Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions

Turner‐McGrievy, Gabrielle; Dunn, Caroline; Wilcox, Sara; Boutté, Alycia K.; Hutto, Brent; Hoover, Adam; Muth, Eric R.

doi:10.1016/j.jand.2019.03.012

Cited by 67 publications

(50 citation statements)

References 54 publications

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“…We identified 4,248 records in our database and hand searches. After the deduplication and screening stages, 53 papers describing 39 unique RCTs met all inclusion criteria (32‐84).…”

Section: Resultsmentioning

confidence: 99%

Self‐Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

Patel

Wakayama

Bennett

2021

Obesity

113

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Objective: Self-monitoring is a core component of behavioral obesity treatment, but it is unknown how digital health has been used for selfmonitoring, what engagement rates are achieved in these interventions, and how self-monitoring and weight loss are related. Methods: This systematic review examined digital self-monitoring in behavioral weight loss interventions among adults with overweight or obesity. Six databases (PubMed, Embase, Scopus, PsycInfo, CINAHL, and ProQuest Dissertations & Theses) were searched for randomized controlled trials with interventions ≥ 12 weeks, weight outcomes ≥ 6 months, and outcomes on self-monitoring engagement and their relationship to weight loss. Results: Thirty-nine studies from 2009 to 2019 met inclusion criteria. Among the 67 interventions with digital self-monitoring, weight was tracked in 72% of them, diet in 81%, and physical activity in 82%. Websites were the most common self-monitoring modality, followed by mobile applications, wearables, electronic scales, and, finally, text messaging. Few interventions had digital self-monitoring engagement rates ≥ 75% of days. Rates were higher in digital-than in paper-based arms in 21 out of 34 comparisons and lower in just 2. Interventions with counseling had similar rates to standalone interventions. Greater digital self-monitoring was linked to weight loss in 74% of occurrences. Conclusions: Self-monitoring via digital health is consistently associated with weight loss in behavioral obesity treatment.

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“…We identified 4,248 records in our database and hand searches. After the deduplication and screening stages, 53 papers describing 39 unique RCTs met all inclusion criteria (32‐84).…”

Section: Resultsmentioning

confidence: 99%

Self‐Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

Patel

Wakayama

Bennett

2021

Obesity

113

View full text Add to dashboard Cite

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“…Relevant to this study, mobile photo meal apps engage the user to take a picture of their food item(s) using their mobile device before it is consumed and require the user to input the quantity and other pertinent details, as needed. Although mobile phone–based methods still rely on user input, an advantage of this method is that food entries are time-stamped, which identifies when food items were consumed [ 9 ]. The use of dietary assessment applications, such as those that use a mobile phone app, has shown an increase in participant satisfaction and preference compared with conventional methods (eg, 24-h recall, written food diary) [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Validity and Usability of a Smartphone Image-Based Dietary Assessment App Compared to 3-Day Food Diaries in Assessing Dietary Intake Among Canadian Adults: Randomized Controlled Trial

Ji¹,

Plourde²,

Bouzo³

et al. 2020

JMIR Mhealth Uhealth

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Background Accurate dietary assessment is needed in studies that include analysis of nutritional intake. Image-based dietary assessment apps have gained in popularity for assessing diet, which may ease researcher and participant burden compared to traditional pen-to-paper methods. However, few studies report the validity of these apps for use in research. Keenoa is a smartphone image-based dietary assessment app that recognizes and identifies food items using artificial intelligence and permits real-time editing of food journals. Objective This study aimed to assess the relative validity of an image-based dietary assessment app — Keenoa — against a 3-day food diary (3DFD) and to test its usability in a sample of healthy Canadian adults. Methods We recruited 102 participants to complete two 3-day food records. For 2 weeks, on 2 non-consecutive days and 1 weekend day, in random order, participants completed a traditional pen-to-paper 3DFD and the Keenoa app. At the end of the study, participants completed the System Usability Scale. The nutrient analyses of the 3DFD and Keenoa data before (Keenoa-participant) and after they were reviewed by dietitians (Keenoa-dietitian) were analyzed using analysis of variance. Multiple tests, including the Pearson coefficient, cross-classification, kappa score, % difference, paired t test, and Bland-Altman test, were performed to analyze the validity of Keenoa (Keenoa-dietitian). Results The study was completed by 72 subjects. Most variables were significantly different between Keenoa-participant and Keenoa-dietitian (P<.05) except for energy, protein, carbohydrates, fiber, vitamin B1, vitamin B12, vitamin C, vitamin D, and potassium. Significant differences in total energy, protein, carbohydrates, % fat, saturated fatty acids, iron, and potassium were found between the 3DFD and Keenoa-dietitian data (P<.05). The Pearson correlation coefficients between the Keenoa-dietitian and 3DFD ranged from .04 to .51. Differences between the mean intakes assessed by the 3DFD and Keenoa-dietitian were within 10% except for vitamin D (misclassification rate=33.8%). The majority of nutrients were within an acceptable range of agreement in the Bland-Altman analysis; no agreements were seen for total energy, protein, carbohydrates, fat (%), saturated fatty acids, iron, potassium, and sodium (P<.05). According to the System Usability Scale, 34.2% of the participants preferred using Keenoa, while 9.6% preferred the 3DFD. Conclusions The Keenoa app provides acceptable relative validity for some nutrients compared to the 3DFD. However, the average intake of some nutrients, including energy, protein, carbohydrates, % fat, saturated fatty acids, and iron, differed from the average obtained using the 3DFD. These findings highlight the importance of verifying data entries of participants before proceeding with nutrient analysis. Overall, Keenoa showed better validity at the group level than the individual level, suggesting it can be used when focusing on the dietary intake of the general population. Further research is recommended with larger sample sizes and objective dietary assessment approaches.

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“…In a previous study on a weight loss intervention, the more participants recorded food intakes on a mobile app, the more likely they were to lose weight [ 9 ]. However, patients may not always be interested and willing to track intakes [ 10 ], and commitment to self-monitoring decreases over time, even with the use of mobile technology [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

A Dietary Mobile App for Patients Undergoing Hemodialysis: Prospective Pilot Study to Improve Dietary Intakes

Khoury¹,

Crutzen²,

Schols³

et al. 2020

J Med Internet Res

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Background Mobile technology has an impact on the health care sector, also within dietetics. Mobile health (mHealth) apps may be used for dietary assessment and self-monitoring, allowing for real-time reporting of food intakes. Changing eating behaviors is quite challenging, and patients undergoing hemodialysis, particularly, struggle to meet the target intakes set by dietary guidelines. Usage of mobile apps that are developed in a person-centered approach and in line with recommendations may support both patients and health care practitioners. Objective This study is a pilot that aims at estimating the potential efficacy of a dietary intervention using a theory-based, person-centered smartphone app. Results will be used to improve both the app and a planned large-scale trial intended to assess app efficacy thoroughly. Methods A prospective pilot study was performed at the hemodialysis unit of Al Qassimi Hospital (The Emirate of Sharjah). All patients that fulfilled the study inclusion criteria were considered eligible to be enrolled in the pilot study. Upon successful installation of the app, users met with a dietitian once a week. Outcomes were measured at baseline (T0) and 2 weeks post app usage (T1). This pilot is reported as per guidelines for nonrandomized pilot and feasibility studies and in line with the CONSORT 2010 checklist for reporting pilot or feasibility trials. Results A total of 23 patients completed the pilot intervention. Mean energy intakes increased from 24.4 kcal/kg/day (SD 8.0) to 29.1 kcal/kg/day (SD 7.8) with a medium effect size (d=0.6, 95% CI 0.0-1.2). Mean protein intakes increased from 0.9 g/kg/day (SD 0.3) to 1.3 g/kg/day (SD 0.5) with a large effect size (d=1.0, 95% CI 0.4-1.6); mean intake of high biological value (%HBV) proteins also increased from 58.6% (SD 10.1) to 70.1% (SD 10.7) with a large effect size (d=1.1, 95% CI 0.5-1.7). Dietary intakes of minerals did not change, apart from sodium which decreased from a mean intake of 2218.8 mg/day (SD 631.6) to 1895.3 mg/day (SD 581.0) with a medium effect size (d=0.5, 95% CI 0.1-1.1). Mean serum phosphorus, potassium, and albumin levels did not change relevantly. Mean serum iron increased from 7.9 mg/dL (SD 2.8) to 11.5 mg/dL (SD 7.9) postintervention with a medium effect size (d=0.6, 95% CI 0.0-1.2). Conclusions This pilot study showed that the KELA.AE app has the potential to improve dietary intakes. Processes related to procedure, resources, tools, and app improvement for a future trial were assessed. A more extended intervention using a randomized controlled trial is required to estimate parameters concerning app efficacy accurately.

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Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions

Cited by 67 publications

References 54 publications

Self‐Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

Self‐Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

Validity and Usability of a Smartphone Image-Based Dietary Assessment App Compared to 3-Day Food Diaries in Assessing Dietary Intake Among Canadian Adults: Randomized Controlled Trial

A Dietary Mobile App for Patients Undergoing Hemodialysis: Prospective Pilot Study to Improve Dietary Intakes

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