From intention to behavior: Within- and between-person moderators of the relationship between intention and physical activity

Intention is a proximal predictor of behavior in many theories of behavior change, but intentions to be physically active do not always translate to actual physical activity. Little research has examined intensive longitudinal changes in physical activity and corresponding within-person moderators needed to elucidate the mechanisms, hurdles, and facilitators of individuals' everyday physical activity behaviors. The present study set out to evaluate the possible moderators of the intention-physical activity relationship across within-person and between-person levels, including cross-level interactions. Data comprise the first intensive measurement burst (14 days) of the longitudinal prospective Healthy Aging in Industrial Environment (HAIE) study, with N = 1135 participants (N = 10,030 person-days), aged 18-65. Physical activity was operationalized as step counts measured objectively using Fitbit Charge 3/4 fitness monitor. Intention, barriers to physical activity, and social support for physical activity were measured daily via smartphone surveys. Stable characteristics, i.e., physical activity habit and exercise identity, were measured using an online questionnaire. A multilevel moderation regression model with Bayesian estimator was fitted. At the within-person level, the relation between intention and steps was weaker on days when barriers were more severe than usual for a given person (Estimate = -0.267; CI95 = [-0.340, -0.196]) and social support was below average for a given person (Est = 0.143; CI95 = [0.023, 0.262]). Additionally, the daily intention-behavior relationship was stronger for people with lower average severity of barriers (Est = -0.153; CI95 = [-0.268, -0.052]), higher exercise identity (Est = 0.300; CI95 = [0.047, 0.546]), men (Est = -1.294, CI95 = [-1.854, -0.707]), and older individuals (Est = 0.042, CI95 = [0.017, 0.064]). At the between-person level, only physical activity habit strengthened the intention-behavior link (Est = 0.794; CI95 = [0.090, 1.486]). Our results underscore the need to separate the between-person differences from the within-person fluctuations to better understand the individual dynamics in physical activity behaviors. Personalized interventions aimed at helping individuals translate intentions to actual physical activity could be tailored and become more intensive when there is a higher risk of intention-behavior gap on a given day for a specific individual (i.e., a day with more severe barriers and less social support), by increasing the dosage or deploying more precisely targeted intervention strategies and components. In addition, interventionists should take gender and age into account when tailoring everyday strategies to help individuals act on their intentions.

Multiple Perspectives on the Adoption of SMART Technologies for Improving Care of Older People: Mixed Methods Study

BACKGROUND

Despite the ever-increasing offering of SMART technologies (ie, computer-controlled devices acting intelligently and capable of monitoring, analyzing or reporting), a wide gap exists between the development of new technological innovations and their adoption in everyday care for older adults.

OBJECTIVE

This study aims to explore the barriers and concerns related to the adoption of SMART technologies among different groups of stakeholders.

METHODS

Data from 4 sources were used: semistructured in-person or internet-based interviews with professional caregivers (n=12), structured email interviews with experts in the area of aging (n=9), a web-based survey of older adults (>55 years) attending the Virtual University of the Third Age (n=369), and a case study on the adoption of new technology by an older adult care facility.

RESULTS

Although all stakeholders noted the potential of SMART technologies to improve older adult care, multiple barriers to their adoption were identified. Caregivers perceived older adults as disinterested or incompetent in using technology, reported preferring known strategies over new technologies, and noted own fears of using technology. Experts viewed technologies as essential but expressed concerns about cost, low digital competency of older adults, and lack of support or willingness to implement technologies in older adult care. Older adults reported few concerns overall, but among the mentioned concerns were lack of ability or interest, misuse of data, and limited usefulness (in specific subgroups or situations). In addition, older adults' ratings of the usefulness of different technologies correlated with their self-rating of digital competency (r=0.258; P<.001).

CONCLUSIONS

Older adults appeared to have more positive views of various technologies than professional caregivers; however, their concerns varied by the type of technology. Lack of competence and lack of support were among the common themes, suggesting that educationally oriented programs for both older adults and their caregivers should be pursued.

Feasibility of Real-time Behavior Monitoring Via Mobile Technology in Czech Adults Aged 50 Years and Above: 12-Week Study With Ecological Momentary Assessment

Background

Czech older adults have lower rates of physical activity than the average population and lag behind in the use of digital technologies, compared with their peers from other European countries.

Objective

This study aims to assess the feasibility of intensive behavior monitoring through technology in Czech adults aged ≥50 years.

Methods

Participants (N=30; mean age 61.2 years, SD 6.8 years, range 50-74 years; 16/30, 53% male; 7/30, 23% retired) were monitored for 12 weeks while wearing a Fitbit Charge 2 monitor and completed three 8-day bursts of intensive data collection through surveys presented on a custom-made mobile app. Web-based surveys were also completed before and at the end of the 12-week period (along with poststudy focus groups) to evaluate participants’ perceptions of their experience in the study.

Results

All 30 participants completed the study. Across the three 8-day bursts, participants completed 1454 out of 1744 (83% compliance rate) surveys administered 3 times per day on a pseudorandom schedule, 451 out of 559 (81% compliance rate) end-of-day surveys, and 736 episodes of self-reported planned physical activity (with 29/736, 3.9% of the reports initiated but returned without data). The overall rating of using the mobile app and Fitbit was above average (74.5 out of 100 on the System Usability Scale). The majority reported that the Fitbit (27/30, 90%) and mobile app (25/30, 83%) were easy to use and rated their experience positively (25/30, 83%). Focus groups revealed that some surveys were missed owing to notifications not being noticed or that participants needed a longer time window for survey completion. Some found wearing the monitor in hot weather or at night uncomfortable, but overall, participants were highly motivated to complete the surveys and be compliant with the study procedures.

Conclusions

The use of a mobile survey app coupled with a wearable device appears feasible for use among Czech older adults. Participants in this study tolerated the intensive assessment schedule well, but lower compliance may be expected in studies of more diverse groups of older adults. Some difficulties were noted with the pairing and synchronization of devices on some types of smartphones, posing challenges for large-scale studies.

Who Is Smart with Their Smartphones? Determinants of Smartphone Security Behavior

Smartphones have recently become a major target for cybercriminals due to large amounts of sensitive data and credentials being stored on the devices. To protect themselves against cyberthreats, users can employ a range of security behaviors. Although research has largely focused on computer security, relatively little is known about personal smartphone security behavior. The goal of our study was to evaluate determinants of smartphone security behavior based on the combination of the Health Belief Model and Protection Motivation Theory. We extended the models by including the construct of general security orientation. We also developed a smartphone security behavior scale that measured various aspects of this behavior. The sample included 331 Czech Android smartphone users aged between 26 and 81 years who were not IT specialists by employment or education. Path analysis showed that individuals who perceived a potential smartphone security threat as more severe, had higher smartphone self-efficacy, and general orientation and interest in digital security, and less personal experience with a digital security incident reported more secure behavior on their smartphones. Perceived susceptibility to security threats and family and friends' previous experience with digital security incidents did not predict smartphone security behavior. General security orientation affected smartphone security behavior also indirectly through perceived severity. These findings have theoretical implications for the models and also emphasize the importance of general digital security awareness as well as smartphone training to increase smartphone security behavior.

Running and Physical Activity in an Air-Polluted Environment: The Biomechanical and Musculoskeletal Protocol for a Prospective Cohort Study 4HAIE (Healthy Aging in Industrial Environment-Program 4)

Far too little attention has been paid to health effects of air pollution and physical (in)activity on musculoskeletal health. The purpose of the Healthy aging in industrial environment study (4HAIE) is to investigate the potential impact of physical activity in highly polluted air on musculoskeletal health. A total of 1500 active runners and inactive controls aged 18–65 will be recruited. The sample will be recruited using quota sampling based on location (the most air-polluted region in EU and a control region), age, sex, and activity status. Participants will complete online questionnaires and undergo a two-day baseline laboratory assessment, including biomechanical, physiological, psychological testing, and magnetic resonance imaging. Throughout one-year, physical activity data will be collected through Fitbit monitors, along with data regarding the incidence of injuries, air pollution, psychological factors, and behavior collected through a custom developed mobile application. Herein, we introduce a biomechanical and musculoskeletal protocol to investigate musculoskeletal and neuro-mechanical health in this 4HAIE cohort, including a design for controlling for physiological and psychological injury factors. In the current ongoing project, we hypothesize that there will be interactions of environmental, biomechanical, physiological, and psychosocial variables and that these interactions will cause musculoskeletal diseases/protection.

The Role of Psychological Factors in Older Adults' Readiness to Use eHealth Technology: Cross-Sectional Questionnaire Study

BACKGROUND

Information and communication technology (ICT) use among older adults has been on the rise in recent years. However, the predictors and mechanisms behind older adults' acceptance and use of ICT are not clear.

OBJECTIVE

This study aimed to systematically describe ICT usage among Czech older adults and to evaluate the factors influencing their ICT use and readiness to use digital technology to promote health (eHealth readiness). The primary focus was on psychological factors and the role of persons close to older adults.

METHODS

The research utilized cross-sectional survey data from a quota-based sample of Czech older adults (>50 years) and persons close to them further referred to as close persons (N=250 dyads). A structural equation modeling framework was used to evaluate relationships between psychological factors, ICT use, and eHealth readiness.

RESULTS

Czech older adults' use of ICT is low with the exception of cell phone usage (cell phone usage by 173/250, 69.2%; other devices used by 50/250, 20.0% of older adults or less). Apart from age (β=-.21; P<.001), eHealth readiness was predicted by ICT use (β=.65; P<.001). eHealth readiness was also indirectly affected by the need for cognitive closure (NFCC): individuals with a high need for closure perceived more barriers to ICT (β=.23; P=.01) and more reported barriers were linked to lower ICT usage (β=-.21; P=.001). The expected positive relationships between eHealth readiness of persons close to older adults and ICT use and eHealth readiness of older adults were not significant, but the total effect of eHealth readiness of persons close to older adults on eHealth readiness of older adults was positive and significant (β=.18; P=.01), indicating some level of influence of persons close to them on older adults' attitudes and behaviors.

CONCLUSIONS

This study provided the first systematic examination of Czech older adults' ICT usage and eHealth readiness. Novel predictors (NFCC and close persons' variables) were evaluated and yielded actionable results. More research is needed to clarify the role of persons close to older adults.