Evaluating Different Visualization Designs for Personal Health Data

Alrehiely, Majedah; Eslambolchilar, Parisa; Borgo, Rita

doi:10.14236/ewic/hci2018.205

Cited by 4 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Alrehiely et al evaluated different types of visualizations of step count, heart rate, and active calories. A majority of the participants in their study were university students who stated that the visualizations were effective in “data comprehension and gaining knowledge (on personal data)” [ 10 ]. Ehn et al investigated how seniors experience using activity monitors for physical activities in daily life.…”

Section: Resultsmentioning

confidence: 99%

“…Users mostly collect these data in clinical settings to manage certain diseases like diabetes. Another type of data is collected automatically by tracking devices; examples include step counts [ 10 ] and sleep waves [ 11 ]. These data are used not only for patients but also by individuals who are interested in their health in daily activities.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities

Kim

2022

IJERPH

View full text Add to dashboard Cite

Due to the development of sensing technology people can easily track their health in various ways, and the interest in personal healthcare data is increasing. Individuals are interested in controlling their wellness, which requires self-awareness and an understanding of various health conditions. Self-generated health data are easily accessed through mobile devices, and data visualization is commonly used in applications. A systematic literature review was conducted to better understand the role of visualizations and learn how to develop effective ones. Thirteen papers were analyzed for types of data, characteristics of visualizations, and effectiveness for healthcare management. The papers were selected because they represented research on personal health data and visualization in a non-clinical setting, and included health data tracked in everyday life. This paper suggests six levels for categorizing the efficacy of visualizations that take into account cognitive and physical changes in users. Recommendations for future work on conducting evaluations are also identified. This work provides a foundation for personal healthcare data as more applications are developed for mobile and wearable devices.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities

Kim

2022

IJERPH

View full text Add to dashboard Cite

show abstract

Fatigue Assessment with Visualizations of Patient-Generated Data: An Evaluation with Informatics-Savvy Healthcare Professionals

Guardado,

Holappa,

Isomursu

2024

Communications in Computer and Information Science

View full text Add to dashboard Cite

Severe and chronic fatigue is a prevalent symptom in multiple chronic conditions. Its complexity, its multifaceted nature and its varied manifestations across different conditions require a nuanced approach for accurate assessment by healthcare professionals. In our research, informatics-savvy public health nurses from a Digital Health Services and Health Promotion Master’s program evaluated various visualizations of patient-generated health data which could potentially be collected through a mobile app designed for people with Multiple Sclerosis. The data visualization prototypes could be a tool to support fatigue assessment and effective communication during consultations and their design was based on prior suggestions from healthcare professionals with experience in fatigue assessment. The patient-generated health data represented in the prototypes comprised a combination of fatigue-related factors and physical activity tracked by Google Fit. This study presents the recommendations of the participants regarding various aspects linked to the visualizations of patient-generated health data, including their utility in the clinical setting, the most suitable types of data summaries, usability aspects and the possibility of meaningful interrelations between distinct types of data. The results of our study emphasize the importance of well-designed data visualizations to support healthcare professionals in decision-making and to improve patient participation in the chronic care process. The iterative design process of the prototypes ensures that the final visualizations have proper usability and the potential to become clinically relevant, and instrumental in the effective assessment of fatigue in chronic management.

show abstract

Improving the visual communication of environmental model projections

Bannister

Blackwell

Hyder

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Environmental and ecosystem models can help to guide management of changing natural systems by projecting alternative future states under a common set of scenarios. Combining contrasting models into multi-model ensembles (MMEs) can improve the skill and reliability of projections, but associated uncertainty complicates communication of outputs, affecting both the effectiveness of management decisions and, sometimes, public trust in scientific evidence itself. Effective data visualisation can play a key role in accurately communicating such complex outcomes, but we lack an evidence base to enable us to design them to be visually appealing whilst also effectively communicating accurate information. To address this, we conducted a survey to identify the most effective methods for visually communicating the outputs of an ensemble of global climate models. We measured the accuracy, confidence, and ease with which the survey participants were able to interpret 10 visualisations depicting the same set of model outputs in different ways, as well as their preferences. Dot and box plots outperformed all other visualisations, heat maps and radar plots were comparatively ineffective, while our infographic scored highly for visual appeal but lacked information necessary for accurate interpretation. We provide a set of guidelines for visually communicating the outputs of MMEs across a wide range of research areas, aimed at maximising the impact of the visualisations, whilst minimizing the potential for misinterpretations, increasing the societal impact of the models and ensuring they are well-placed to support management in the future.

show abstract

Evaluating Different Visualization Designs for Personal Health Data

Cited by 4 publications

References 16 publications

A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities

A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities

Fatigue Assessment with Visualizations of Patient-Generated Data: An Evaluation with Informatics-Savvy Healthcare Professionals

Improving the visual communication of environmental model projections

Contact Info

Product

Resources

About