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A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobile health (mHealth) applications, hold promise to provide novel insights for healthy aging and the ability to collect data between clinical care visits. Machine learning/artificial intelligence methods have the potential to uncover insights into healthy aging. Nurses and nurse informaticians have a unique lens to shape the future use of this technology.
The purpose of this research was to apply machine learning methods to MyStrengths+MyHealth de-identified data (N = 988) for adults 45 years of age and older. An exploratory data analysis process guided this work.
Overall (n = 988), the average Strength was 66.1% (SD = 5.1), average Challenges 66.5% (SD = 7.5), and average Needs 60.06% (SD = 3.1). There was a significant difference between Strengths and Needs (p < 0.001), between Challenges and Needs (p < 0.001), and no significant differences between average Strengths and Challenges. Four concept groups were identified from the data (Thinking, Moving, Emotions, and Sleeping). The Thinking group had the most statistically significant challenges (11) associated with having at least one Thinking Challenge and the highest average Strengths (66.5%) and Needs (83.6%) compared to the other groups.
This retrospective analysis applied machine learning methods to de-identified whole person health resilience data from the MSMH application. Adults 45 and older had many Strengths despite numerous Challenges and Needs. The Thinking group had the highest Strengths, Challenges, and Needs, which aligns with the literature and highlights the co-occurring health challenges experienced by this group. Machine learning methods applied to consumer health data identify unique insights applicable to specific conditions (e.g., cognitive) and healthy aging. The next steps involve testing personalized interventions with nurses leading artificial intelligence integration into clinical care.
Building resilience among nurses has been postulated as one of the key strategies to support nurses and retain them in the profession. This study aimed to evaluate the effectiveness, of spaced education pedagogy in enhancing Nurses' knowledge on emotional resilience. Secondary objectives include evaluation of the usability and acceptability of delivery of the training via a mobile application in one's own mobile device.
A quasi-experimental study with single group pre-test and post-test trial was conducted.
Full-time registered nurses working in an acute care hospital were invited to participate from June 2021 to June 2022. The group used the mobile application daily for 1 month. Pre-test measurement includes socio-demographic data and baseline resilience level before the intervention. Post-test measurement includes resilience level, usability and acceptability of mobile-assisted cognitive-behavioral therapy measured upon completion of the training. The mobile application enabled the delivery of resilience educational content in small quantities through a repeating manner, with a concurrent evaluation of learner's understanding.
When compared to their baseline (mean = 24.38, SD = 5.50), participants reported significant increase in the Connor-Davison Resilience Scale score (mean = 26.33, SD = 5.57) (t = −4.40, p < 0.001). Upon 1 month usage of the mobile application, a higher percentage of the participants reported intermediate to high level of resilience (57.4%), as compared to prior usage (54.7%). Respondents reported knowledge of most useful strategies for their daily lives including: (i) managing negative emotions (54.1%); (ii) psychoeducation about mental health and the risks of burnout (44.7%); (iii) achieving work and life balance (43.5%); and (iv) depiction of workplace scenarios to demonstrate what can be and cannot be controlled during times of change (43.5%). Participants reported usability of the mobile application with a mean SUS score 70.5 (SD = 13.0), which was considered “acceptable.” Overall, 82.3% of the participants found the mobile application appealing, 64.7% reported they were likely to use the mobile application in the future and 72.9% would recommend it to other nurses.
The mobile application provided nurses with the availability and convenience to access resilience building learning content integrated with the spaced education pedagogy.
The use of mobile-assisted cognitive behavioral training can aid in increasing nurses' resilience level. Nurses provided acceptable usability ratings and satisfactory acceptance of receiving training via the mobile application, showing promising opportunities in the improvement of overall well-being.
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