Presenting self-monitoring test results for consumers: the effects of graphical formats and age

Objective To examine the effects of graphical formats and age on consumers' comprehension and perceptions of the use of self-monitoring test results. Methods Participants (36 older and 36 young adults) were required to perform verbatim comprehension and value interpretation tasks with hypothetical self-monitoring test results. The test results were randomly presented by four reference range number lines: basic, color enhanced, color/text enhanced, and personalized information enhanced formats. We measured participants' task performance and eye movement data during task completion, and their perceptions and preference of the graphical formats. Results The 4 graphical formats yielded comparable task performance, while text/color and personalized information enhanced formats were believed to be easier and more useful in information comprehension, and led to increased confidence in correct comprehension of test results, compared with other formats (all p's < .05). Perceived health risk increased as the formats applied more information cues (p = .008). There were age differences in task performance and visual attention (all p's < .01), while young and older adults had similar perceptions for the 4 formats. Personalized information enhanced format was preferred by both groups. Conclusions Text/color and personalized information cues appear to be useful for comprehending test results. Future work can be directed to improve the design of graphical formats especially for older adults, and to assess the formats in clinical settings.

[1]  Andrew Hayen,et al.  The Influence of Graphic Display Format on the Interpretations of Quantitative Risk Information among Adults with Lower Education and Literacy , 2012, Medical decision making : an international journal of the Society for Medical Decision Making.

[2]  Wändi Bruine de Bruin,et al.  Designing Graphs that Promote Both Risk Understanding and Behavior Change , 2018, Risk analysis : an official publication of the Society for Risk Analysis.

[3]  Jacob Solomon,et al.  Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results , 2016, J. Am. Medical Informatics Assoc..

[4]  Nananda F. Col,et al.  Balancing the presentation of information and options , 2012 .

[5]  Edgar Erdfelder,et al.  G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences , 2007, Behavior research methods.

[6]  Lotty Hooft,et al.  Decision aids to help older people make health decisions: a systematic review and meta-analysis , 2016, BMC Medical Informatics and Decision Making.

[7]  David T. Bauer,et al.  The design and evaluation of a graphical display for laboratory data , 2010, J. Am. Medical Informatics Assoc..

[8]  Deb Feldman-Stewart,et al.  Do personal stories make patient decision aids more effective? A critical review of theory and evidence , 2013, BMC Medical Informatics and Decision Making.

[9]  Xingda Qu,et al.  Effects of consumer-oriented health information technologies in diabetes management over time: a systematic review and meta-analysis of randomized controlled trials , 2017, J. Am. Medical Informatics Assoc..

[10]  Vivian West,et al.  Innovative information visualization of electronic health record data: a systematic review , 2014, J. Am. Medical Informatics Assoc..

[11]  Charlotte A. Weaver,et al.  Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. , 2013, Journal of the American Medical Informatics Association : JAMIA.

[12]  P. Ubel,et al.  The impact of the format of graphical presentation on health-related knowledge and treatment choices. , 2008, Patient education and counseling.

[13]  Nicole L. Exe,et al.  Numeracy and Literacy Independently Predict Patients’ Ability to Identify Out-of-Range Test Results , 2014, Journal of medical Internet research.

[14]  Aileen Clarke,et al.  Developing a quality criteria framework for patient decision aids: online international Delphi consensus process , 2006, BMJ : British Medical Journal.

[15]  S. Czaja,et al.  The Impact of Numeracy Ability and Technology Skills on Older Adults’ Performance of Health Management Tasks Using a Patient Portal , 2014, Journal of applied gerontology : the official journal of the Southern Gerontological Society.

[16]  E. Boyko,et al.  Brief questions to identify patients with inadequate health literacy. , 2004, Family medicine.

[17]  I. Lipkus.  Numeric, Verbal, and Visual Formats of Conveying Health Risks: Suggested Best Practices and Future Recommendations , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[18]  P. Groenewegen,et al.  Consumers’ interpretation and use of comparative information on the quality of health care: the effect of presentation approaches , 2012, Health expectations : an international journal of public participation in health care and health policy.

[19]  Rebecca V Harris,et al.  Does information form matter when giving tailored risk information to patients in clinical settings? A review of patients’ preferences and responses , 2017, Patient preference and adherence.

[20]  T. Landauer,et al.  Handbook of Human-Computer Interaction , 1997 .

[21]  M. Galesic,et al.  Statistical Numeracy for Health A Cross-cultural Comparison With Probabilistic National Samples , 2010 .

[22]  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2015, The Lancet.

[23]  Xingda Qu,et al.  Predicting Factors of Consumer Acceptance of Health Information Technologies , 2016 .

[24]  Da Tao,et al.  The effectiveness of the use of consumer health information technology in patients with heart failure: A meta-analysis and narrative review of randomized controlled trials , 2017, Journal of telemedicine and telecare.

[25]  Xuefei Gao,et al.  Memory and comprehension for health information among older adults: Distinguishing the effects of domain-general and domain-specific knowledge , 2015, Memory.

[26]  Lidewij Henneman,et al.  Presenting health risk information in different formats: the effect on participants' cognitive and emotional evaluation and decisions. , 2008, Patient education and counseling.

[27]  Da Tao,et al.  Usability Study of a Computer-Based Self-Management System for Older Adults with Chronic Diseases , 2012, JMIR research protocols.

[28]  D. Morrow,et al.  Cognition and Health Literacy in Older Adults’ Recall of Self-Care Information , 2015, The Gerontologist.

[29]  Sunmoo Yoon,et al.  Sometimes more is more: iterative participatory design of infographics for engagement of community members with varying levels of health literacy , 2016, J. Am. Medical Informatics Assoc..

[30]  Yasmina Okan,et al.  How People with Low and High Graph Literacy Process Health Graphs: Evidence from Eye‐tracking , 2016 .

[31]  Valerie J. Trifts,et al.  Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids , 2000 .

[32]  D. Morrow,et al.  A Multi-faceted Approach to Promote Comprehension of Online Health Information Among Older Adults , 2018, The Gerontologist.

[33]  Da Tao,et al.  Does the use of consumer health information technology improve outcomes in the patient self-management of diabetes? A meta-analysis and narrative review of randomized controlled trials , 2014, Int. J. Medical Informatics.

[34]  Da Tao,et al.  A 3-Month Randomized Controlled Pilot Trial of a Patient-Centered, Computer-Based Self-Monitoring System for the Care of Type 2 Diabetes Mellitus and Hypertension , 2016, Journal of Medical Systems.

[35]  Noel T Brewer,et al.  Tables or Bar Graphs? Presenting Test Results in Electronic Medical Records , 2012, Medical decision making : an international journal of the Society for Medical Decision Making.

[36]  Edward T. Cokely,et al.  Science Current Directions in Psychological , 2010 .

[37]  L. G. Doak,et al.  The role of pictures in improving health communication: a review of research on attention, comprehension, recall, and adherence. , 2006, Patient education and counseling.

[38]  Torbjørn Torsvik,et al.  Presentation of clinical laboratory results: an experimental comparison of four visualization techniques , 2012, J. Am. Medical Informatics Assoc..

[39]  Haeran Jae,et al.  Decision Making by Low-Literacy Consumers in the Presence of Point-of-Purchase Information , 2004 .

[40]  Jiajie Zhang,et al.  Representations in Distributed Cognitive Tasks , 1994, Cogn. Sci..

[41]  S. Smith,et al.  Health literacy, cognitive ability, and functional health status among older adults. , 2014, Health services research.

[42]  Katerina Tzafilkou,et al.  Diagnosing user perception and acceptance using eye tracking in web-based end-user development , 2017, Comput. Hum. Behav..

[43]  S. Smith,et al.  ABCs or 123s? The independent contributions of literacy and numeracy skills on health task performance among older adults , 2015, Patient education and counseling.

[44]  ZOE HILDON,et al.  Impact of format and content of visual display of data on comprehension, choice and preference: a systematic review. , 2012, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[45]  Paul K. J. Han,et al.  Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers , 2013, BMC Medical Informatics and Decision Making.

[46]  T. Bodenheimer,et al.  Patient self-management of chronic disease in primary care. , 2002, JAMA.

[47]  Xingda Qu,et al.  Influence of drug colour on perceived drug effects and efficacy , 2018, Ergonomics.

[48]  Beth Chaney,et al.  Web 2.0 Chronic Disease Self-Management for Older Adults: A Systematic Review , 2013, Journal of medical Internet research.

[49]  E. Kurtzman,et al.  Effective presentation of health care performance information for consumer decision making: A systematic review. , 2016, Patient education and counseling.

[50]  Robert J. Volk,et al.  Balancing the presentation of information and options in patient decision aids: an updated review , 2013, BMC Medical Informatics and Decision Making.

[51]  Gastón Ares,et al.  Influence of Interpretation Aids on Attentional Capture, Visual Processing, and Understanding of Front-of-Package Nutrition Labels. , 2015, Journal of nutrition education and behavior.

[52]  Michael Siegrist,et al.  The Effect of Graphical and Numerical Presentation of Hypothetical Prenatal Diagnosis Results on Risk Perception , 2008, Medical decision making : an international journal of the Society for Medical Decision Making.

[53]  David E Bloom,et al.  Towards a comprehensive public health response to population ageing , 2015, The Lancet.

[54]  S. Czaja,et al.  Designing computer systems for older adults , 2002 .

[55]  Da Tao,et al.  Effects of Self-Management Health Information Technology on Glycaemic Control for Patients with Diabetes: A Meta-Analysis of Randomized Controlled Trials , 2013, Journal of telemedicine and telecare.

[56]  Dan J Stein,et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2015, The Lancet.