App-Tailoring Requirements to Increase Stress Management Competencies Within Families: Cross-sectional Survey Study

Abstract

Background Families experiencing high levels of psychological distress are considered a particularly vulnerable population for adverse effects on mental and physical health. Moreover, highly stressed individuals engage less in mental health promoting activities and show low stress management competencies. App-based stress interventions seem promising for the treatment and prevention of stress outcomes and might be a low-threshold solution. Objective The aim of this study was to identify the requirements for a tailored app to reduce stress in a cohort of highly stressed families that have low stress management skills. Methods Parents (n=1008; age: mean 47.7 years, SD 6.1; female: 599/1008, 59.7%) completed an extensive web-based survey and were subdivided into a target (stressed individuals with low stress competency) and nontarget group according to their reported stress level and stress management competencies. Group differences were analyzed using analysis of variance. In principal component analysis with Kaiser varimax rotation, personally defined stress management goals were grouped into components. Linear regression models were also calculated. Results A 3-factor solution cumulatively explained 56% of the variance in personally defined goals of interest for stress management with (1) active strategies (25.61% explained variance), (2) general competency (17.95% explained variance) and (3) passive strategies (12.45% explained variance). The groups differed in age (F1,978=27.67, P<.001), health index (F1,958=246.14, P<.001), personally defined general-competency goal (F1,958=94.16 P<.001), as well as “information acquisition” (F1,971=14.75, P<.001) and “need for stimulation” (F1,981=54.49, P<.001) personality traits. A regression model showed that for the active strategies goals of interest, only app feature information or instructional videos had a significant effect (P=.02). The general competency factor showed none, and the passive strategies factor showed significant effects for 2 app features—suggestions for planning possible activities with the family (P=.01) and diaries for documentation and development of strategies (P=.03). Conclusions The results of this survey study highlight the need to develop an app to increase stress management competencies that takes into consideration perceived stress level, stress management skills, personality, and personally defined goals of the user. The content of the app should be tailored to previously detected personality traits, especially selective information acquisition and low need for stimulation. Furthermore, personally defined stress management goals seem to affect interest in some features.

Healthy Lifestyle Behavior, Goal Setting, and Personality among Older Adults: A Synthesis of Literature Reviews and Interviews

“…Most of the 22 research articles mentioned the types of healthy lifestyle behavior that may be affected by personality traits and goal achievement. They include exercising, participating in sports, eating a healthy diet, participating in physical activity using electronic devices [ 19 , 20 ], participating in leisure-time physical activity that is “planned, structured, repeated and with maintenance” [ 21 ], controlling one’s weight, managing one’s nutrition [ 22 ], engaging in social activities, and having intentions and beliefs about physical activity [ 23 ]. The literature indicated that people who engage in these HLBs tend to have better physical, mental, emotional, and cognitive health [ 24 ].…”

“…On the other hand, research on M-health indicated that electronic devices, such as a Fitbit, were considered to be effective in facilitating goal setting and achievements. This is because the planning, learning [ 19 ], rewarding, comparing, and sharing functions in electronic devices can trigger individuals’ motivation to achieve their desired goals [ 30 , 48 ]; it is also noteworthy that electronic devices can support personalized goals based on individual personality traits.…”

“…Hence, it is recommended that smart devices provide personalized goal setting systems in which big data can be used to provide goals or HLB plans that are tailored to users’ individual differences and personalities [ 20 ]. Bischoff [ 19 ] highlighted the importance of goal-specific apps in smart devices in being able to identify individual differences, including personality traits, levels of vulnerability, and usual health behaviors, and being able to provide suitable goal planning and management strategies, as well as relevant features for pursuing HLBs. In addition, based on the differences in physical activity outcomes among people with different personality traits in intervention studies, including personalized interventions and individualized goals based on people’s personality traits, priorities, and attitudes is also suggested, instead of standardized goals and procedures, in order to achieve positive and successful aging [ 48 , 55 , 56 ].…”

Efficacy of Individualized Sensory-Based mHealth Interventions to Improve Distress Coping in Healthcare Professionals: A Multi-Arm Parallel-Group Randomized Controlled Trial

“…One possible explanation for the limited effectiveness of our intervention, in addition to the high dropout rate, is the insufficient incorporation of health behavior change strategies. While our biofeedback app included both active and passive behavior change techniques and promoted stress management skills, some of the content proposed by Bischoff et al [ 112 ] was not implemented. Specifically, we applied individualization of app content, fulfilling common weekly goals and tasks, increasing knowledge about a healthy lifestyle, reminders for objectives, and controlling and checking progress but did not include many suggestions for activities with diaries for documentation and development of strategies or informational or instructional videos.…”

mHealth interventions to reduce stress in healthcare workers (fitcor): study protocol for a randomized controlled trial

“…Digital Interventions can be a low-threshold opportunity for health promotion and are a promising possibility to achieve prevention goals [ 69 , 70 ], even though eHealth literacy is sometimes missing [ 65 ]. The free allocation of time and flexibility of availability were evaluated on a positive note.…”