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. 2022 Nov 22:8:20552076221138316.
doi: 10.1177/20552076221138316. eCollection 2022 Jan-Dec.

HRQoL and nutritional well-being dissimilarities between two different online collection methods: Value for digital health implementation

Affiliations

HRQoL and nutritional well-being dissimilarities between two different online collection methods: Value for digital health implementation

Andrea Higuera-Gomez et al. Digit Health. .

Abstract

Background: Online health data collection has gained a reputation over the last years to record and process information about health issues for implementing digital health.

Objective: The research aim was to appraise two online methods (open and rewarded) to collect information about HRQoL and nutritional well-being and to compare the results between both surveyed populations.

Methods: This cross-sectional study is framed on the NUTRiMDEA project. Online data through two different web-based methods (open survey and rewarded survey) were retrieved to assemble data related to sociodemographic, lifestyle (diet, physical activity and sleep patterns) and general health aspects, as well as HRQoL by an evidence-based form such as the SF-12 questionnaire, the IPAQ survey, and MEDAS-14, participants were adults (>18 years old).

Results: Overall, 17,332 participants responded to the open survey (OS, n = 11,883) or the rewarded survey (RS, n = 5449). About 65.1% of the participants were female, while the mean age was in the range of 40-70 years. There were significant differences (p < 0.05) between surveyed populations in sociodemographic, lifestyle (diet and physical activity), health and HRQoL data.

Conclusions: This investigation implemented an evidence-based online questionnaire that collected demographic, lifestyle factors, phenotypic and health-related aspects as well as compared differential outcomes in HRQoL and nutritional/lifestyle well-being depending on the online mode data collection. Findings demonstrated dissimilarities in most aspects of health, HRQoL, dietary intake and physical activity records between both populations. Overall, OS sample was characterized as a healthier population with superior lifestyle habits than RS participants.

Keywords: Online data collection; digital health; eHealth; health-related quality of life; nutritional well-being; web-based health.

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Conflict of interest statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Flowchart for the NUTRiMDEA study.
Figure 2.
Figure 2.
Descriptive lifestyle and health characteristics of a population categorized by type of survey. (a) Body Mass Index (BMI), Mediterranean Diet Score (MDS), Physical Activity (PA), Physical and Mental Component Summary of SF-12 Survey (PCS12 and MCS12). (b) Diseases prevalence (%). (c) Family diseases prevalence (%). *p < 0.05, propensity score analysis was made to balance the distribution of the initial observed covariates so that they are similar among subjects in the different groups. Statistical analyses were performed using chi-square (χ2) test to compare categorical variables. T-test was used to compare the mean of parametric continuous variables.
Figure 3.
Figure 3.
Physical and mental component summary of SF-12 survey (PCS12 and MCS12) score categorized by level of physical activity (low or high), Mediterranean diet score (low or high) and type of survey (open survey and rewarded survey), (a) PCS12 total score categorized by physical activity and type of survey, (b) MCS12 total score categorized by physical activity and type of survey, (c) PCS12 total score categorized by Mediterranean diet score and type of survey, (d) MCS12 total score categorized by Mediterranean diet score and type of survey. *p < 0.05, propensity score analysis was made to balance the distribution of the initial observed covariates so that they are similar among subjects in the different groups. P-values for two-way analysis of variance (ANOVA) and Sidak post-hoc test between groups.

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