Remembering Human Factors when Implementing Technology Use

2016 ◽  
pp. 145-156 ◽  
Author(s):  
Lori A. Byers
Keyword(s):  
Human Factors ◽  
Technology Use

Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation

2021 ◽  
Vol 65 (1) ◽  
pp. 776-780
Author(s):  
Bijita Devkota ◽  
Fernando Montalvo ◽  
Daniel S. McConnell ◽  
Janan A. Smither
Keyword(s):  
Human Factors ◽  
Technology Acceptance ◽  
Treatment Adherence ◽  
Technology Use ◽  
Technology Implementation ◽  
Medical Information ◽  
Treatment Protocols ◽  
Lower Treatment ◽  
Relationship Of ◽  
The Relationship

eHealth applications are expected to improve the effectiveness and efficiency of healthcare systems by providing improved medical information flow between medical providers and patients. Although the technology is expected to empower patients, lower treatment costs, and provide real-time collection of health data, individuals may be apprehensive about the use and efficacy of eHealth technologies. Medical professionals are often unaware of human factors technology acceptance or usability models which impact the use of medically focused technology, such as eHealth applications. Similarly, human factors professionals are often unaware of treatment adherence models which map the relationship of illness factors and individual differences to treatment protocols. The present paper presents a theoretical approach through which technology acceptance and usability models should be combined with medical treatment adherence models to ensure that eHealth applications are used properly and effectively.

Factors Affecting the Design and Development of a Personal Learning Environment

2012 ◽  
pp. 226-236
Author(s):  
Helene Fournier ◽  
Rita Kop
Keyword(s):  
Learning Environment ◽  
Human Factors ◽  
Learning Environments ◽  
Technology Use ◽  
Interface Design ◽  
Design And Development ◽  
Factors Affecting ◽  
Personal Learning ◽  
Personal Learning Environment ◽  
Personal Learning Environments

After speculation in literature about the nature of Personal Learning Environments, research in the design and development of PLEs is now in progress. This paper reports on the first phase of the authors’ research on PLE, the identification process of what potential users would consider important components, applications, and tools in a PLE. The methodology included surveying “super-users” on their use of existing tools, applications and systems and their preferences in learning, in order to enhance the development of a PLE and reach a specification that potential learners will find useful and empowering in their learning. The research resulted in suggestions on factors affecting technology use and uptake, human factors and attitudes, and interface design that need to be factored in the design and development of a PLE.

Exploring Challenges of Monitoring Technology and Self-Injurious Behavior in Autism Spectrum Disorder

2018 ◽  
Vol 62 (1) ◽  
pp. 620-621 ◽  
Author(s):  
Kristine Cantin-Garside ◽  
Rupa S. Valdez ◽  
Maury A. Nussbaum ◽  
Susan White ◽  
Sunwook Kim ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Human Factors ◽  
Technology Use ◽  
Health Technology ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Monitoring Technology ◽  
Home Setting ◽  
Sensory Stimuli ◽  
Patient Work

Self-injurious behavior (SIB), such as head banging or self-hitting, is considered one of the most dangerous characteristics of autism spectrum disorder (ASD) (Mahatmya, Zobel, & Valdovinos, 2008). Clinicians traditionally rely on structured observation, which can be time-consuming and invasive. Recent technological developments in motion tracking may decrease these burdens. For example, accelerometers in smart watches can gather movement information, which could be automatically classified to detect and predict events associated with SIB using machine learning algorithms. While such systems have clear potential to objectively, accurately, and efficiently monitor and predict SIB, this potential will not be fully realized unless devices are adopted and integrated into clinics and homes. The lack of user input when designing home-based technological interventions for ASD likely contributes to the fact that technology has been rarely, if at all, implemented. In ongoing work, we included stakeholders before design is complete, and embraced a user-centered perspective by evaluating user needs and translating them into system requirements (Karsh, Weinger, Abbott, & Wears, 2010). To this end, we evaluated stakeholder perspectives regarding monitoring technology for SIB in children with ASD. Sixteen parents (age 31-62, M = 45.1 ± 8.1 years) with children (age 6-26, M = 14.1 ± 6.7 years) with ASD and SIB were engaged in individual or group interviews to assess needs and challenges associated with SIB. Interviews with broad and open-ended questions were conducted to allow for response variability that may decrease in larger groups. Questions spanned several aspects of SIB and its management, as well as current and projected technology use. Parents discussed perceived benefits and challenges of different technologies, such as smart watches and video cameras, as related to tracking movement associated with SIB. Data from the first six interviews influenced a second version of interview questions to reflect participant responses. Qualitative content analysis was used to organize the responses into seven main themes surrounding experiences of SIB and technology: (1) triggers, (2) emotional responses, (3) SIB characteristics, (4) management strategies, (5) caregiver impact, (6) child impact, and (7) preferred sensory stimuli (Graneheim & Lundman, 2004). Data were cross-coded with two underlying themes of (8) uncertainty and (9) state of experience. Critical to preserving the original interview content, categories and themes were derived directly from the data rather than from predetermined topics (Hsieh & Shannon, 2005). The derived themes were related to the needs and challenges of SIB, and they were then interpreted to determine design considerations for monitoring methods. Parents described changes in SIB, and they often associated these changes with either child-specific variables (e.g., maturity, medical concerns) or environment-specific variables (e.g., time, new triggers). The variety of triggers and behaviors and the high likelihood of these parameters changing require adaptive monitoring technology capable of learning new behavioral patterns. Tracking systems should be customizable to accommodate the strong presence of variability (Cabibihan, Javed, Aldosari, Frazier, & Elbashir, 2017) and to support patient and contextual variability, which is an opportunity for human factors research through the patient work lens (Valdez, Holden, Novak, & Veinot, 2014). Participants also expressed a shared deficit in resources, referring to both a lack of available technology and information. Monitoring system design should therefore employ affordable, accessible technology while empowering caregivers to access interpretable data. Whether devices are embedded in the environment or attached to a child, parents prefer mitigating required input because of their already high levels of stress, discussed within the caregiver impact theme. Parents mentioned that their typical schedules afforded limited time for data collection, which indicates the designed system should require a limited number of quick interactions. Automated and manual options (Valdez et al., 2014) may address both the need to reduce workload, a factor affecting patient work (Holden, Valdez, Schubert, Thompson, & Hundt, 2017), and the need to increase control when monitoring SIB. The findings from this study and the resulting design implications provide a foundation for future technology development. It is expected that early-stage user involvement will encourage acceptance of this monitoring technology (Panchanathan & McDaniel, 2015; Veryzer & Borja de Mozota, 2005). Users will continue to participate throughout the design process. Careful consideration of the user may lead to accepted and adopted health technology with both efficiency and accuracy in detecting SIB. Results from this study highlight the importance of parent consideration in the health technology space for children with disabilities, particularly when parents participate in management methods. Further, this research contributes to an underexplored domain of qualitative human factors applied to disability and design. Future work could employ human factors approaches, such as contextual inquiries (Marcu et al., 2013) reflecting the patient work framework, to evaluate child and parent needs within the home setting. This research was supported by a National Science Foundation Graduate Research Fellowship (to the first author) and a 4-VA Collaborative Research Grant (to RSV). However, neither agency had any involvement in data analysis or interpretation.

scholarly journals Interdisciplinary systematic review: does alignment between system and design shape adoption and use of barcode medication administration technology?

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e044419
Author(s):  
Rachel Williams ◽  
Reham Aldakhil ◽  
Ann Blandford ◽  
Yogini Jani
Keyword(s):  
Human Computer Interaction ◽  
Human Factors ◽  
Technology Use ◽  
Medication Administration ◽  
Appropriate Technology ◽  
Synthesis Methods ◽  
Eligibility Criteria ◽  
Research Perspectives ◽  
Mediating Factors ◽  
Computer Interaction

BackgroundIn order to reduce safety risks associated with medication administrations, technologies such as barcode medication administration (BCMA) are increasingly used. Examining how human factors influence adoption and usability of this technology can potentially highlight areas for improvement in design and implementation.ObjectiveTo describe how human factors related determinants for BCMA have been researched and reported by healthcare and human–computer interaction disciplines.Data sourcesThe Cumulative Index of Nursing, and Allied Health Literature, PubMed, OVID MEDLINE and Google Scholar.Study eligibility criteriaPrimary research published from April 2000 to April 2020, search terms developed to identity different disciplinary research perspectives that examined BCMA use, used a human factors lens and were published in English.Synthesis methodsComputerised systematic searches were conducted in four databases. Eligible papers were systematically analysed for themes. Themes were discussed with a second reviewer and supervisors to ensure they were representative of content.ResultsOf 3707 papers screened, 11 were included. Studies did not fit neatly into a clinical or human-computer interaction perspective but instead uncovered a range of overlapping narratives, demonstrating consensus on the key themes despite differing research approaches. Prevalent themes were misaligned design and workflow, adaptation and workarounds, mediating factors, safety, users’ perceptions and design and usability. Inadequate design frequently led to workarounds, which jeopardised safety. Reported mediating factors included clarity of user needs, pre/post implementation evaluations, analysis of existing workarounds and appropriate technology, infrastructure and staffing.LimitationsMost studies were relatively small and qualitative, making it difficult to generalise findings.ConclusionEvaluating interdisciplinary perspectives including human factors approaches identified similar and complementary enablers and barriers to successful technology use. Often, mediating factors were developed to compensate for unsuitable design; a collaborative approach between system designer and end users is necessary for BCMA to achieve its true safety potential.

scholarly journals Human Factors and Data Logging Processes With the Use of Advanced Technology for Adults With Type 1 Diabetes: Systematic Integrative Review (Preprint)

2017 ◽  
Author(s):  
Marion Waite ◽  
Clare Martin ◽  
Rachel Franklin ◽  
David Duce ◽  
Rachel Harrison
Keyword(s):  
Type 1 Diabetes ◽  
Human Factors ◽  
Technology Use ◽  
Self Care ◽  
Advanced Technology ◽  
Self Management ◽  
Data Logging ◽  
The Relationship ◽  
The Way

BACKGROUND People with type 1 diabetes (T1D) undertake self-management to prevent short and long-term complications. Advanced technology potentially supports such activities but requires consideration of psychological and behavioral constructs and usability issues. Economic factors and health care provider capacity influence access and uptake of advanced technology. Previous reviews have focused upon clinical outcomes or were descriptive or have synthesized studies on adults with those on children and young people where human factors are different. OBJECTIVE This review described and examined the relationship between human factors and adherence with technology for data logging processes in adults with T1D. METHODS A systematic literature search was undertaken by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Quality appraisal was undertaken and data were abstracted and categorized into the themes that underpinned the human factor constructs that were examined. RESULTS A total of 18 studies were included. A total of 6 constructs emerged from the data analysis: the relationship between adherence to data logging and measurable outcomes; satisfaction with the transition to advanced technology for self-management; use of advanced technology and time spent on diabetes-related activities; strategies to mediate the complexities of diabetes and the use of advanced technology; cognition in the wild; and meanings, views, and perspectives from the users of technology. CONCLUSIONS Increased treatment satisfaction was found on transition from traditional to advanced technology use—insulin pump and continuous glucose monitoring (CGM); the most significant factor was when blood glucose levels were consistently <7.00 mmol/L (P ≤.01). Participants spent considerable time on their diabetes self-care. Logging of data was positively correlated with increasing age when using an app that provided meaningful feedback (regression coefficient=55.8 recordings/year; P ≤.01). There were benefits of CGM for older people in mediating complexities and fears of hypoglycemia with significant differences in well-being (P ≤.001). Qualitative studies explored the contextual use and uptake of technology. The results suggested frustrations with CGM, continuous subcutaneous insulin infusion, calibration of devices, and alarms. Furthermore implications for “body image” and the way in which “significant others” impacted on the behavior and attitude of the individual toward technology use. There were wide variations in the normal use of and interaction with technology across a continuum of sociocultural contexts, which has implications for the way in which future technologies should be designed. Quantitative studies were limited by small sample sizes, making it difficult to generalize findings to other contexts. This was further limited by a sample that was predominantly white, well-controlled, and engaged with self-care. The use of critical appraisal frameworks demonstrated where research into human factors and data logging processes of individuals could be improved. This included engaging people in the design of the technology, especially hard-to-reach or marginalized groups.

Aging and assistive technology use

1997 ◽  
Vol 6 (1-2) ◽  
pp. 63-75 ◽  
Author(s):  
William C. Mann
Keyword(s):  
Assistive Technology ◽  
Technology Use

An Application of the HFACS Method to Aviation Accidents in Africa

2016 ◽  
Vol 6 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Isaac Munene
Keyword(s):  
Human Factors ◽  
Physical Environment ◽  
Human Factor ◽  
Flight Training ◽  
African Countries ◽  
Causal Factors ◽  
Aviation Accidents ◽  
Factors Analysis ◽  
Adverse Weather ◽  
Decision Errors

Abstract. The Human Factors Analysis and Classification System (HFACS) methodology was applied to accident reports from three African countries: Kenya, Nigeria, and South Africa. In all, 55 of 72 finalized reports for accidents occurring between 2000 and 2014 were analyzed. In most of the accidents, one or more human factors contributed to the accident. Skill-based errors (56.4%), the physical environment (36.4%), and violations (20%) were the most common causal factors in the accidents. Decision errors comprised 18.2%, while perceptual errors and crew resource management accounted for 10.9%. The results were consistent with previous industry observations: Over 70% of aviation accidents have human factor causes. Adverse weather was seen to be a common secondary casual factor. Changes in flight training and risk management methods may alleviate the high number of accidents in Africa.

Asiana Airlines Flight 214

2014 ◽  
Vol 4 (2) ◽  
pp. 113-121 ◽  
Author(s):  
Stephanie Chow ◽  
Stephen Yortsos ◽  
Najmedin Meshkati
Keyword(s):  
Human Factors ◽  
Aviation Safety ◽  
Cultural Factors ◽  
Vital Role ◽  
Cultural Issues ◽  
Flight Crew ◽  
Pilot Performance ◽  
Engineering Designs ◽  
Flight Deck

This article focuses on a major human factors–related issue that includes the undeniable role of cultural factors and cockpit automation and their serious impact on flight crew performance, communication, and aviation safety. The report concentrates on the flight crew performance of the Boeing 777–Asiana Airlines Flight 214 accident, by exploring issues concerning mode confusion and autothrottle systems. It also further reviews the vital role of cultural factors in aviation safety and provides a brief overview of past, related accidents. Automation progressions have been created in an attempt to design an error-free flight deck. However, to do that, the pilot must still thoroughly understand every component of the flight deck – most importantly, the automation. Otherwise, if pilots are not completely competent in terms of their automation, the slightest errors can lead to fatal accidents. As seen in the case of Asiana Flight 214, even though engineering designs and pilot training have greatly evolved over the years, there are many cultural, design, and communication factors that affect pilot performance. It is concluded that aviation systems designers, in cooperation with pilots and regulatory bodies, should lead the strategic effort of systematically addressing the serious issues of cockpit automation, human factors, and cultural issues, including their interactions, which will certainly lead to better solutions for safer flights.

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