We carried out a web based survey to look at public attitudes towards using PHRs, together with genome knowledge and the cloud for well being care analysis. The response charge was 20.4% (n = 5830), and Desk 2 exhibits the individuals’ demographic traits. The respondents who selected the “different” gender classification (n = 28) had been excluded from the evaluation as a result of there weren’t sufficient of them to make sure statistical significance. Sure teams had been requested extra questions. Questions concerning genomic knowledge utilization had been addressed to direct-to-consumer (DTC) genetic testing customers (n = 151, 2.6%) and people fascinated by consuming DTC genetic testing providers (n = 1138, 19.6%). Equally, we solely addressed questions on accessing well being knowledge from wearable units (e.g., smartwatches) to individuals who indicated utilizing such units (n = 488, 8.4%).
The general public’s recognition and information of phrases regarding digital well being and BLSs
First, we examined the individuals’ recognition and information of the six phrases proven in Desk 1. Over half of the individuals indicated that they’d heard of the phrases or that they understood their meanings, as follows: genome 77.9%, genomic medication 58.1%, cloud computing 88.3%, AI 90.5%, app 96.1%, and wearable system 56.6%. Nonetheless, concerning the definitions of the phrases, over 50% answered incorrectly or selected “I don’t know,” as follows: genome 52.8%, genomic medication 50.9%, cloud computing 62.0%, app 54.6%, and wearable system 45.8%. For AI, the speed of incorrect/“don’t know” responses was 27.8%. Notably, 88.3% had at the least heard of the cloud; nevertheless, the right reply charge for his or her understanding of it was solely 38.0%.
The descriptive statistics for the digital well being BLSs had been imply 9.6, median 10.0, and SD 4.5 for all respondents (Desk 2). Statistical significance was confirmed for gender, age group, family revenue, schooling stage, occupation, and historical past of outpatient visits (p < 0.001). For the demographic traits, these in socially deprived positions tended to have decrease imply BLSs; such respondents included girls (M = 8.7, SD = 4.1), these with low annual family incomes (e.g., lower than 3 million JPY: M = 8.6, SD = 4.5), these with much less schooling (e.g., junior and senior highschool: M = 8.2, SD = 4.2), and people with unstable occupations (e.g., non permanent employees: M = 8.7, SD = 4.3; p < 0.001). Moreover, those that knew about DTC genetic testing providers had the next imply (M = 12.1, SD = 3.8) than those that didn’t (M = 7.9, SD = 4.2; t (5430) = 39.299, p < 0.001).
Public issues about sharing PHRs with out identifiers for well being care analysis
Determine 1 depicts the individuals’ issues about offering their medical file, medical check-up, genetic testing, smartphone well being apps, and wearable-device well being knowledge with out identifiers for well being care analysis. Whatever the knowledge kind, the respondents’ prime three issues had been the identical: “knowledge leakage” (≧55.5%), “knowledge getting used with out my information” (hereafter “unrecognized knowledge use”) (≧50.4%), and “unauthorized use of my knowledge” (i.e., knowledge used with out permission; hereafter “unauthorized knowledge use”) (≧48.8%). Particularly within the case of genomic testing knowledge, the chances for the aforementioned three issues and people about discrimination had been the best (knowledge leakage 61.7%, unrecognized knowledge use 60.0%, unauthorized knowledge use 56.9%, and discrimination 22.3%). Notably, of the respondents, almost 40% (≧38.5%) had been involved about attainable reidentification for every type of information used for well being care analysis regardless of the elimination of distinctive identifiers to make sure anonymity.
The outcomes of the questionnaire asking individuals about their issues concerning using various kinds of knowledge for medical analysis after their identifiable info had been eliminated. The multiple-choice solutions revealed that whatever the knowledge kind, the respondents’ prime three issues had been knowledge leakage (≧55.5%), knowledge getting used with out their information (≧50.4%), and unauthorized use of their knowledge (≧48.8%).
Relationship between the general public’s views on the cloud and digital well being BLSs
We requested the respondents about their views of the cloud itself. Desk 3 exhibits the questions and outcomes. Merchandise a requested about their issues concerning data-type dealing with by way of the cloud; merchandise b requested about their perceptions of the benefits and downsides of utilizing the cloud.
Concerning merchandise a, the respondents had been extra involved about their transaction information with monetary establishments (74.8%), their buy histories (64.1%), and their journey histories (60.0%) than with their PHRs being dealt with by way of the cloud, that’s, their medical file knowledge (54.2%), genome knowledge (53.7%), medical check-up knowledge (51.2%), smartphone well being app knowledge (48.9%), and well being knowledge from wearable units (45.7%). For all sorts of information, the imply BLS for respondents who answered that they had been “unconcerned” about their knowledge being dealt with by way of the cloud was statistically important and better than the imply for respondents who answered “involved” or “I don’t know” (p < 0.001; Desk 3, Merchandise a).
Concerning merchandise b on the benefits and challenges of the cloud, 50.2% of respondents thought-about the cloud helpful for backing up knowledge, and 45% acknowledged that the cloud was helpful for managing massive datasets. Nonetheless, 58.7% of the respondents had been involved concerning the safety of the cloud, and solely 21.1% agreed that the cloud’s safety measures had been reliable. Moreover, 52.7% had been involved about knowledge preservation following cloud supplier takeovers, and 49.6% thought-about the laws for cloud preservation insufficient. As well as, 43.8% had been involved concerning the knowledge administration location being unknown in cloud computing (Desk 3, Merchandise b).
Notably, the imply BLS for respondents who chosen “agree” (≧11.47) for all benefits listed within the questions was considerably greater than the imply for respondents who chosen “disagree” (≧8.37) or “I don’t know” (≧6.80; p < 0.001). Moreover, the imply BLS for many who chosen “agree” (≧10.93) for all issues listed within the questions was considerably greater than the imply for respondents who chosen “disagree” (≧8.99) or “I don’t know” (≧6.46; p < 0.001). In brief, the imply BLS values for each the respondents who acknowledged advantages and people involved concerning the cloud had been considerably greater than these for the opposite respondents.
Relationship between digital well being BLSs and the affect of incentives for WTSD on well being care analysis
The respondents had been divided into two teams primarily based on imply and median values: a low-BLS group (0 ≦ BLS < 10) and a high-BLS group (10 ≦ BLS ≦ 18). We then carried out a binominal logistic regression evaluation. The outcomes confirmed that the high-BLS group’s BLSs ranged from 11.0 to 18.0 (imply 14.1, median 14.0, and SD 2.1), whereas the low-BLS group’s BLSs ranged from 0.0 to 14.0 (imply 6.6, median 7.0, and SD 2.9; Desk 2). Notably, the imply and median of the high-BLS group had been roughly twice these of the low-BLS group.
Gender, age group, annual family revenue, schooling stage, occupation, marital standing, and historical past of outpatient visits had been considerably related to an inclination to be within the high-BLS group (Desk 2). As an example, males had a larger tendency to be within the high-BLS group (odds ratio [OR] = 1.90, 95% confidence interval [CI] 1.67–2.15, p < 0.001). The respondents with “5 million JPY to lower than 8 million JPY” (OR = 1.28, 95% CI 1.10–1.49, p = 0.002) and people “8 million JPY to lower than 20 million JPY” (OR = 1.62, 95% CI 1.37–1.92, p < 0.001) tended to be within the high-BLS group, in contrast to these with “3 million JPY to lower than 5 million JPY.” Concerning instructional stage, the OR for “occupational faculty or junior faculty” (OR = 1.38, 95% CI 1.18–1.6 2, p < 0.001) was bigger than that for “junior or senior highschool.” Notably, the OR for “college or graduate faculty” was greater than twice (OR = 2.71, 95% CI 2.37–3.11, p < 0.001) that for “junior or senior highschool”. Moreover, those that had a historical past of outpatient visits had a statistically important tendency to be within the high-BLS group: the values for “outpatient go to inside the previous 12 months” (OR = 1.50, 95% CI 1.30–1.74, p < 0.001) and “presently receiving outpatient care at a hospital” (OR = 1.51, 95% CI 1.32–1.73, p < 0.001) had been greater than these for “no historical past of outpatient visits”.
Though we thought-about 5 kinds of PHR knowledge, together with app and wearable system knowledge, we current the outcomes for medical file knowledge, genomic testing knowledge, and medical check-up knowledge. In Japan, medical information generally include medical check knowledge, however medical check-ups don’t. The respondents’ WTSD differed primarily based on which group used their knowledge. As well as, their WTSD differed in line with whether or not they had been within the high- or low-BLS group. Determine 2 exhibits the outcomes for every group’s willingness to share their medical file, genetic testing, and medical check-up knowledge for well being care analysis in two hypothetical conditions: (1) the respondents obtained no honorarium and (2) the respondents obtained redeemable reward factors (RRPs). The high-BLS group had a larger WTSD than the low-BLS group, even when honorariums weren’t awarded. Apart from the case of personal corporations, the proportion of respondents who indicated their WTSD with out honorariums within the high-BLS group was over 63.8%, and the proportion exceeded 70% when RRPs had been awarded for all three kinds of knowledge. Even within the low-BLS group, the willingness to share genomic testing knowledge exceeded 50% with out honorariums.
The outcomes for the low and the excessive digital well being BLS teams’ willingness to share knowledge (WTSD) for well being care analysis in two hypothetical conditions: (1) the respondents obtained no honorarium and (2) the respondents obtained redeemable reward factors (RRPs). a The outcomes of the low-BLS group, b the outcomes of the high-BLS group. Notably, even within the absence of an honorarium, the high-BLS group demonstrated the next stage of WTSD in comparison with the low-BLS group.
When RRPs had been awarded, a rise within the proportion of WTSD was noticed for every type of information in each BLS teams. The supplementary materials consists of the outcomes with out differentiating between excessive and low BLS; it exhibits that whatever the knowledge kind, the variety of respondents who had been WTSD elevated with awarded RRPs, however the improve solely reached 8.7%, whereas within the low-BLS group, the best improve was noticed at 9.1% when there have been RRPs, which was the case for sharing genomic testing knowledge with a analysis institute. Within the high-BLS group, the biggest improve was 10.2% for using medical file knowledge by the buying establishment; nevertheless, in different instances, the rise was lower than 8.5%.
Total, in each the high- and low-BLS teams, the WTSD with personal corporations was decrease than in instances the place knowledge had been shared with buying establishments or analysis institutes, no matter whether or not RRPs had been awarded.
Lastly, the variety of respondents who answered “I don’t know” concerning whether or not they would share knowledge with organizations for analysis with out honoraria was greater within the low-BLS group, particularly within the case of medical file knowledge, which was at roughly 40%, whatever the group. Nonetheless, within the high-BLS group, the utmost proportion was 20.9%.
