Factors Affecting Clinician Readiness to Adopt Smart Home Technology for Remote Health Monitoring: Systematic Review.

Background: The population of older adults worldwide continues to increase, placing higher demands on primary health care and long-term care. The costs of housing older people in care facilities have economic and societal impacts that are unsustainable without innovative solutions. Many older people wish to remain independent in their homes and age in place.

Toward Sustaining Web-Based Senior Center Programming Accessibility With and for Older Adult Immigrants: Community-Based Participatory Research Cross-Sectional Study.

Background: During the COVID-19 pandemic, many community-based organizations serving Asian Americans pivoted to provide web-based care and social services. Asian American community leaders in the United States Pacific Northwest, including Asian Health & Service Center expressed that there are older immigrant adults who experienced backlash from discrimination, fear, and anxiety owing in part to anti-Asian hate and isolation, including from infection precautions. Pivoting supported staying safe from COVID-19 transmission and anti-Asian hate crimes.

Family caregiver readiness to adopt smart home technology to monitor care-Dependent older adults: A qualitative exploratory study.

Aims: The aim of this study was to explore factors that influence family caregiver readiness to adopt health smart home technology for their care-dependent older adult family member. Health smart homes are designed to remotely monitor the health and wellness of community-dwelling older adults supporting independent living for as long as possible. Accordingly, if the health smart home is deployed into the home of a care-depended older adult, it can potentially support family caregivers by facilitating workforce participation and give piece of mind to the family caregiver who may not live close to the older adult.

Piloting Smart Home Sensors to Detect Overnight Respiratory and Withdrawal Symptoms in Adults Prescribed Opioids.

Background: Novel strategies are needed to curb the opioid overdose epidemic. Smart home sensors have been successfully deployed as digital biomarkers to monitor health conditions, yet they have not been used to assess symptoms important to opioid use and overdose risks.

Aim: This study piloted smart home sensors and investigated their ability to accurately detect clinically pertinent symptoms indicative of opioid withdrawal or respiratory depression in adults prescribed methadone.

Nurse-in-the-loop smart home detection of health events associated with diagnosed chronic conditions: A case-event series.

Background: Telehealth and home-based care options significantly expanded during the SARS-CoV2 pandemic. Sophisticated, remote monitoring technologies now exist that support at-home care. Advances in the research of smart homes for health monitoring have shown these technologies are capable of recognizing and predicting health changes in near-real time.

Factors influencing community-dwelling older adults' readiness to adopt smart home technology: A qualitative exploratory study.

Aims: Ageing-in-place for older people could be more feasible with the support of smart home technology. Ageing in-place may maximize the independence of older adults and enhance their well-being and quality of life, while decreasing the financial burden of residential care costs, and addressing workforce shortages. However, the uptake of smart home technology is very low among older adults.

Behavioral Differences Between Subject Groups Identified Using Smart Homes and Change Point Detection.

With the arrival of the internet of things, smart environments are becoming increasingly ubiquitous in our everyday lives. Sensor data collected from smart home environments can provide unobtrusive, longitudinal time series data that are representative of the smart home resident's routine behavior and how this behavior changes over time. When longitudinal behavioral data are available from multiple smart home residents, differences between groups of subjects can be investigated.

Interpreting Health Events in Big Data Using Qualitative Traditions.

The training of artificial intelligence requires integrating real-world context and mathematical computations. To achieve efficacious smart health artificial intelligence, contextual clinical knowledge serving as ground truth is required. Qualitative methods are well-suited to lend consistent and valid ground truth.

A nurse-driven method for developing artificial intelligence in "smart" homes for aging-in-place.

Objectives: To offer practical guidance to nurse investigators interested in multidisciplinary research that includes assisting in the development of artificial intelligence (AI) algorithms for "smart" health management and aging-in-place.

Methods: Ten health-assistive Smart Homes were deployed to chronically ill older adults from 2015 to 2018. Data were collected using five sensor types (infrared motion, contact, light, temperature, and humidity).

A conceptual framework for clinicians working with artificial intelligence and health-assistive Smart Homes.

The Smart Home designed to extend older adults independence is emerging as a clinical solution to the growing ageing population. Nurses will and should play a key role in the development and application of Smart Home technology. Accordingly, conceptual frameworks are needed for nurse scientists who are collaborating with multidisciplinary research teams in developing an intelligent Smart Home that assists with managing older adults' health.

Iterative Design of Visual Analytics for a Clinician-in-the-Loop Smart Home.

In order to meet the health needs of the coming "age wave," technology needs to be designed that supports remote health monitoring and assessment. In this study we design clinician in the loop (CIL), a clinician-in-the-loop visual interface, that provides clinicians with patient behavior patterns, derived from smart home data. A total of 60 experienced nurses participated in an iterative design of an interactive graphical interface for remote behavior monitoring.

Using Smart City Technology to Make Healthcare Smarter.

Smart cities use information and communication technologies (ICT) to scale services include utilities and transportation to a growing population. In this article we discuss how smart city ICT can also improve healthcare effectiveness and lower healthcare cost for smart city residents. We survey current literature and introduce original research to offer an overview of how smart city infrastructure supports strategic healthcare using both mobile and ambient sensors combined with machine learning.

Data Collection via In-Depth Email Interviewing: Lessons From the Field.

This methods article is a reflection on the use of in-depth email interviewing in a qualitative descriptive study. The use of emailing to conduct interviews is thought to be an effective way to collect qualitative data. Building on current methodological literature in qualitative research regarding in-depth email interviewing, we move the conversation toward elicitation of quality data and management of multiple concurrent email interviews.

Health-Assistive Smart Homes for Aging in Place: Leading the Way for Integration of the Asian Immigrant Minority Voice.

Caring for America's aging population is a complex humanitarian issue. The number of older adults is expected to increase to 98.5 million by 2060 with a 295% growth in foreign-born older adults, including Asian immigrants.

Interactive CO-learning for Research Engagement and Education (I-COREE) Curriculum to Build Capacity Between Community Partners and Academic Researchers.

The voice of diverse communities continues to be minimal in academic research. Few models exist for education and training of new research topics and terminology and building partnership capacity in community-engaged research. Little is known about integrative education and training when building participatory research partnerships for sustainability and developing trust and rapport.

Research education: findings of a study of teaching-learning research using multiple analytical perspectives.

This multimethod, qualitative study provides results for educators of nursing doctoral students to consider. Combining the expertise of an empirical analytical researcher (who uses statistical methods) and an interpretive phenomenological researcher (who uses hermeneutic methods), a course was designed that would place doctoral students in the midst of multiparadigmatic discussions while learning fundamental research methods. Field notes and iterative analytical discussions led to patterns and themes that highlight the value of this innovative pedagogical application.