METHODS: Various combinations of keywords related to "digital health", "intervention", "workplace" and "developing country" were applied in Ovid MEDLINE, EMBASE, CINAHL Plus, PsycINFO, Scopus and Cochrane Library for peer-reviewed articles in English language. Manual searches were performed to supplement the database search. The screening process was conducted in two phases and a narrative synthesis to summarise the data. The review protocol was written prior to undertaking the review (OSF Registry:10.17605/OSF.IO/QPR9J).
RESULTS: The search strategy identified 10,298 publications, of which 24 were included. Included studies employed the following study designs: randomized-controlled trials (RCTs) (n = 12), quasi-experimental (n = 4), pilot studies (n = 4), pre-post studies (n = 2) and cohort studies (n = 2). Most of the studies reported positive feedback of the use of digital wellness interventions in workplace settings.
CONCLUSIONS: This review is the first to map and describe the impact of digital wellness interventions in the workplace in LMICs. Only a small number of studies met the inclusion criteria. Modest evidence was found that digital workplace wellness interventions were feasible, cost-effective, and acceptable. However, long-term, and consistent effects were not found, and further studies are needed to provide more evidence. This scoping review identified multiple digital health interventions in LMIC workplace settings and highlighted a few important research gaps.
OBJECTIVE: The aim of this study is to compare the accuracy, acceptability, and cost-effectiveness of 3 technology-assisted 24-hour dietary recall (24HR) methods relative to observed intake across 3 meals.
METHODS: Using a controlled feeding study design, 24HR data collected using 3 methods will be obtained for comparison with observed intake. A total of 150 healthy adults, aged 18 to 70 years, will be recruited and will complete web-based demographic and psychosocial questionnaires and cognitive tests. Participants will attend a university study center on 3 separate days to consume breakfast, lunch, and dinner, with unobtrusive documentation of the foods and beverages consumed and their amounts. Following each feeding day, participants will complete a 24HR process using 1 of 3 methods: the Automated Self-Administered Dietary Assessment Tool, Intake24, or the Image-Assisted mobile Food Record 24-Hour Recall. The sequence of the 3 methods will be randomized, with each participant exposed to each method approximately 1 week apart. Acceptability and the preferred 24HR method will be assessed using a questionnaire. Estimates of energy, nutrient, and food group intake and portion sizes from each 24HR method will be compared with the observed intake for each day. Linear mixed models will be used, with 24HR method and method order as fixed effects, to assess differences in the 24HR methods. Reporting bias will be assessed by examining the ratios of reported 24HR intake to observed intake. Food and beverage omission and intrusion rates will be calculated, and differences by 24HR method will be assessed using chi-square tests. Psychosocial, demographic, and cognitive factors associated with energy misestimation will be evaluated using chi-square tests and multivariable logistic regression. The financial costs, time costs, and cost-effectiveness of each 24HR method will be assessed and compared using repeated measures analysis of variance tests.
RESULTS: Participant recruitment commenced in March 2021 and is planned to be completed by the end of 2021.
CONCLUSIONS: This protocol outlines the methodology of a study that will evaluate the accuracy, acceptability, and cost-effectiveness of 3 technology-enabled dietary assessment methods. This will inform the selection of dietary assessment methods in future studies on nutrition surveillance and epidemiology.
TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12621000209897; https://tinyurl.com/2p9fpf2s.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32891.
OBJECTIVE: To compare the accuracy of energy and nutrient intake estimation of four technology-assisted dietary assessment methods relative to true intake across breakfast, lunch, and dinner.
METHODS: In a controlled feeding study with a crossover design, 152 participants (55% women; mean age 32y (SD 11); mean BMI 26 kg/m2 (SD 5)) were randomized to one of three separate feeding days to consume breakfast, lunch, and dinner, with unobtrusive weighing of foods and beverages consumed. Participants undertook a 24HR the following day (Automated Self-Administered Dietary Assessment Tool-Australia© (ASA24); Intake24-Australia©; mobile Food Record™ - Trained Analyst (mFR-TA); or Image-Assisted Interviewer-Administered 24-hour recall (IA-24HR)). When assigned to IA-24HR, participants referred to images captured of their meals using the mobile Food Record™ app. True and estimated energy and nutrient intakes were compared, and differences among methods were assessed using linear mixed models.
RESULTS: The mean difference between true and estimated energy intake as a percentage of true intake was 5.4% (95% CI 0.6, 10.2) using ASA24, 1.7% (95% CI -2.9, 6.3) using Intake24, 1.3% (95% CI -1.1, 3.8) using mFR-TA, and 15.0% (95% CI 11.6, 18.3) using IA-24HR. The variances of estimated and true energy intakes were statistically significantly different for all methods (P<0.01), apart from Intake 24 (P=0.1). Differential accuracy in nutrient estimation was present among the methods.
CONCLUSIONS: Under controlled conditions, Intake24, ASA24, and mFR-TA estimated average energy and nutrient intakes with reasonable validity, but intake distributions were estimated accurately by Intake24 only (energy and protein). This study may inform considerations regarding instruments of choice in future population surveillance.
TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry Number ACTRN12621000209897; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381165&isReview=true.