-based sleep technologies may have the greatest impact by supporting family activities and rituals, encouraging children's independence, and providing comfort.
Helping Their Child, Helping Each Other: Parents’ Mediated Social Support in the Children's Hospital
(ACM, 2021-10) Nikkhah, Sarah; John, Swaroop; Yalamarti, Krishna; Muller, Emily L.; Miller, Andrew D.; Human-Centered Computing, School of Informatics and Computing
During a health crisis, such as the hospitalization of a child with a serious illness, families must adjust and support each other in coordinating care. CSCW researchers have shown the potential for collaborative technologies to enhance social support in different settings. However, less is known about the potential for CSCW technologies to augment social support practices within family caregiving circles. In this poster, we describe findings from 14 interviews with parents of children hospitalized for cancer treatment. We categorized the support practices between parents and found that they rely heavily on technology to support each other from a distance. We identified opportunities for designing future collaborative technology to augment social support in caregiving teams.
Needs and Challenges of Post-Acute Brain Injury Patients in Understanding Personal Recovery
(ACM, 2017-10) Karanam, Yamini; Miller, Andrew D.; Brady, Erin; Human-Centered Computing, School of Informatics and Computing
Recovery from brain injury is a complex and longitudinal process consisting of clinical recovery, illness management, and personal recovery. Lack of initiatives to create awareness about expected recovery and tools for helping patients understand their progress make the personal recovery journey challenging and frustrating. In this paper, we discuss results from interviews with five post-acute brain injury patients about their needs and challenges in understanding their personal recovery.
"Notjustgirls": Exploring Male-related Eating Disordered Content across Social Media Platforms
(ACM, 2019-05) Pater, Jessica A.; Reining, Lauren E.; Miller, Andrew D.; Toscos, Tammy; Mynatt, Elizabeth D.; Human-Centered Computing, School of Informatics and Computing
Eating disorders (EDs) are a worldwide public health concern that impact approximately 10% of the U.S. population. Our previous research characterized these behaviors across online spaces. These characterizations have used clinical terminology, and their lexical variants, to identify ED content online. However, previous HCI research on EDs (including our own) suffers from a lack of gender and cultural diversity. In this paper, we designed a follow-up study of online ED characterizations, extending our previous methodologies to focus specifically on male/masculine-related content. We highlight the similarities and differences found in the terminology utilized and media archetypes associated with the social media content. Finally, we discuss other considerations highlighted through our analysis of the male-related content that is missing from the previous research.

Browsing by Author "Miller, Andrew D."

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