The effect of positive mood on intention to use computerized decision aids

While psychology research indicates that positive mood enhances cognition and behavior, MIS researchers have largely ignored the potential effects of positive mood on user acceptance of new information technologies (IT). Using two cognitive theories about mood and memory, positive mood theory and the affect infusion model (AIM), this study develops hypotheses about users’ acceptance of new IT under two mood conditions and two levels of uncertainty. These hypotheses are investigated via a lab experiment using a computerized decision aid. The lab experiment found that positive mood increased acceptance, as compared to a control group, under both levels of uncertainty. These results held for both induced and naturally occurring positive mood. The results for the high uncertainty condition along with results of two post-hoc tests are consistent with positive mood theory, but not with the AIM. These results indicate that mood is an important focus for future MIS acceptance research, which should be based on positive mood theory rather than the AIM

Effects of smoking and nicotine withdrawal on prospective memory

Prospective memory (PM) refers to the ability to successfully remember an intention to be carried out in the future. The current study investigated the effects of cigarette smoking and nicotine withdrawal on PM. Smokers were randomly assigned to one of two conditions: nondeprived or deprived of nicotine for the 24-hours preceding the appointment. Nonsmokers were included for comparison. To mimic the experience of smokers during cessation attempts and to assess the potential additive effect of withdrawal, all smokers engaged in a cue reactivity task with the intent of increasing craving to comparable levels across the smoker groups. Despite equivalent use of memory strategies between groups, all 3 subscales of the self-report PM measure were significantly different between smokers and nonsmokers. Contrary to hypotheses, nondeprived smokers, not deprived smokers, demonstrated the lowest levels of PM across measures. As predicted, nonsmokers demonstrated the highest levels of PM performance across all measures. Withdrawal appeared to negatively influence lexical decisions and reaction times. Computerized PM performance did not correlate with self-reported everyday PM failures, and affect was related only to the self-report PM not the computerized tasks. Results suggest that PM impairment is related to smoking, but is not worsened by withdrawal, and point toward a potential mechanism through which coping response execution failures occur during cessation attempts

Moods and Their Relevance to Systems Usage Models within Organizations: An Extended Framework

Traditionally, information systems (IS) usage models have examined user behavior within a cognitive framework, that is, these models suggest that a user’s cognition influences his/her IS usage behavior. Research over the past three decades has shown that mood, one’s global feeling state at a given time, can significantly impact a person’s cognitive processes. Mood effects on cognition are particularly relevant to organizational settings. Because moods are pervasive, they provide a stable context for cognitive processes that influence behavior at work; therefore, the inclusion of mood in individual IS usage models that support organizational tasks is both relevant and necessary. Because positive mood can enhance performance under certain circumstances, mood management is also relevant to IS usage models. Thus, we highlight how moods can be managed via IS and propose a model that takes into account users’ moods at the time they work with a system. This model provides an extended framework for incorporating relevant mood literature into current IS usage behavioral models. With this model, researchers can examine certain aspects of the model (such as how IS design can influence user feeling states or how users’ moods can impact their behavior), or conduct more comprehensive research using the entire model. This model can contribute to theory by providing a more complete picture of user behavior, and contribute to practice by helping mangers plan for desired outcomes

Modeling the Longitudinality of User Acceptance of Technology with an Evidence-Adaptive Clinical Decision Support System

This paper presents multiple innovations associated with an electronic health record system developed to support evidence-based medicine practice, and highlights a new construct, based on the technology acceptance model, to explain end users’ acceptance of this technology through a lens of continuous behavioral adaptation and change. We show that this new conceptualization of technology acceptance reveals a richer level of detail of the developmental course whereby individuals adjust their behavior gradually to assimilate technology use. We also show that traditional models such as technology acceptance model (TAM) are not capable of delineating this longitudinal behavioral development process. Our TAM-derived analysis provides lens through which we summarize the significance of this project to research and practice. We show that our application is an excellent exemplar of the “end-to-end” IS design realization process; it has drawn upon multiple disciplines to formulate and solve challenges in medical knowledge engineering, just-in-time provisioning of computerized decision-support advice, diffusion of innovation and individual users’ technology acceptance, usability of human-machine interfaces in healthcare, and sociotechnical issues associated with integrating IT applications into a patient care delivery environment

Can a Reasonable Time Limit Improve the Effective Usage of a Computerized Decision Aid?

This study examines the impact of a reasonable time limit on the effective usage of a computerized decision aid. Using current decision making models, a theoretical argument about decision aid usage is developed. This argument is then investigated via two lab experiments. The first experiment determines a reasonable time limit for the task used in the study. The second experiment investigates users’ behavior and heart rate variability under this time limit. The results of our study indicate that the reasonable time limit determined in the first study improved effective utilization of the computerized decision aid. The analysis of heart rate variability provides evidence that the given time constraint improved users’ cognitive coherence

Impact of a Workplace Stress Reduction Program on Blood Pressure and Emotional Health in Hypertensive Employees

This study examined the impact of a workplace-based stress management program on blood pressure (BP), emotional health, and workplace-related measures in hypertensive employees of a global information technology company

The effect of positive emotion and perceived risk on usage intention to online decision aids

Abstract Although perceived risk has a negative effect on usage intention toward new information technology, both perceived risk and usage intention are the results of cognitive processes, so they are inevitably influenced by emotion. Based on positive mood theory and the appraisal-tendency framework (ATF), a laboratory experiment using online decision aids with 126 participants was conducted. The results indicate that positive emotion (happy emotion in the current study) can increase usage intention and decrease perceived risk, while perceived risk decreases usage intention. Further investigation finds that perceived risk is a mediator between emotion and usage intention

Can Use of Digital Technologies by People with Dementia Improve Self-Management and Social Participation? A Systematic Review of Effect Studies

There is increasing interest in the use of technology to support social health in dementia. The primary objective of this systematic review was to synthesize evidence of effectiveness of digital technologies used by people with dementia to improve self-management and social participation. Records published from 1 January 2007 to 9 April 2020 were identified from Pubmed, PsycInfo, Web of Science, CINAHL, and the Cochrane Central Register of Controlled Trials. Controlled interventional studies evaluating interventions based on any digital technology were included if: primary users of the technology had dementia or mild cognitive impairment (MCI); and the study reported outcomes relevant to self-management or social participation. Studies were clustered by population, intervention, and outcomes, and narrative synthesis was undertaken. Of 1394 records identified, nine met the inclusion criteria: two were deemed to be of poor methodological quality, six of fair quality, and one of good quality. Three clusters of technologies were identified: virtual reality, wearables, and software applications. We identified weak evidence that digital technologies may provide less benefit to people with dementia than people with MCI. Future research should address the methodological limitations and narrow scope of existing work. In the absence of strong evidence, clinicians and caregivers must use their judgement to appraise available technologies on a case-by-case basis

Cognitive Training Interventions for Patients with Alzheimer's Disease : A Systematic Review

Background: Cognitive training (CT) refers to guided cognitive exercises designed to improve specific cognitive functions, as well as enhance performance in untrained cognitive tasks. Positive effects of CT on cognitive functions in healthy elderly people and persons with mild cognitive impairment have been reported, but data regarding the effects of CT in patients with dementia is unclear. Objective: We systematically reviewed the current evidence from randomized controlled trials (RCTs) to find out if CT improves or stabilizes cognition and/or everyday functioning in patients with mild and moderate Alzheimer's disease. Results: Altogether, 31 RCTs with CT as either the primary intervention or part of a broader cognitive or multi-component intervention were found. A positive effect was reported in 24 trials, mainly on global cognition and training-specific tasks, particularly when more intensive or more specific CT programs were used. Little evidence of improved everyday functioning was found. Conclusions: Despite some positive findings, the inaccurate definitions of CT, inadequate sample sizes, unclear randomization methods, incomplete datasets at follow-up and multiple testing may have inflated the results in many trials. Future high quality RCTs with appropriate classification and specification of cognitive interventions are necessary to confirm CT as an effective treatment option in Alzheimer's disease.Peer reviewe

Technology-supported shared decision-making in chronic conditions:a systematic review of randomized controlled trials

Objectives: To describe the role of patients with a chronic disease, healthcare professionals (HCPs) and technology in shared decision making (SDM) and the use of clinical decision support systems (CDSSs), and to evaluate the effectiveness of SDM and CDSSs interventions. Methods: Randomized controlled studies published between 2011 and 2021 were identified and screened independently by two reviewers, followed by data extraction and analysis. SDM elements and interactive styles were identified to shape the roles of patients, HCPs and technology. Results: Forty-three articles were identified and reported on 21 SDM-studies, 15 CDSS-studies, 2 studies containing both an SDM-tool and a CDSS, and 5 studies with other decision support components. SDM elements were mostly identified in SDM-tools and interactions styles were least common in the other decision support components. Conclusions: Patients within the included RCTs mainly received information from SDM-tools and occasionally CDSSs when it concerns treatment strategies. HCPs provide and clarify information using SDM-tools and CDSSs. Technology provides interactions, which can support more active SDM. SDM-tools mostly showed evidence for positive effects on SDM outcomes, while CDSSs mostly demonstrated positive effects on clinical outcomes. Practice implications: Technology-supported SDM has potential to optimize SDM when patients, HCPs and technology collaborate well together.</p