Background The increasing digitization of health care services with enhanced access to fast internet connections, along with wide use of smartphones, offers the opportunity to get health advice or treatment remotely. For service providers, it is important to consider how consumers can take full advantage of available services and how this can create an enabling environment. However, it is important to consider the digital context and the attributes of current and future users, such as their readiness (ie, knowledge, skills, and attitudes, including trust and motivation). Objective The objective of this study was to evaluate how the eHealth Literacy Questionnaire (eHLQ) combined with selected dimensions from the Health Education Impact Questionnaire (heiQ) and the Health Literacy Questionnaire (HLQ) can be used together as an instrument to characterize an individual’s level of health technology readiness and explore how the generated data can be used to create health technology readiness profiles of potential users of health technologies and digital health services. Methods We administered the instrument and sociodemographic questions to a population of 305 patients with a recent cancer diagnosis referred to rehabilitation in a setting that plans to introduce various technologies to assist the individuals. We evaluated properties of the Readiness and Enablement Index for Health Technology (READHY) instrument using confirmatory factor analysis, convergent and discriminant validity analysis, and exploratory factor analysis. To identify different health technology readiness profiles in the population, we further analyzed the data using hierarchical and k-means cluster analysis. Results The confirmatory factor analysis found a suitable fit for the 13 factors with only 1 cross-loading of 1 item between 2 dimensions. The convergent and discriminant validity analysis revealed many factor correlations, suggesting that, in this population, a more parsimonious model might be achieved. Exploratory factor analysis pointed to 5 to 6 constructs based on aggregates of the existing dimensions. The results were not satisfactory, so we performed an 8-factor confirmatory factor analysis, resulting in a good fit with only 1 item cross-loading between 2 dimensions. Cluster analysis showed that data from the READHY instrument can be clustered to create meaningful health technology readiness profiles of users. Conclusions The 13 dimensions from heiQ, HLQ, and eHLQ can be used in combination to describe a user’s health technology readiness level and degree of enablement. Further studies in other populations are needed to understand whether the associations between dimensions are consistent and the number of dimensions can be reduced.

Creating well-designed clinical patient programs that actively involve the spouse appears to promote empowerment (meaning, self-efficacy, positive impact, and self-determination) in spouses. Spousal participation in clinical patient programs can give spouses relief from anxieties while recognizing them as a vital support for their husband.

Background: During recent years, there has been an increased focus on technology within cancer survivorship and physical activity rehabilitation. Failure to acknowledge the individuals wishes and/or limitations in the use of technology introduces risk of neglecting or excluding low-resource individuals, thus adding to an already existing inequity within cancer management. It is important to identify vulnerable sub-populations with particular needs when introducing health technology to offer appropriate rehabilitation and support individuals in taking advantage of technology in their physical activity rehabilitation. We report how a population of cancer survivors referred to municipality-based rehabilitation can be segmented, according to their receptiveness and readiness for health technology utilization, to understand their potential barriers towards using technology. Methods: We used a cross-sectional design with convenience sampling among Danish cancer survivors (n ¼ 305) referred to rehabilitation. Participants completed a questionnaire survey covering background information and a new tool to assess self-reported health technology readiness. Demographic, disease and behavioral factors were described in relation to the participants' receptiveness to use technology in physical activity rehabilitation. Participants were stratified according to their health technology readiness and the resulting groups described with regards to the above-mentioned factors. Results: Almost 30% of the participants were un-receptive to use technology in relation to physical activity rehabilitation and were characterized by being more vulnerable with regards to sociodemographic characteristics and scoring lower on dimensions related to eHealth literacy. Stratification of the participants according to their health technology readiness profile revealed four distinct profiles that were significantly different in sociodemographic, disease and behavioral factors. Conclusion:To reduce the risk of alienating low-resource individuals when introducing health technology, evaluation of the individuals' receptiveness to use technology in a rehabilitation context and their readiness for health technology may help tailor the extent to which technology should be offered to assist the cancer survivors.

Background Information technologies (IT) are increasingly implemented in type 2 diabetes (T2D) treatment as a resource for remotely supported health care. However, possible pitfalls of introducing IT in health care are generally overlooked. Specifically, the effectiveness of IT to improve health care may depend on the user’s readiness for health technology. Objective We aim to investigate readiness for health technology in relation to mental well-being, sociodemographic, and disease-related characteristics among individuals with T2D. Methods Individuals with T2D (aged ≥18 years) who had been referred to self-management education, exercise, diet counseling, smoking cessation, or alcohol counseling completed a questionnaire survey covering (1) background information, (2) the 5-item World Health Organization Well-Being Index (WHO-5), (3) receptiveness to IT use in physical activity, and (4) the Readiness and Enablement Index for Health Technology (READHY), constituted by dimensions related to self-management, social support, and eHealth literacy. Individuals were divided into profiles using cluster analysis based on their READHY scores. Outcomes included differences across profiles in mental well-being, sociodemographic, and disease-related characteristics. Results Participants in the study were 155 individuals with T2D with a mean age of 60.2 (SD 10.7) years, 55.5% (86/155) of which were men and 44.5% (69/155) of which were women. Participants were stratified into 5 health technology readiness profiles based on the cluster analysis: Profile 1, high health technology readiness; Profile 2, medium health technology readiness; Profile 3, medium health technology readiness and high level of emotional distress; Profile 4, medium health technology readiness and low-to-medium eHealth literacy; Profile 5, low health technology readiness. No differences in sociodemographic and disease-related characteristics were observed across profiles; however, we identified 3 vulnerable subgroups of individuals: Profile 3 (21/155, 13.5%), younger individuals (mean age of 53.4 years, SD 8.9 years) with low mental well-being (mean 42.7, SD 14.7) and emotional distress (mean 1.69, SD 0.38); Profile 4 (20/155, 12.9%), older individuals (mean age 66.3 years, SD 9.0 years) with less IT use (50.0% used IT for communication) and low-to-medium eHealth literacy; and Profile 5 (36/155, 23.2%) with low mental well-being (mean 43.4, SD 20.1) and low readiness for health technology. Conclusions Implementation of IT in health care of individuals with T2D should be based on comprehensive consideration of mental well-being, emotional distress, and readiness for health technology rather than sociodemographic and disease-related characteristics to identify the individuals in need of social support, self-management education, and extensive IT support. A one-size-fits-all approach to IT implementation in health care will potentially increase the risk of treatment failure among the most vulnerable individuals.

Background Physical activity is associated with a positive prognosis in cancer survivors and may decrease the risk of adverse effects of treatment. Accordingly, physical activity programs are recommended as a part of cancer rehabilitation services. Digital technology may support cancer survivors in increasing their level of physical activity and increase the reach or efficiency of cancer rehabilitation services, yet it also comes with a range of challenges. Objective The aim of this qualitative study was to explore cancer survivors’ receptiveness to using digital technology as a mode of support to increase their physical activity in a municipality-based cancer rehabilitation setting. Methods Semistructured interviews were conducted with 11 cancer survivors (3 males, 8 females, age range 32-82 years) who were referred for cancer rehabilitation and had participated in a questionnaire survey using the Readiness and Enablement Index for Health Technology (READHY) questionnaire. Data analysis was based on the content analysis method. Results Two themes were identified as important for the interviewees’ receptiveness to using digital technology services in connection with their physical activity during rehabilitation: their attitude toward physical activity and their attitude toward digital technology–assisted physical activity. Our results indicated that it is important to address the cancer survivors’ motivation for using technology for physical activity and their individual preferences in terms of the following: (1) incidental or structured (eg, cardiovascular and strength exercises or disease-specific rehabilitative exercises) physical activity; (2) social or individual context; and (3) instruction (know-how) or information (know-why). Conclusions The identified preferences provide new insight that complements the cancer survivors’ readiness level and can likely help designers, service providers, and caregivers provide solutions that increase patient receptiveness toward technology-assisted physical activity. Combining digital technology informed by cancer survivors’ needs, preferences, and readiness with the capacity building of the workforce can aid in tailoring digital solutions to suit not only individuals who are receptive to using such technologies but also those reluctant to do so.