Understanding Monitoring Technologies for Adults With Pain: Systematic Literature Review

Abstract

BackgroundMonitoring of patients may decrease treatment costs and improve quality of care. Pain is the most common health problem that people seek help for in hospitals. Therefore, monitoring patients with pain may have significant impact in improving treatment. Several studies have studied factors affecting pain; however, no previous study has reviewed the contextual information that a monitoring system may capture to characterize a patient’s situation.ObjectiveThe objective of this study was to conduct a systematic review to (1) determine what types of technologies have been used to monitor adults with pain, and (2) construct a model of the context information that may be used to implement apps and devices aimed at monitoring adults with pain.MethodsA literature search (2005-2015) was conducted in electronic databases pertaining to medical and computer science literature (PubMed, Science Direct, ACM Digital Library, and IEEE Xplore) using a defined search string. Article selection was done through a process of removing duplicates, analyzing title and abstract, and then reviewing the full text of the article.ResultsIn the final analysis, 87 articles were included and 53 of them (61%) used technologies to collect contextual information. A total of 49 types of context information were found and a five-dimension (activity, identity, wellness, environment, physiological) model of context information to monitor adults with pain was proposed, expanding on a previous model. Most technological interfaces for pain monitoring were wearable, possibly because they can be used in more realistic contexts. Few studies focused on older adults, creating a relevant avenue of research on how to create devices for users that may have impaired cognitive skills or low digital literacy.ConclusionsThe design of monitoring devices and interfaces for adults with pain must deal with the challenge of selecting relevant contextual information to understand the user’s situation, and not overburdening or inconveniencing users with information requests. A model of contextual information may be used by researchers to choose possible contextual information that may be monitored during studies on adults with pain.

Understanding the Experience of Cancer Pain From the Perspective of Patients and Family Caregivers to Inform Design of an In-Home Smart Health System: Multimethod Approach

“…A better understanding of the impact of variables that influence cancer pain in the home setting can facilitate the design of tailored systems equipped to measure and assess the most salient variables. Although we did not detect statistically significant differences between patient and caregiver mean impact scores (most likely due to our small sample size and the possible influence of participants being interviewed together), our results make an important contribution and extend existing work [ 30 , 73 ] as they (1) focus on perceived influences on cancer pain from both the patient and caregiver perspective; (2) consider a holistic set of environmental and contextual variables; (3) suggest important data collection features to include in remote symptom monitoring systems; and (4) provide initial insights into the impact of critical variables that may influence cancer pain, which can be built upon for future inquiry. The lack of a significant difference may suggest that patients and caregivers are largely in sync about what impacts pain, which could be helpful and productive.…”

“…Although the literature richly describes the experience and consequences of poorly managed cancer pain within the home setting [ 4 , 5 , 24 , 25 ], gaps exist in understanding real-time, dynamic contextual factors that may worsen or mitigate the experience of cancer pain from the perspectives of patients and family caregivers [ 4 , 15 , 26 - 30 ]. Smart health (eg, wireless/mobile technology and user interfaces) is increasingly being utilized to improve remote symptom monitoring and management [ 31 , 32 ], but it is not always designed with meaningful end-user input [ 33 ] and may not be appropriate or feasible for the unique needs of patients and caregivers coping with the stressors of advanced, late-stage illness, limiting its ultimate utility and effectiveness [ 34 , 35 ].…”

“…Smart health (eg, wireless/mobile technology and user interfaces) is increasingly being utilized to improve remote symptom monitoring and management [ 31 , 32 ], but it is not always designed with meaningful end-user input [ 33 ] and may not be appropriate or feasible for the unique needs of patients and caregivers coping with the stressors of advanced, late-stage illness, limiting its ultimate utility and effectiveness [ 34 , 35 ]. Relatedly, ever-evolving technological capabilities can capture a large range of data, but it is not always clear which variables, especially environmental, are most essential and how they should be prioritized [ 30 ].…”

Optimizing telehealth pain care after COVID-19

“…25 As accepted with in-person pain management, patient assessment would include not only pain reports but broader psychosocial functions as well (eg, pain interference, function, mood, and sleep) to facilitate evaluations and inform treatment options. 14 , 32 , 59 M-Health technology (eg, web-based questionnaires completed at regular intervals and electronic diaries for more granular information) 74 can be incorporated into the telehealth clinical flow to seamlessly capture these outcomes over time. Wearable user interfaces (eg, accelerometers and mobile phones) 74 can also be used to track changes in physical activity and sleep.…”

Monitoring Older Adults’ Health Information Using Mobile Technology: A Systematic Literature Review

“…Several systematic reviews related to technology for health management for the elderly have been conducted. Some studies have considered publications in a short time span (e.g., [57]), while others have considered specific problem areas such as pain [58], cardiovascular disease [14], or balance and fall risk assessments [59]. In addition, some research has focused on interventions that use mobile technology to alter physical activity, sedentary behavior, and sleep in older adults [60].…”