Self-Monitoring via Digital Tracking and Obesity
Clinical Question: Obesity is major health concern among many people in the United States which contributes to the development of many chronic diseases. For many, it is difficult to participate in weight reduction activities because of how tedious it is to keep track of everything they eat and how much they exercise. With new technology such as, smartphone apps and smartwatches, individuals can track everything they consume, their exercise, and they can even set weight goals without having to do any calculations. My question is whether self-monitoring using digital tracking is a feasible option for obese patients to promote weight loss.
PICO Question: In obese adults, is self-monitoring via digital tracking an effective behavioral weight management intervention for promoting weight loss?
PICO search terms:
| P | I | C | O |
| Obese adults | Digital tracking | Paper recording | Weight loss |
| Obesity | Smartphone apps | Paper journals | Weight reduction |
| Overweight | Personal digital assistants | ||
| Self-monitoring |
Search tools and strategy used:
Please indicate what databases/tools you used, provide a list of the terms you searched together in each tool, and how many articles were returned using those terms and filters. Explain how you narrow your choices to the few selected articles.
PubMed
- Mobile health AND weight loss —> 1, 041
- Full text & last 10 years —> 962
- Systematic review, meta-analysis, RCTs —> 337
- Full text & last 10 years —> 962
Science Direct
- Digital tracking AND obesity —> 22
- Full text —> 19
- Last 10 years —> 18
- Full text —> 19
Wiley Online Library
- Self-monitoring AND weight loss —> 10, 432
- Last 9 years —> 7, 7762
- Article & English —> 3, 848
- Medicine and public health, medicine/public health, general, public health, health promotion and disease prevention —> 1,136
- Article & English —> 3, 848
- Last 9 years —> 7, 7762
I narrowed down these results by looking at the titles first to see which ones were actually related to my topic. I also focused on articles based in the US or those that included at least one or more US studies is they were a systematic review or meta-analysis. I also looked at articles that were listed on the first page of each search because any articles listed after that were unrelated to my PICO question.
Articles Chosen:
Article 1
| Citation:Patel, M. L., Wakayama, L. N., & Bennett, G. G. (2021). Self‐monitoring via digital health in weight loss interventions: A systematic review among adults with overweight or obesity. Obesity, 29(3), 478–499. https://doi.org/10.1002/oby.23088 Link: https://pubmed.ncbi.nlm.nih.gov/33624440/ |
| Abstract:Objective: Self- monitoring is a core component of behavioral obesity treatment, but it is unknown how digital health has been used for self- monitoring, 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. |
Article 2
| Citation:Cavero-Redondo, I., Martinez-Vizcaino, V., Fernandez-Rodriguez, R., Saz-Lara, A., Pascual-Morena, C., & Álvarez-Bueno, C. (2020). Effect of Behavioral Weight Management Interventions Using Lifestyle mHealth Self-Monitoring on Weight Loss: A Systematic Review and Meta-Analysis. Nutrients, 12(7), 1977. https://doi.org/10.3390/nu12071977 Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400167/pdf/nutrients-12-01977.pdf |
| Abstract:Abstract: Alongside an increase in obesity, society is experiencing the development of substantial technological advances. Interventions that are easily scalable, such as lifestyle (including diet and physical activity) mobile health (mHealth) self-monitoring, may be highly valuable in the prevention and treatment of excess weight. Thus, the aims of this systematic review and meta-analysis were to estimate the following: (i) the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss and (ii) the adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring. MEDLINE via PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science databases were systematically searched. The DerSimonian and Laird method was used to estimate the effect of and adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss. Twenty studies were included in the systematic review and meta-analysis, yielding a moderate decrease in weight and higher adherence to intervention of behavioral weight management interventions using lifestyle mHealth self-monitoring, which was greater than other interventions. Subgroup analyses showed that smartphones were the most effective mHealth approach to achieve weight management and the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring was more pronounced when compared to usual care and in the short-term (less than six months). Furthermore, behavioral weight management interventions using lifestyle mHealth self-monitoring showed a higher adherence than: (i) recording on paper at any time and (ii) any other intervention at six and twelve months. |
Article 3
| Citation:Patel, M. L., Hopkins, C. M., Brooks, T. L., & Bennett, G. G. (2019). Comparing Self-Monitoring Strategies for Weight Loss in a Smartphone App: Randomized Controlled Trial. JMIR mHealth and uHealth, 7(2), e12209. https://doi.org/10.2196/12209 Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416539/ |
| Abstract:Background: Self-monitoring of dietary intake is a valuable component of behavioral weight loss treatment; however, it declines quickly, thereby resulting in suboptimal treatment outcomes. Objective: This study aimed to examine a novel behavioral weight loss intervention that aims to attenuate the decline in dietary self-monitoring engagement. Methods: GoalTracker was an automated randomized controlled trial. Participants were adults with overweight or obesity (n=105; aged 21-65 years; body mass index, BMI, 25-45 kg/m2) and were randomized to a 12-week stand-alone weight loss intervention using the MyFitnessPal smartphone app for daily self-monitoring of either (1) both weight and diet, with weekly lessons, action plans, and feedback (Simultaneous); (2) weight through week 4, then added diet, with the same behavioral components (Sequential); or (3) only diet (App-Only). All groups received a goal to lose 5% of initial weight by 12 weeks, a tailored calorie goal, and automated in-app reminders. Participants were recruited via online and offline methods. Weight was collected in-person at baseline, 1 month, and 3 months using calibrated scales and via self-report at 6 months. We retrieved objective self-monitoring engagement data from MyFitnessPal using an application programming interface. Engagement was defined as the number of days per week in which tracking occurred, with diet entries counted if ≥800 kcal per day. Other assessment data were collected in-person via online self-report questionnaires. Results: At baseline, participants (84/100 female) had a mean age (SD) of 42.7 (11.7) years and a BMI of 31.9 (SD 4.5) kg/m2. One-third (33/100) were from racial or ethnic minority groups. During the trial, 5 participants became ineligible. Of the remaining 100 participants, 84% (84/100) and 76% (76/100) completed the 1-month and 3-month visits, respectively. In intent-to-treat analyses, there was no difference in weight change at 3 months between the Sequential arm (mean −2.7 kg, 95% CI −3.9 to −1.5) and either the App-Only arm (−2.4 kg, −3.7 to −1.2; P=.78) or the Simultaneous arm (−2.8 kg, −4.0 to −1.5; P=.72). The median number of days of self-monitoring diet per week was 1.9 (interquartile range [IQR] 0.3-5.5) in Sequential (once began), 5.3 (IQR 1.8-6.7) in Simultaneous, and 2.9 (IQR 1.2-5.2) in App-Only. Weight was tracked 4.8 (IQR 1.9-6.3) days per week in Sequential and 5.1 (IQR 1.8-6.3) days per week in Simultaneous. Engagement in neither diet nor weight tracking differed between arms. Conclusions: Regardless of the order in which diet is tracked, using tailored goals and a commercial mobile app can produce clinically significant weight loss. Stand-alone digital health treatments may be a viable option for those looking for a lower intensity approach. |
Article 4
| Citation:Chew, H. S. J., Koh, W. L., Ng, J. S. H. Y., & Tan, K. K. (2022). Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes. Journal of medical Internet research, 24(9), e40141. https://doi.org/10.2196/40141 Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536524/?report=printable |
| Abstract:BackgroundEvidence on the long-term effects of weight management smartphone apps on various weight-related outcomes remains scarce. Objective In this review, we aimed to examine the effects of smartphone apps on anthropometric, metabolic, and dietary outcomes at various time points. MethodsArticles published from database inception to March 10, 2022 were searched, from 7 databases (Embase, CINAHL, PubMed, PsycINFO, Cochrane Library, Scopus, and Web of Science) using forward and backward citation tracking. All randomized controlled trials that reported weight change as an outcome in adults with overweight and obesity were included. We performed separate meta-analyses using random effects models for weight, waist circumference, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, blood glucose level, blood pressure, and total energy intake per day. Methodological quality was assessed using the Cochrane Risk of Bias tool. Results Based on our meta-analyses, weight loss was sustained between 3 and 12 months, with a peak of 2.18 kg at 3 months that tapered down to 1.63 kg at 12 months. We did not find significant benefits of weight loss on the secondary outcomes examined, except for a slight improvement in systolic blood pressure at 3 months. Most of the included studies covered app-based interventions that comprised of components beyond food logging, such as real-time diet and exercise self-monitoring, personalized and remote progress tracking, timely feedback provision, smart devices that synchronized activity and weight data to smartphones, and libraries of diet and physical activity ideas. Conclusions Smartphone weight loss apps are effective in initiating and sustaining weight loss between 3 and 12 months, but their effects are minimal in their current states. Future studies could consider the various aspects of the socioecological model. Conversational and dialectic components that simulate health coaches could be useful to enhance user engagement and outcome effectiveness. |
Article 5
| Citation:Turner-McGrievy, G. M., Beets, M. W., Moore, J. B., Kaczynski, A. T., Barr-Anderson, D. J., & Tate, D. F. (2013). Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program. Journal of the American Medical Informatics Association : JAMIA, 20(3), 513–518. https://doi.org/10.1136/amiajnl-2012-001510 Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628067/ |
| Abstract:ABSTRACT Objective Self-monitoring of physical activity (PA)and diet are key components of behavioral weight loss programs. The purpose of this study was to assess the relationship between diet (mobile app, website, or paper journal) and PA (mobile app vs no mobile app) self-monitoring and dietary and PA behaviors.Materials and methods This study is a post hoc analysis of a 6-month randomized weight loss trial among 96 overweight men and women (body mass index (BMI) 25–45 kg/m2) conducted from 2010 to 2011. Participants in both randomized groups were collapsed and categorized by their chosen self- monitoring method for diet and PA. All participants received a behavioral weight loss intervention delivered via podcast and were encouraged to self-monitor dietary intake and PA. ResultsAdjusting for randomized group and demographics, PA app users self-monitored exercise more frequently over the 6-month study (2.6±0.5 days/week) and reported greater intentional PA (196.4±45.9 kcal/day) than non-app users (1.2±0.5 days/week PA self-monitoring, p<0.01; 100.9±45.1 kcal/day intentional PA, p=0.02). PA app users also had a significantly lower BMI at 6 months (31.5±0.5 kg/m2) than non-users (32.5±0.5 kg/m2; p=0.02). Frequency of self-monitoring did not differ by diet self-monitoring method (p=0.63); however, app users consumed less energy (1437±188 kcal/day) than paper journal users (2049±175 kcal/day; p=0.01) at 6 months. BMI did not differ among the three diet monitoring methods ( p=0.20). ConclusionsThese findings point to potential benefits of mobile monitoring methods during behavioral weight loss trials. Future studies should examine ways to predict which self-monitoring method works best for an individual to increase adherence. |
Article 6
| Citation: Dunn, C.G., Turner-McGrievy, G. M., Wilcox, S., & Hutto, B. (2019). Dietary Self-Monitoring Through Calorie Tracking but Not Through a Digital Photography App Is Associated with Significant Weight Loss: The 2SMART Pilot Study—A 6-Month Randomized Trial. Journal of the Academy of Nutrition and Dietetics, 119(9), 1525–1532. https://doi.org/10.1016/j.jand.2019.03.013 Link: https://www-sciencedirect-com.york.ezproxy.cuny.edu/science/article/pii/S2212267219302667 |
| Abstract:Background Dietary self-monitoring (DSM) of foods and beverages is associated with weight loss in behavioral interventions; however, DSM may be burdensome, and adherence may decrease over time. Novel methods of DSM, including apps that track food using photographs, may decrease burden, increase DSM adherence, and improve weight loss. Objective The objective was to test a mobile photo DSM app compared to a calorie- tracking DSM app on tracking frequency and weight loss in a remotely delivered behavioral weight-loss intervention. Design This was a 6-month (October 2016 to April 2017) randomized trial. Participants/setting Participants were adults (n1⁄441) classified as overweight or obese (body mass index 25 to 49.9) from South Carolina. Intervention Participants received remotely delivered twice-weekly behavioral weight-loss podcasts and tracked diet using a calorie-tracking DSM app (Calorie Group) or a photo DSM app (Photo Group). Main outcome measures Main outcomes were the number of days diet was tracked, podcasts downloaded, and weight change at 6 weeks and 6 months. Statistical analyses Researchers used nonparametric Wilcoxon rank sum tests and c2 analysis to test for differences between groups at baseline; repeated-measures models to estimate weight change and Spearman correlations to determine relationships between DSM frequency, podcasts downloaded, and weight change at 6 months. Results There were no differences between groups for the number of days that diet was recorded (P1⁄40.18), which was low overall (<30% of days) but was statistically significantly and strongly correlated with weight change for all participants pooled (r1⁄40.63; P<0.001) and for the calorie tracking group (r1⁄40.70; P1⁄40.004), but not the photo tracking group (r1⁄40.51; P1⁄40.06). Participants in both groups had significant weight loss at 6 months (Photo Group, e2.50.9 kg; P1⁄40.008; Calorie Group e2.40.9 kg; P1⁄40.007), with no differences between groups at either 6 weeks (P1⁄40.66) or at 6 months (P1⁄40.74). Conclusions As part of a remotely delivered weight loss intervention, frequency of DSM was significantly associated with overall weight loss for participants using a calorie DSM app but not a photo DSM app. DSM was low regardless of group and weight loss was significant, although minimal. Increasing user engagement with any DSM may be important to increase self-monitoring and improve weight loss. |
Summary of Evidence:
| Author (Date) | Level of Evidence | Sample/Setting (# of subjects/studies, cohort definitions etc.) | Outcome(s) Studied | Key Findings | Limitations and Biases |
| Patel et al., (2021) | Systematic Review | -39 studies- date of studies: 2009-2019-# of participants: 8,232- participants: 18 or older with overweight or obesity at baseline-overweight/obesity: >/= BMI of 25-weight loss interventions lasted minimum of 12 weeks and involved at least one weight-related behavior or outcome being self-monitored via digital health-31/39 studies conducted in US-self-monitored activity included body weight, dietary intake, physical activity and behavior change goals | Primary: To determine whether digital self-monitoring is positively related to weight loss Secondary: To examine how digital health has been used for self-monitoring; to evaluate self-monitoring engagement rates in these interventions | -self-monitoring via digital health was better than engagement via paper 56% of occasions, worse on 12% of occasions, and no different on 32% of occasions-Engagement rates were higher when tracking intervals were shorter than 12 months-Most interventions had higher engagement rates for the behavior that passively monitored-Self-monitoring was higher via digital health than paper in 5 out of 8 occasions when tracking body weight, 10 out of 13 when tracking diet, 3 out of 8 when tracking physical activity, and 1 out of 3 when multiple tracked behaviors were recorded-Combining counseling with self-monitoring did not improve engagement rates when compared to stand-alone interventions.-Self-monitoring was associated with greater weight loss in 74% if occasions.-Frequency of self-monitoring weight and weight loss had a positive association and this pattern was consistently repeated across self-monitored behaviors, digital health modalities, and counseling types.-80% found that greater self-monitoring of dietary behavior was associated with greater weight loss-73% instances found greater self-monitoring of physical activity was linked to greater weight loss-websites were the most common modality at 66% for digital self-monitoring followed by apps at 33% | -Technology is always changing, and rapidly, so some of the devices studied/included in the studies became discontinued or weren’t used as much, reducing the generalizability of the research-participants were also allowed to choose the method of self-monitoring which prevented the ability to directly examine the impact of each specific modality on self-monitoring engagement rates- individuals were not randomized to differing levels of self-monitoring so some may engage more than others which can overestimate the magnitude of the effects- not all results reported were tested for statistical significance in the study itself-review was limited to adults |
| Cavero-Redondo et al., (2020) | Systematic Review & Meta-Analysis | -20 studies were included- studies were from 6 countries: 12 in US, 2 in UK, 3 in Australia, 1 in New Zealand, 1 in South Korea, 1 in Finland-17 RCTs and 3 non-RCTs-study dates: 2007-2019-sample sizes ranged from 11-131-participants in each study ranged from 6-133-baseline weight: 62.1 – 116.9kg-baseline BMI: 27 – 40.1 kg/m2Baseline waist circumference: 88.2 – 120.4 cm-lifestyle mHealth: lifestyle mobile health-lifestyle mhealth included personal digital assistants, smartphones, websites | Primary: To estimate the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight lossSecondary: To estimate adherence to behavioral weight management interventions when lifestyle mHealth self-monitoring was used | -The use of mHealth can have a mean weight loss of 1.78kg greater than with other intervention types-There were fewer dropouts of participants included in mHealth interventions in the short and long-term.-The effect of behavioral weight management interventions using lifestyle mHealth self-monitoring interventions was more pronounced when they were compared to usual care and in the short-term (less than six months)-greater effect for weight management was seen when the mHealth intervention used was a smartphone with-higher adherence rate with mhealth than paper records or any other intervention at 6 and 12 months-mHealth monitoring can be effective for both the patient and in the clinical setting by empowering the patient and also decreasing the workload for healthcare workers. | -moderate risk for bias as there was no blinding interventions which can be difficult to do with this type of intervention-lack of studies using devices that did not allow for comparison between them-intervention groups could be very distinct considered they used different modalities-most studies did not control for effect of other factors such as educational or socioeconomic level-multiple reasons other than lifestyle mhealth for participants to dropout-small sample size |
| Patel et al., (2019) | Randomized Control Trial | -# of participants: 100-mean BMI: 31.9-Goal tracker was a 3-arm randomized control trial comparing 3 stand alone weight loss interventions: simultaneous self-monitoring, (sequential arm) mastery of 1 skill (ie, self-monitoring of body weight) before beginning self-monitoring of diet, (app only arm) that tracked only diet with no additional behavior change components-evaluation visits were conducted at baseline, 1 month, and 3 months. Self-reported weight at 6 months | Primary: Weight change at 3 months | -Weight change was significant over time for all arms-The proportion of participants achieving at least 3% weight loss at 3 months was similar between arms (sequential:44% vs app only:29% vs simultaneous: 41%)-The sequential arm tracked weight significantly more days than the App-Only arm (who was not asked to track weight) over the 12-week intervention-The percentage of days weight was tracked was significantly associated with 3-month weight change in both the Simultaneous arm and the Sequential arm- the sequential arm did not differ from the app only or simultaneous arm at 1, 3 or 6 months -Self-monitoring engagement was high and greater frequency of self-monitoring was related to greater weight loss. | -study was powered on superiority and not equivalency preventing the assertion that the treatment arms produce comparable weight loss-some financial compensation was given which could affect participation-neither participant or staff was blinded to treatment arm-study did not include pure control arm without an intervention which could have led to underestimation of treatment effects |
| Chew et al., (2022) | Systematic Review and Meta-Analysis | -16 articles- most studies conducted in US-69% of articles reported on dated reflecting the sample’s socioeconomic status, 81% reported on data on sample’s educational level-# of participants: 2,870-mean weight: 70.6 – 114.1 kg-mean BMI: 27.5 – 36.6 kg/m2-interventions ranged from 12 weeks to 24 months and follow up time points ranged from 8 weeks to 24 months | Primary: To examine effects of smartphone apps on anthropometric, metabolic, and dietary outcomes and various time points | -The use of a smartphone app together with a smart activity band resulted in greater weight loss 12 months into the program, where both the intervention and control groups were found to have decreased their calorie intake comparably.-Weight loss as large as 10 kg may be required for significant improvements in cholesterol and BP to be detected.-Weight loss was sustained between 3 and 12 months, with a peak of −2.18 kg at 3 months that tapered down with time to −1.63 at 12 months-All 16 articles reported results on weight change. A total of 38% (6/16) of articles reported results of weight change at 3 months, of which 4 (67%) reported significant weight loss and 2 (33%) reported otherwise.-Of the 16 articles, 11 (69%) reported results of weight change at 3 months, of which 8 (50%) reported significant weight loss and 3 (19%) reported otherwise-A total of 75% (12/16) of articles reported results of weight change at 6 months, of which 7 (44%) reported significant weight loss, and 5 (31%) reported otherwise- 25% (4/16) of articles reported results of weight change at 12 months, of which 2 (50%) reported significant weight loss, and 2 (50%) reported otherwise.- Interventional effect was assessed at 9 months, 18 months, and 24 months; only 6% (1/16) of articles reported significant weight loss at both 18 and 24 months- 5 articles reported on waist circumference and of these, 2 articles (40%) reported a significant reduction in waist circumference at 3 months, whereas 1 article (20%) reported otherwise-Significant reductions in waist circumference were reported at 3 months and 6 months, whereas different results were reported at 12 to 24 months- Findings didn’t suggest significant reduction in total calorie intake per day-use of a smartphone together with a smart activity band results in greater weight loss at 12 months into the program- there was a significant interventional effect on systolic blood pressure at 3 months but not at 6 or with diastolic pressure- no significant change in HDL-C and LDL-C at any point in time. | -Small sample size could have caused analyses to be underpowered in detecting true effects, if any where present, so inferences based on these results of secondary outcomes should be made with caution.- most studies included had an unclear or high rate of bias-heterogeneity between studies was high which suggest a certain level of inaccuracy |
| Turner-McGrievy et al., (2013) | Randomized Control Trial | -# of participants: 96-6 month weight loss trial-dates: 2010-2011-conducted in North Carolina-BMI: 25-45-18-60 years old-weight loss intervention delivered by audio podcast only (Podcast group, n=49) or an intervention delivered by the same podcast plus mobile diet monitoring using a diet and PA monitoring app as well as moderator and social support (from fellow study participants) delivered via the social networking site Twitter (Podcast+Mobile group, n=47). | Primary: To assess if the method of physical activity (app vs no app) and diet (app, website, or paper journal) monitory is related to changes in self-monitoring frequency, dietary outcomes, energy expenditures, BMI, and body weight | -PA app users lost more weight (−3.7±1.5%) than non-app users (−0.5±1.5%) at 6 months.-Change in PA was significantly related to percent weight loss at 6 months-Percent energy from fat, added sugar, vegetables, EBI, and BMI were significant but diet self-monitoring method was not significantly associated with any of these outcomes-Average days/week that diet was self- monitored over the 6-month study significantly predicted percent weight loss at 6 months-In this study, it is unknown whether use of a mobile app helped to increase adherence to PA recommendations or if those who were meeting PA recommendations were more likely to use a mobile app-Also, those who may have been reporting self-monitoring may not have been meeting caloric goals, whereas, there may have been those who were reporting self-monitoring for PA who did indeed partake in physical activity.-The mean days/week participants reported self-monitoring PA and diet was low, no matter what method was used, pointing to the fact that mobile methods of self-monitoring may not be a solution for increasing adherence | -participants in the 3 diet monitoring groups and 2 exercising track groups were not randomized-participants could have reported other methods over primary self-monitoring method-study did not account for other methods of tracking physical activity other than app vs no app- all outcomes except weight change were self-reported-majority of participants were white, educated females which reduced the generalizability of the research |
| Dunn et al., (2019) | Randomized Control Trial | -# of participants- 2 groups: Photo group and Calorie Group- 22 participants were in the photo group-19 participants in calorie group-patients were overweight or obese- overweight or obese classified as BMI of 25-49.9-6 month trial took place from Oct 2016 to April 2017 in South Carolina- photo group used Meal Logger app which is a journal app that allows participants to track and rate foods, view other users’ foods, and leave comments and reviews- calorie group used FatSecret app which is a free food diary app that allows users to enter amounts and types of foods and beverages consumed | Primary: To test a mobile photography-based dietary self-monitoring (DSM) app compared with a calorie tracking DSM app on tracking frequency and weight loss in a remotely delivered behavioral weight-loss intervention | -no differences between groups in the number of days that diet was recorded out of 168 possible days or the number of podcasts downloaded out of 48 episodes-number of days that diet were tracked with their app was significantly and strongly correlated with weight change for all participants pooled and calorie group but not for photo group which may be attributed to sample size-weight change was not significantly correlated with number of podcasts downloaded- photo group participants lost significant amount of weight at both 6 weeks and 6 monthsCalorie group did not lose significant amount of weight at 6 weeks, but did at 6 months-no differences in weight loss between groups at either 6 weeks or 6 months | -small sample size-sample consisted of mainly white women with college educations or advanced degrees which reduces generalizability of results-attrition rate was high at 30% which could be due to follow up meeting times during weeks before busy holiday season and a hurricane during scheduled study assessments-participants may have had different recommendations or levels of social support from assigned app-method of DSM may have influenced dietary intake-lack of true control or delayed intervention control |
Weight of evidence:
I weighed the evidence based on the year published, number of articles included and organization of the data as it applied to my patient scenario. I also considered where most of the studies included in article took place in the US and the sample sizes. I weighted them in the following order: Patel et al. (2021), Chew et al. (2022), Cavero-Redondo et al. (2020), Patel et al. (2019), Dunn et al. (2019), and Turner-McGrievy et al. (2012). I weighted Patel et al. (2021), Chew et al. (2022), and Cavero-Redondo et al. (2020) the heaviest because they were either systematic reviews or systematic reviews and meta-analysis. While Patel et al. (2021) is only a systematic review and published earlier than Chew et al. (2022), I weighted it the heaviest because it had a larger sample size. Patel et al. (2019), Dunn et al. (2019), and Turner-McGrievy et al. (2013) are all randomized control trials, but Patel et al. (2019) and Dunn et al. (2019) were published more recently; however, Dunn et al. (2019) had a smaller sample size compared to Patel et al. (2019).
Conclusions:
Article 1:
Patel et al. (2021) concluded that self-monitoring via digital tracking is associated with weight loss. It was noted that self-monitoring was associated with greater weight loss in 74% of occasions and this association was seen among different self-monitored behaviors, digital health modalities and counseling types. There was also a positive relationship between frequency of monitoring weight and weight loss in 72% of the cases. Dietary behavior was also associated with greater weight loss in 80% of occasions. In addition, 73% of cases found greater weight loss with greater self-monitoring of physical activity. However, there was no significant association between self-monitoring behavior change goals and weight loss. It was also noted that self-monitoring long-term was less effective for weight loss due to either less engagement or because rate of weight loss slowed down even though level of engagement remained the same. Engagement rates were also higher with digital self-monitoring than paper. Although the results showed a positive relationship between digital self-monitoring and weight loss, other methods or platforms of self-monitoring should be investigated, as well as self-monitoring strategies.
Article 2:
Cavero-Redondo et al. found that self-monitoring via digital tracking with lifestyle mHealth was an effective intervention for behavioral weight management for short-term weight loss in overweight or obese adults. There was a mean weight loss of 1.78 kg greater than with other intervention types. There was even greater weight loss when a smartphone was used (ES = 0.36; 95%CI: 0.51, 0.13, I2 = 56.4%). However, the effect on weight loss was not great when intervention was more than 6 months. At 12 months or more, the p value for length of intervention was .432 making it not statistically significant. While self-monitoring with lifestyle mHealth had a positive correlation with weight loss compared to paper records, more studies are needed with better statistical power to solidify the evidence provided.
Article 3:
Patel et al., (2019) concluded that greater weight loss was associated with using tailored goals and a mobile app and was significant over time for all arms. There was at least a 3% weight loss at 3 months which was similar between arms. However, there were no significant differences in weight change between arms. When comparing the Sequential arm and App-Only arm weight change was not significantly different at 1 month (P=.06), 3 months (P=.78), or 6 months (P=.72). In exploratory analyses, the Sequential arm did not differ from the Simultaneous arm in weight change at 1 month (P=.36), 3 months (P=.92), or 6 months (P=.45). The study also noted that more frequent monitoring was associated with greater weight loss at 3 months.
Article 4:
Chew et al. found that digital tracking with the use of smartphone apps to lose weight is an effective method to initiate and sustain weight loss between 3 and 12 months. There was a peak of −2.18 kg at 3 months that declined with time to −1.63 at 12 months. There were even greater effects seen for weight loss at 12 months when combining a smartphone weight loss app with a smart activity band. While digital tracking with a smartphone app is an effective method for weight loss, the amount of weight loss as evidenced by this study may not be enough to lower cardiometabolic disease risk; therefore, it may only be useful for those who are slightly overweight. The addition of health coaching as a source of motivation is an additional factor to consider for more significant clinical outcomes.
Article 5:
Turner-McGrievy et al. concluded that there is not enough data to support digital tracking as an effective behavior weight management intervention. The average number of days per week individuals reported self-monitoring was low across all modalities meaning there was low adherence. However, the use of digital tracking physical activity and diet was associated with increased energy expenditure and decreased energy intake. Physical activity app users lost more weight (−3.7±1.5%) than non-app users (−0.5±1.5%) at 6 months. More studies are needed to conclude whether mobile monitoring is superior to wed or paper journal methods regarding number of days being self-monitored and greater weight loss. There are also needs to be research on other digital tracking methods, as one method maybe more suitable for one individual than another.
Article 6:
Dunn et al. found that frequency of dietary self-monitoring was significantly associated with weight loss in all participants pooled (r=0.63; P < 0.001), those using a calorie dietary self-monitoring app (r= 0.70; P= 0.004) but not in those using a photo dietary self-monitoring app ( r= 0.51: P + 0.06); however, the results may be skewed by the small sample size of photo group. These findings suggest that adherence to self-monitoring is an important component of behavioral weight loss interventions. Photo group participants lost a significant amount of weight at 6 weeks (-2.2+/-0.8 kg; P <0.01) and at 6 months (-2.5 +/-0.9 kg; P <0.01). Calorie group participants did not lose at 6 weeks (-1.5+/-0.8 kg; P=0.08) but did at 6 months (-2.4+/-0.9 kg; P <0.01). The results show that dietary self-monitoring of calories for weight loss maybe more helpful long-term.
Overall conclusion:
Overall, most of the articles agree that self-monitoring via digital tracking may be useful as a behavior weight loss management intervention. The articles come to the same conclusion that frequency of self-monitoring and adherence is one of the factors that have biggest impact on weight loss. While self-monitoring via digital tracking may be useful for weight loss, it may not make significant clinical changes for those who are overweight or obese. There is a need for more RCTs looking at different modalities for tracking and the use of health coaches to increase adherence.
What is the clinical “bottom line” derived from these articles in answer to your question?
The clinical bottom line is that there are benefits and associations with self-monitoring via digital tracking regarding the promotion of weight loss in obese adults. While there are many different modalities or digital resources available to choose from, most studies conclude that self-monitoring via either method of digital tracking have better outcomes for weight loss compared to traditional paper recording. Paper recording can be tedious for most people, which discourage individuals from keeping up with daily tracking of calculations of energy intake and expenditures, calorie intake, and exercise; however, technology has made many new advances that take the mental work out of performing those calculations. It also makes it easier for people because the different modalities include access to caloric values for all the different foods someone may eat. Digital tracking has allowed for individuals to track their diet and exercise in real time, especially when considering devices or apps that allow for passive monitoring. Most studies have shown that interventions through smartphone are the most effective. Now although technological advances have made it more feasible for people to track their dietary and exercise habits, the probability of positive outcomes of greater weight loss does rely on participation of the patient. Studies showed more positive associations with those who more frequently self-monitored their weight, dietary habits, and exercise. The frequency of self-monitoring allows for individuals to reflect on their exercise and eating habits, leading them to make the appropriate changes over time and tracking that progress as they go. The resulting weight loss in obese patients also has benefits for other weight-related outcomes, such as blood pressure, HDL-C, LDL-C and HbA1c levels; however, it is important to note that you may need a significant amount of weight loss to have detectable outcomes in these particular categories. Even though weight loss may not make a big impact on these other weight-related outcomes, participating in self-monitoring via digital tracking for weight loss does not cause any harm. More studies with larger sample sizes are also needed that consider education and socioeconomic factors. With that being said, self-monitoring via digital tracking for the promotion of weight loss is a viable option for obese patients, however, plans or interventions should be individualized based on the patient and their needs or goals, access to the type of digital tracking method, and socioeconomic factors.
