Adherence to a Smartphone Application for Weight Loss Compared to Website and Paper Diary: Pilot Randomized Controlled Trial
Open accessAbstract
BACKGROUND: There is growing interest in the use of information communication technologies to treat obesity. An intervention delivered by smartphone could be a convenient, potentially cost-effective, and wide-reaching weight management strategy. Although there have been studies of texting-based interventions and smartphone applications (apps) used as adjuncts to other treatments, there are currently no randomized controlled trials (RCT) of a stand-alone smartphone application for weight loss that focuses primarily on self-monitoring of diet and physical activity. OBJECTIVE: The aim of this pilot study was to collect acceptability and feasibility outcomes of a self-monitoring weight management intervention delivered by a smartphone app, compared to a website and paper diary. METHODS: A sample of 128 overweight volunteers were randomized to receive a weight management intervention delivered by smartphone app, website, or paper diary. The smartphone app intervention, My Meal Mate (MMM), was developed by the research team using an evidence-based behavioral approach. The app incorporates goal setting, self-monitoring of diet and activity, and feedback via weekly text message. The website group used an existing commercially available slimming website from a company called Weight Loss Resources who also provided the paper diaries. The comparator groups delivered a similar self-monitoring intervention to the app, but by different modes of delivery. Participants were recruited by email, intranet, newsletters, and posters from large local employers. Trial duration was 6 months. The intervention and comparator groups were self-directed with no ongoing human input from the research team. The only face-to-face components were at baseline enrollment and brief follow-up sessions at 6 weeks and 6 months to take anthropometric measures and administer questionnaires. RESULTS: Trial retention was 40/43 (93%) in the smartphone group, 19/42 (55%) in the website group, and 20/43 (53%) in the diary group at 6 months. Adherence was statistically significantly higher in the smartphone group with a mean of 92 days (SD 67) of dietary recording compared with 35 days (SD 44) in the website group and 29 days (SD 39) in the diary group (P<.001). Self-monitoring declined over time in all groups. In an intention-to-treat analysis using baseline observation carried forward for missing data, mean weight change at 6 months was -4.6 kg (95% CI -6.2 to -3.0) in the smartphone app group, -2.9 kg (95% CI -4.7 to -1.1) in the diary group, and -1.3 kg (95% CI -2.7 to 0.1) in the website group. BMI change at 6 months was -1.6 kg/m(2) (95% CI -2.2 to -1.1) in the smartphone group, -1.0 kg/m(2) (95% CI -1.6 to -0.4) in the diary group, and -0.5 kg/m(2) (95% CI -0.9 to 0.0) in the website group. Change in body fat was -1.3% (95% CI -1.7 to -0.8) in the smartphone group, -0.9% (95% CI -1.5 to -0.4) in the diary group, and -0.5% (95% CI -0.9 to 0.0) in the website group. CONCLUSIONS: The MMM app is an acceptable and feasible weight loss intervention and a full RCT of this approach is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT01744535; http://clinicaltrials.gov/ct2/show/NCT01744535 (Archived by WebCite at http://www.webcitation.org/6FEtc3PVB).
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Written from the paper’s full text.
TL;DR
In a 6-month pilot randomized controlled trial, a stand-alone smartphone app for weight loss self-monitoring (My Meal Mate) produced higher trial retention and dietary self-monitoring adherence than a website or paper diary. The app was rated acceptable and feasible, and the authors concluded that a full RCT is warranted.
Key findings
- Trial retention at 6 months was 40/43 (93%) in the smartphone group, 19/42 (55%) in the website group, and 20/43 (53%) in the diary group.
- Mean days of dietary recording were 92 (SD 67) in the smartphone group, 35 (SD 44) in the website group, and 29 (SD 39) in the diary group (P<.001); self-monitoring declined over time in all groups.
- In intention-to-treat analysis with baseline observation carried forward, mean weight change at 6 months was –4.6 kg (95% CI –6.2 to –3.0) for smartphone, –2.9 kg (95% CI –4.7 to –1.1) for diary, and –1.3 kg (95% CI –2.7 to 0.1) for website.
- Clinically significant weight loss (≥5% of initial weight) was achieved by 16/43 (37.2%) in the smartphone group, 12/43 (27.9%) in the diary group, and 7/42 (16.7%) in the website group.
Methods
- Three-arm parallel-group pilot RCT: 128 overweight volunteers with BMI ≥27 kg/m², aged 18–65 years, recruited from large employers in Leeds, UK; randomized by minimization to smartphone app, website, or paper diary for 6 months.
- The smartphone intervention (My Meal Mate) included goal setting, self-monitoring of diet and activity, and weekly tailored text-message feedback; comparator groups used a commercial slimming website or paper diary plus calorie-counting book, all based on the same Weight Loss Resources food database.
- Primary outcomes were feasibility and acceptability, including trial retention and intervention adherence/frequency of use; anthropometric measures were taken at baseline, 6 weeks, and 6 months, with descriptive analyses, ANOVA/Kruskal-Wallis tests, and intention-to-treat and completer analyses.
Limitations
- The paper states that generalizability is limited because the sample was predominantly white, female, and employed in managerial/professional occupations; the app was a prototype and participants reported frequent bugs causing it to close; and contamination occurred, with 20 participants reporting use of another intervention, including one diary-group participant who used MyFitnessPal and lost 32 kg, strongly influencing the diary-group mean.
- The paper also states that unequal dropout among groups is a potential source of bias for a larger RCT, and that the pilot was not statistically powered to detect change in anthropometric measures.
- Evident from the text: the small pilot sample and high overall attrition (38%) limit interpretation of weight-loss effect sizes.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
0 of 14 cited sources checked · 0 supported · 0 flagged
- Findingown data
At 6 weeks, 86.8% reported satisfaction with the smartphone equipment, compared with 57.7% in the diary group and 50.0% in the website group (P=.02).
“When asked about how satisfied they were with the study equipment at 6 weeks, 86.8% reported that they were satisfied or very satisfied with the smartphone, compared with 57.7% in the diary group and 50.0% in the website group (P=.02).”
Quote in the paperSubstantial claim - Findingown data
Of those who completed the 6-week questionnaires (n=93), 91.2% of smartphone participants reported initial satisfaction with group allocation at baseline, compared with 23.1% in the diary group and 71.4% in the website group (P=.01).
“Of those who completed the 6-week questionnaires (n=93), 91.2% of smartphone participants reported that they were initially satisfied or very satisfied with their group allocation at baseline compared with 23.1% in the diary group and 71.4% in the website group (P=.01).”
Quote in the paperNot a substantial claim - Findingown data
In the smartphone group, 76.3% agreed or strongly agreed that they felt comfortable using the study equipment to record their diet in social settings, compared with 40.0% in the diary group and 21.1% in the website group (P<.001).
“In the smartphone group, 76.3% of participants agreed or strongly agreed that they felt comfortable using the study equipment to record their diet in social settings compared with 40.0% in the diary group and 21.1% in the website group (P<.001).”
Quote in the paperSubstantial claim - Findingown data
Self-reported ease of use of study equipment did not differ statistically significantly between the smartphone, diary, and website groups (86.8% smartphone, 65.0% diary, 83.3% website; P=.63).
“No statistically significant difference was seen between the groups for self-reported ease of use of study equipment. In the smartphone group, 86.8% reported that they found their study equipment easy to use, compared with 65.0% in the diary group and 83.3% in the website group (P=.63).”
Quote in the paperNot a substantial claim - Findingown data
At 6 months, weight change over time was statistically significantly greater in the smartphone group compared to the website group (-3.3 kg, 95% CI -5.4 to 1.2).
“At 6 months, weight change over time was statistically significantly greater in the smartphone group compared to the website group (–3.3 kg, 95% CI –5.4 to 1.2), but not when the smartphone group was compared to the diary group (P=.12).”
Quote in the paperNot a substantial claim
- Findingown data
The pilot trial suffered from 38% attrition overall.
“The pilot trial suffered from 38% attrition overall.”
Quote in the paperSubstantial claim - Findingown data
At 6 weeks and 6 months, satisfaction with group allocation was statistically significantly lower in the diary and Web groups.
“Questionnaire data collected at follow-up also supports dissatisfaction with treatment group because at 6 weeks and 6 months satisfaction with group allocation was statistically significantly lower in the diary and Web groups.”
Quote in the paperSubstantial claim - Findingown data
At 6 months, weight change over time was not statistically significantly greater in the smartphone group compared to the diary group (P=.12).
“At 6 months, weight change over time was statistically significantly greater in the smartphone group compared to the website group (–3.3 kg, 95% CI –5.4 to 1.2), but not when the smartphone group was compared to the diary group (P=.12).”
Quote in the paperNot a substantial claim - Findingown data
There was a statistically significant difference in follow-up weight between the groups at 6 months (P=.004).
“There was found to be a statistically significant difference in follow-up weight between the groups at 6 months (P=.004).”
Quote in the paperSubstantial claim - Findingown data
A dislike of the study equipment was the most popular reason given for nonattendance at follow-up.
“Unequal dropout among groups is likely to be intervention-related [32], and a dislike of the study equipment was the most popular reason given for nonattendance at follow-up.”
Quote in the paperSubstantial claim - Findingown data
Adherence to dietary recording at 6 months was statistically significantly higher in the smartphone group (mean 92 days, SD 67) than in the website group (mean 35 days, SD 44) and the diary group (mean 29 days, SD 39).
“Adherence was statistically significantly higher in the smartphone group with a mean of 92 days (SD 67) of dietary recording compared with 35 days (SD 44) in the website group and 29 days (SD 39) in the diary group (P<.001).”
- Also stated in: § Frequency of Use of the Interventions · plain
“Intervention usage was highest in the smartphone group at 6 months with a mean of 92 days (SD 67) completed compared with 29 days (SD 39) in the diary group and 35 (SD 44) in the website group. There was found to be a statistically significant difference in the number of days usage among the groups at 6 weeks (P<.001) and 6 months (P=.001).”
Quote in the paperSubstantial claim - Also stated in: § Frequency of Use of the Interventions · plain
- Findingown data
At 6 months, 63.2% of smartphone participants were satisfied with the study equipment, compared with 50.0% in the diary group and 42.1% in the website group (P=.05).
“At 6 months, of those who completed questionnaires (n=77), 63.2% of smartphone participants were satisfied or very satisfied with the study equipment compared with 50.0% in the diary group and 42.1% in the website group (P=.05).”
Quote in the paperNot a substantial claim - Findingown data
Self-reported convenience of use differed statistically significantly between the groups, with 64.9% in the smartphone group, 35.0% in the diary group, and 52.6% in the website group reporting convenience (P<.001).
“However, a statistically significant difference between the groups was found for self-reported convenience of use with 64.9% reporting that they found the smartphone convenient, (compared with 35.0% in the diary group and 52.6% in the website group, P<.001).”
Quote in the paperNot a substantial claim - Findingown data
At 6 months, 23 (30.0%) completers reported that they would not have volunteered for the trial if there had been no offer of using a smartphone.
“At 6 months, 23 (30.0%) completers reported that they would not have volunteered for the trial if there had been no offer of using a smartphone.”
Quote in the paperNot a substantial claim - Findingown data
In this trial, attrition was not equal among the groups, with more noncompleters at follow-up in the diary and Web groups compared to the smartphone group (P<.001).
“In this trial, attrition was not equal among the groups, with more noncompleters at follow-up in the diary and Web groups compared to the smartphone group (P<.001).”
Quote in the paperSubstantial claim - Findingown data
Self-monitoring declined over time in all groups.
“Self-monitoring declined over time in all groups.”
- Also stated in: § Frequency of Use of the Interventions · plain
“Usage within each intervention arm declined over time as shown in Figure 4.”
Quote in the paperNot a substantial claim - Also stated in: § Frequency of Use of the Interventions · plain
- Findingnone given
MMM was more highly rated in comparison to the diary and website on a range of acceptability measures, including overall satisfaction, convenience, and acceptability of use in social settings.
“In terms of acceptability, MMM was more highly rated in comparison to the diary and website on a range of acceptability measures, including overall satisfaction, convenience, and acceptability of use in social settings.”
Quote in the paperSubstantial claim - Findingown data
Adherence to dietary self-monitoring was statistically significantly higher in the smartphone group than the website and paper diary group (P<.001).
“Adherence to dietary self-monitoring was found to be statistically significantly higher in the smartphone group than the website and paper diary group (P<.001).”
Quote in the paperSubstantial claim - Findingown data
Twenty people in the trial reported that they had used another intervention (either instead of or in addition to their originally allocated intervention) during the trial.
“Twenty people in the trial also reported that they had used another intervention (either instead of or in addition to their originally allocated intervention) during the trial.”
Quote in the paperSubstantial claim - Findingown data
When an intention-to-treat analysis is used with baseline observation carried forward, the mean weight change in the diary and Web groups is more modest.
“When an intention-to-treat analysis is used with baseline observation carried forward for missing data, the mean weight change in the diary and Web groups is more modest.”
Quote in the paperNot a substantial claim - Study design and conductnone given
The pilot trial is not statistically powered to detect change in anthropometric measures.
“The pilot trial is not statistically powered to detect change in anthropometric measures; however, results are displayed to give an idea of effect size.”
Quote in the paperSubstantial claim - Study design and conductown data
Compared to trial completers, noncompleters had a statistically significantly greater baseline BMI and body fat.
“Compared to trial completers, noncompleters had a statistically significantly greater baseline BMI and BF.”
Quote in the paperNot a substantial claim - Study design and conductnone given
This pilot trial was not statistically powered to detect change in anthropometric measures.
“This pilot trial was not statistically powered to detect change in anthropometric measures; however, results are displayed for interest and to provide information on effect size.”
Quote in the paperSubstantial claim - Premisecitation
There have not been any RCTs of a smartphone app as a weight loss intervention in itself using both self-monitoring and text-messaging functions.
“Although there have been RCTs using text-messaging interventions for weight management, PDAs for self-monitoring and smartphone apps as adjuncts to other weight management interventions, to our knowledge there have not been any RCTs of a smartphone app as a weight loss intervention in itself using both self-monitoring and text-messaging functions.”
Quote in the paperSubstantial claim0 of 5 sources checked - Study design and conductown data
There was a statistically significant difference in self-reported health status at baseline between completers and noncompleters, with more completers reporting their health status as good or excellent (P=.001).
“There was a statistically significant difference in self-reported health status at baseline between completers and noncompleters, with more completers reporting their health status as good or excellent (P=.001).”
Quote in the paperNot a substantial claim - Interpretationcitation
Unequal dropout among groups is likely to be intervention-related.
“Unequal dropout among groups is likely to be intervention-related [32], and a dislike of the study equipment was the most popular reason given for nonattendance at follow-up.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [32] Altman, DG, 1991, Practical Statistics for Medical Research
Not checked in the free run.
- Interpretationcitation
The weight loss in the smartphone group is comparable to the weight loss achieved in a large multicentered RCT of popular commercial diet programs that reported an average weight loss of -5.9 kg at 6 months across all diets.
“This is comparable to the weight loss achieved in a large multicentered RCT of popular commercial diet programs that reported an average weight loss of -5.9 kg at 6 months across all diets [43].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [43] source
Not checked in the free run.
- Premisecitation
Adherence to self-monitoring is an important process outcome because it has been consistently linked to weight loss.
“Adherence to self-monitoring is an important process outcome because it has been consistently linked to weight loss [39].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [39] source
Not checked in the free run.
- Interpretationown data
Generalizability of the pilot results is limited given that the sample are predominantly white, female, and employed in managerial/professional occupations.
“Generalizability of the pilot results is limited given that the sample are predominantly white, female, and employed in managerial/professional occupations.”
Quote in the paperSubstantial claim
- May combine two claims. 34
- Classified as probably not a substantial claim. 18
- The quote only partly states this claim. 1
May combine two claims.
Findingown dataIn trial completers, mean weight change at 6 months was -5.0 kg (95% CI -6.7 to -3.3) in the smartphone group, -6.2 kg (95% CI -9.8 to -2.7) in the diary group, and -2.8 kg (95% CI -5.9 to 0.2) in the website group.
“In those who completed the trial, the mean weight change was –5.0 kg (95% CI –6.7 to –3.3) in the smartphone group, –6.2 kg (95% CI –9.8 to –2.7) in the diary group, and –2.8 kg (95% CI –5.9 to 0.2) in the website group.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataIn total, 128 people were randomly allocated to 1 of 3 groups, representing 38.1% of those who originally expressed interest and 70.3% of eligible invited participants.
“In total, 128 people were randomly allocated to 1 of the 3 groups. These 128 represented 38.1% of those who had originally expressed an interest in taking part, and 70.3% of those who had been invited to take part who met the eligibility criteria.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn an intention-to-treat analysis using baseline observation carried forward for missing data, mean weight change at 6 months was -4.6 kg (95% CI -6.2 to -3.0) in the smartphone app group, -2.9 kg (95% CI -4.7 to -1.1) in the diary group, and -1.3 kg (95% CI -2.7 to 0.1) in the website group.
“In an intention-to-treat analysis using baseline observation carried forward for missing data, mean weight change at 6 months was -4.6 kg (95% CI –6.2 to –3.0) in the smartphone app group, –2.9 kg (95% CI –4.7 to –1.1) in the diary group, and –1.3 kg (95% CI –2.7 to 0.1) in the website group.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataBMI change at 6 months was -1.6 kg/m2 (95% CI -2.2 to -1.1) in the smartphone group, -1.0 kg/m2 (95% CI -1.6 to -0.4) in the diary group, and -0.5 kg/m2 (95% CI -0.9 to 0.0) in the website group.
“BMI change at 6 months was –1.6 kg/m2 (95% CI –2.2 to –1.1) in the smartphone group, –1.0 kg/m2 (95% CI –1.6 to –0.4) in the diary group, and –0.5 kg/m2 (95% CI –0.9 to 0.0) in the website group.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAssuming baseline observation carried forward, 35/128 (27.3%) of all participants randomized achieved a clinically significant weight loss (≥5% of initial weight), including 16/43 (37.2%) in the smartphone group, 12/43 (27.9%) in the diary group, and 7/42 (16.7%) in the website group.
“Assuming baseline observation carried forward for those who did not return for follow-up at 6 months, 35/128 (27.3% of all participants randomized) achieved a clinically significant weight loss (≥5% of initial weight). This included 16/43 participants (37.2%) in the smartphone group, 12/43 (27.9%) participants in the diary group, and 7/42 (16.7%) participants in the website group.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataThe pilot trial recruited 128 participants, which was 95% of the original recruitment target.
“In terms of recruitment and response, we were able to recruit 128 participants to the pilot, which was 95% of the original recruitment target.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataThe sample was 77% women and 91% white.
“As is common to many weight loss trials, a large proportion of the sample (77%) were women and white (91%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataChange in body fat at 6 months was -1.3% (95% CI -1.7 to -0.8) in the smartphone group, -0.9% (95% CI -1.5 to -0.4) in the diary group, and -0.5% (95% CI -0.9 to 0.0) in the website group.
“Change in body fat was –1.3% (95% CI –1.7 to –0.8) in the smartphone group, –0.9% (95% CI –1.5 to –0.4) in the diary group, and –0.5% (95% CI –0.9 to 0.0) in the website group.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataOf those screened, 49 (21.2%) were excluded for not meeting inclusion criteria, and almost half (49.0%) were excluded because their self-reported BMI was less than 27 kg/m2.
“Of those screened, 49 (21.2%) were excluded for not meeting the inclusion criteria, and almost half (49.0%) were excluded because their self-reported BMI was less than 27 kg/m2.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the intention-to-treat analysis with baseline observation carried forward, change in BMI at 6 months was -1.6 kg/m2 (95% CI -2.2 to -1.1) in the smartphone group, -1.0 kg/m2 (95% CI -1.6 to -0.4) in the diary group, and -0.5 kg/m2 (95% CI -0.9 to 0.0) in the website group.
“In the intention-to-treat analysis with baseline observation carried forward, change in BMI at 6 months was –1.6 kg/m2 (95% CI –2.2 to –1.1) in the smartphone group, –1.0 kg/m2 (95% CI –1.6 to –0.4) in the diary group, and –0.5 kg/m2 (95% CI –0.9 to 0.0).”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataA similar trend in results was seen for BMI and BF in trial completers.
“A similar trend in results was seen for BMI and BF.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataMost participants (83.6%) heard about the study from an electronic source, either by email (61.7%) or intranet (21.9%).
“Most participants (83.6%) heard about the study from an electronic source, either by email (61.7%) or intranet (21.9%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataPairwise comparison showed the difference in number of days usage at 6 months lies between the smartphone and diary groups (P<.001), between the smartphone and website groups (P<.001), but not between the website and diary groups (P=.14).
“Pairwise comparison showed that this difference lies between the smartphone group and the diary group (P<.001), between the smartphone group and the website group (P<.001), but not between the website group and the diary group (P=.14).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn trial completers, there were no statistically significant differences in follow-up weight between the groups at 6 months (P=.63) or in difference in change over time (smartphone-diary P=.99; smartphone-website P=.40; diary-website P=.47).
“There were not found to be statistically significant differences in follow-up weight between the groups at 6 months (P=.63) or in difference in change over time (smartphone-diary, P=.99; smartphone-website, P=.40; diary-website, P=.47).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataTrial retention at 6 months was 40/43 (93%) in the smartphone group, 19/42 (55%) in the website group, and 20/43 (53%) in the diary group.
“Trial retention was 40/43 (93%) in the smartphone group, 19/42 (55%) in the website group, and 20/43 (53%) in the diary group at 6 months.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the intention-to-treat analysis with baseline observation carried forward, mean weight change at 6 months was -4.6 kg (95% CI -6.2 to -3.0) in the smartphone group, -2.9 kg (95% CI -4.7 to -1.1) in the diary group, and -1.3 kg (95% CI -2.7 to 0.1) in the website group.
“In the intention-to-treat analysis using all of the participants assigned to their original group, the mean weight change was –4.6 kg (95% CI –6.2 to –3.0) in the smartphone group, –2.9 kg (95% CI –4.7 to –1.1) in the diary group, and –1.3 kg (95% CI –2.7 to 0.1) in the website group.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataRecruitment to the trial took 3 months between March and May 2011.
“Recruitment to the trial took 3 months between March and May 2011.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe smartphone group had 93% retention at 6 months, compared with 53% in the diary group and 55% in the website group.
“In fact, the smartphone group had extremely high retention with 93% returning for follow-up at 6 months (compared with 53% in the diary group and 55% in the website group).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataOne participant allocated to the diary group reported using a commercially available weight loss smartphone app during the trial and lost 32 kg; excluding this participant, the mean weight change in completers was -4.8 kg (95% CI -7.1 to -2.7).
“One person allocated to the diary group reported that they had actually used a commercially available weight loss smartphone app during the trial rather than the paper diary. This person lost 32 kg overall; if they are excluded from the diary group analysis, the mean weight change in completers is –4.8 kg (95% CI –7.1 to –2.7).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the intention-to-treat analysis with baseline observation carried forward, change in body fat at 6 months was -1.3% (95% CI -1.7 to -0.8) in the smartphone group, -0.9% (95% CI -1.5 to -0.4) in the diary group, and -0.5% (95% CI -0.9 to 0.0) in the website group.
“Change in BF was –1.3% (95% CI –1.7 to –0.8) in the smartphone group, –0.9% (95% CI –1.5 to –0.4) in the diary group, and –0.5% (95% CI –0.9 to 0.0) in the website group.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe noncompleters in the trial were more likely to have a higher BMI at baseline and report poorer health status.
“The noncompleters in the trial were more likely to have a higher BMI at baseline and report poorer health status.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn all 3 groups, self-monitoring declined over time, so that by 6 months only 7 participants (16%) in the smartphone group had recorded their dietary intake every day, and no participants in the diary and Web groups had done this.
“In all 3 groups, self-monitoring declined over time so that by 6 months only 7 participants (16% of the group) in the smartphone group had managed to record their dietary intake every day (no participants in the diary and Web group had done this).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe MMM app was a prototype app and participants reported that they frequently encountered bugs that caused the app to close.
“The MMM app was a prototype app and participants reported that they frequently encountered bugs that caused the app to close.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductreasoningThis was not a phase III trial; a formal sample size calculation was not appropriate, and the trial aimed to recruit 135 based partly on available study equipment.
“This was not a phase III trial; therefore, a formal sample size calculation was not appropriate and there are few published guidelines on recommended sample sizes for pilot trials. The trial aimed to recruit a sample size of 135, which was a pragmatic decision based partly on the amount of available study equipment.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitationRandomization was by minimization using the Minim software package, balanced equally at the medians on starting BMI, age, and gender.
“After measurements were taken, participants were randomized by a process of minimization using the Minim software package [31] to 1 of 3 groups. The minimization balanced equally at the medians on 3 factors: starting BMI, age, and gender.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [31] EvansSRoystonPDaySMinim: allocation by minimisation in clinical trials2013-02-08http://www-users.york.ac.uk/~mb55/guide/minim.htm6EHn7EFx0
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenFieldworkers carrying out measurements were blinded to group assignment and participants were asked not to discuss their group allocation when measurements were taken.
“Fieldworkers carrying out measurements on participants were blinded to group assignment and participants were asked not to discuss their group allocation when measurements were taken.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThere were no statistically significant differences among the 3 intervention groups for the factors balanced at minimization: gender (P=.97), age (P=.82), and BMI (P=.74).
“There were no statistically significant differences found among the 3 intervention groups for the factors balanced at minimization: gender (P=.97), age (P=.82), and BMI (P=.74).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductreasoningAn intention-to-treat analysis was completed with baseline observations carried forward for missing data.
“As there is a proportion of missing data and unequal dropout, an intention-to-treat analysis was completed with baseline observations carried forward for missing data (Table 5).”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationCurrent UK evidence-based obesity guidelines advocate a lifestyle change approach to treatment; therefore, the key behavioral strategies of goal setting, self-monitoring, and feedback underpin the MMM app.
“Current UK evidence-based obesity guidelines advocate a lifestyle change approach to treatment [23]; therefore, in-line with this, the key behavioral strategies of goal setting, self-monitoring, and feedback underpin the MMM app.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [23] National Institute for Health and Clinical ExcellenceNational Collaborating Centre for Primary CareObesity: the prevention, identification, assessment and management of overweight and obesity in adults and children2006122013-02-08http://www.ncbi.nlm.nih.gov/books/NBK63696/pdf/TOC.pdf6EHmUsiDu
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAttrition is a serious difficulty in weight loss trials because of its potential to bias results.
“Attrition is a serious difficulty in weight loss trials because of its potential to bias results [35].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [35] source
Not checked in the free run.
May combine two claims.
Study design and conductown dataTrial dropout differed statistically significantly among the groups (P=.001), with 3 nonattendees at 6-month follow-up in the smartphone group compared with 23 in the diary group and 23 in the website group.
“Trial dropout was statistically significantly different among the groups (P=.001) with 3 people not attending 6-month follow-up in the smartphone group compared with 23 people not attending 6-month follow-up in the diary group and 23 people not attending 6-month follow-up in the website group.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductreasoningMost analyses are descriptive because this was a pilot trial and not powered to detect weight change.
“Most analyses are descriptive because this was a pilot trial and not powered to detect weight change.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoningTwo analyses were conducted because of missing data and unequal dropout: an intention-to-treat analysis using baseline weight carried forward for missing data, and an analysis of completers at 6-month follow-up.
“Two analyses were conducted because there was a proportion of missing data and unequal dropout between groups: an intention-to-treat analysis in which all are included but using baseline weight carried forward for missing data, and an analysis in just those who completed 6-month follow-up.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe MMM app is an acceptable and feasible weight loss intervention.
“The MMM app is an acceptable and feasible weight loss intervention and a full RCT of this approach is warranted.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationA large community-based survey showed that individuals desire alternatives to face-to-face weight loss treatments and some would be interested in minimal contact weight management programs.
“A large community-based survey showed that individuals desire alternatives to face-to-face weight loss treatments and, if given the choice, some would be interested in engaging with minimal contact weight management programs [5].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [5] Sherwood, NE, 1998, Am J Health Promot source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe diet measures captured on MMM have been found to correlate well with a reference measure of diet.
“The diet measures captured on MMM have been found to correlate well with a reference measure of diet [24].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [24] source
Not checked in the free run.
May combine two claims.
Interpretationown dataThe MMM app is a feasible and acceptable weight loss intervention.
“This pilot trial has shown the MMM app to be a feasible and acceptable weight loss intervention.”
- Also stated in: § Conclusion · boosted
“This pilot trial of a smartphone app for weight loss has shown that it is both an acceptable and feasible intervention.”
Quote in the paperSubstantial claim- Also stated in: § Conclusion · boosted
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationMobile phones are an intuitively appealing intervention platform given that they are ubiquitous, engaging, and portable.
“Mobile phones, in particular, are an intuitively appealing intervention platform given that they are ubiquitous, engaging, and portable [6].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [6] source
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductnone givenThis pilot trial has a randomized design.
“This pilot trial has several strengths including its randomized design.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataThe degree of contamination seen in the trial is a serious issue and has implications for the design of a definitive RCT.
“The degree of contamination seen in the trial is a serious issue and has implications for the design of a definitive RCT.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenThe app used in the trial is up-to-date and comparable in appearance and functionality to commercial diet tracking apps.
“Another strength of the trial is the up-to-date app for tracking diet and physical activity which is comparable in appearance and functionality to commercial diet tracking apps.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
InterpretationreasoningUnequal dropout is a potential source of bias in a large RCT.
“Unequal dropout is a potential source of bias in a large RCT so this will need to be considered for the full trial.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Smartphone apps are likely to be used as a stand-alone intervention rather than as an adjunct to another intervention.
“A trial of this type is necessary because smartphone apps are readily available to the public to download and likely to be used as a stand-alone intervention rather than as an adjunct to another intervention (such as podcasts or face-to-face advice).”
The paper relies on this without support.
Commercial diet tracking apps have not been comprehensively evaluated to date.
“Despite their apparent popularity, these commercial apps have not been comprehensively evaluated to date.”
The paper relies on this without support.
There have been no large RCTs of smartphone apps for weight loss.
“To our knowledge, there have been no large RCTs of smartphone apps for weight loss and this pilot trial provides valuable data that could be used to inform such a trial.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Electronic self-monitoring tools have led to better adherence to self-monitoring in BWL than paper-and-pencil tracking.
“Electronic self-monitoring tools, as compared to paper-and-pencil tracking, have produced increased adherence to self-monitoring within BWL”
From Associations Between Self-Monitoring and Weight Change in Behavioral Weight Loss Interventions (2019) · cites this paper as Carter, Burley, Nykjaer, & Cade, 2013
Adherence to diet self-monitoring is higher among patients using a smartphone app compared to patients using a paper diary.
“One pilot trial recently demonstrated that adherence to diet self-monitoring is higher among patients using a smartphone app compared to patients using a paper diary (13).”
From Effectiveness of a Smartphone Application for Weight Loss Compared With Usual Care in Overweight Primary Care Patients: A Randomized, Controlled Trial (2014) · cites this paper as [13]
Brief, daily or weekly feedback and encouragement could boost usage and self-efficacy in dieting.
“Brief, daily or weekly feedback and encouragement could also boost usage and self-efficacy in dieting (13).”
From Effectiveness of a Smartphone Application for Weight Loss Compared With Usual Care in Overweight Primary Care Patients: A Randomized, Controlled Trial (2014) · cites this paper as [13]
Previous research reveals positive usage and views of app-based self-monitoring interventions.
“This contrasts with previous research revealing positive usage and views of app-based self-monitoring interventions [16,17,44]”
From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [17]
Previous examinations of hybrid interventions designed to promote self-monitoring of behavior have reported that app-based delivery was associated with better adherence to self-monitoring compared to Web-based formats.
“Previous examinations of hybrid interventions designed to promote self-monitoring of behavior have reported that app-based delivery was associated with better adherence to self-monitoring compared to Web-based formats [17,44].”
From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [17]
Unlike the interventions provided by Carter et al and Kirwan et al, self-monitoring was not the only technique promoted by the POWeR intervention.
“Unlike the interventions provided by Carter et al [17] and Kirwan et al [44], self-monitoring was not the only technique promoted by the POWeR intervention.”
From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [17]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Diary retention percentage is incorrect
MajorAt 6 months, 20 of 43 diary participants were retained, or 46.5%, not 53%. The stated 53% is approximately the percentage who did not return.
Reported 53 · recomputed 46.511628
“20/43 (53%) in the diary group”
Website retention percentage is incorrect
MajorAt 6 months, 19 of 42 website participants were retained, or 45.2%, not 55%. The stated 55% is approximately the percentage who did not return.
Reported 55 · recomputed 45.238095
“19/42 (55%) in the website group”
Smartphone baseline weight differs between tables
MinorTables 1 and 5 both give baseline weight for all 43 smartphone participants, but report means of 96.4 kg and 96.8 kg, respectively.
“| Weight (kg), mean (SD) | 96.4 (16.0) | 97.9 (18.7) | 96.4 (19.9) |”
“| | Baseline | 43 | 96.8 (91.9-101.8) | 43 | 97.9 (92.2-103.6) | 42 | 96.4 (90.2-102.6) | |”
Six-week follow-up count differs between text and Table 6
MinorThe text says 94 participants returned for six-week follow-up measurements, but Table 6 describes recorded anthropometric measures at six weeks for 95 participants.
“94 (73.4%) people returned for 6-week follow-up measurements”
“Table: Table 6 Change in recorded anthropometric measures at 6 weeks (n=95) and 6 months (n=79) for trial completers.”
Six-month intervention-use P value differs between text and table
MinorThe text reports P=.001 for the between-group difference at 6 months, whereas Table 4 reports P<.001.
“and 6 months (P=.001).”
“| 6 months (184 days), median (IQR) | 82 (28-172) | 18 (0-37) | 15 (7-45) | <.001 |”
Percentage for 31 diary participants does not match group size
MinorTable 4 labels the diary group as n=43. Thus 31 participants represent 72.1%, not the reported 78%; no different denominator is specified for this row.
Reported 78 · recomputed 72.093023
“| Completing 0 days/not returningpaper diary, n (%) | 1 (2) | 31 (78) | 3(7) | |”
Six-week intervention-use P value differs between text and table
MinorThe text reports P<.001 for the between-group difference at 6 weeks, whereas Table 4 reports .004 for that comparison.
“among the groups at 6 weeks (P<.001)”
“| 6 weeks (42 days), median (IQR) | 36 (21-42) | 29 (0-38) | 15 (6-33) | .004 |”
Claimed significant weight difference has a confidence interval crossing zero
MinorThe reported 95% confidence interval for the smartphone-website difference extends from a negative value to a positive value, contradicting the statement that this difference was statistically significant.
“weight change over time was statistically significantly greater in the smartphone group compared to the website group”
“(–3.3 kg, 95% CI –5.4 to 1.2)”
Cites
International physical activity questionnaire: 12-country reliability and validity
CRAIG, C. L., MARSHALL, A. L., SJ??STR??M, M., BAUMAN, A. E., BOOTH, M. L., AINSWORTH, B. E., PRATT, M., EKELUND, U., YNGVE, A., SALLIS, J. F., et al. (2003) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000078924.61453.fb · Cited by 21,619 · see citing works
CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials
the CONSORT Group, Schulz, K. F., Altman, D. G., & Moher, D. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-18 · Cited by 13,371 · see citing works
Practical Statistics for Medical Research.
Walter, S., & Altman, D. G. (1992) · Biometrics · doi:10.2307/2532320 · Cited by 11,665 · see citing works
Practical Statistics for Medical Research
Altman, D. G. (1990) · doi:10.1201/9780429258589 · Cited by 10,668 · see citing works
CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials
Schulz, K. F., Altman, D. G., Moher, D., & for the CONSORT Group (2010) · BMJ · doi:10.1136/bmj.c332 · Cited by 9,329 · see citing works
The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger
Stunkard, A. J., & Messick, S. (1985) · Journal of Psychosomatic Research · doi:10.1016/0022-3999(85)90010-8 · Cited by 4,687 · see citing works
The international personality item pool and the future of public-domain personality measures
Goldberg, L. R., Johnson, J. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., & Gough, H. G. (2006) · Journal of Research in Personality · doi:10.1016/j.jrp.2005.08.007 · Cited by 3,185 · see citing works
Fuller, N. R., Colagiuri, S., SCHOFIELD, D. J., Olson, A. D., Shrestha, R. N., Holzapfel, C., Wolfenstetter, S. B., Holle, R., Ahern, A. L., Hauner, H., et al. (2012) · International Journal of Obesity · doi:10.1038/ijo.2012.139 · Cited by 2,125 · see citing works
Eysenbach, G., & CONSORT-EHEALTH Group (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1923 · Cited by 1,863 · cited 1× · see citing works
“gov NCT01744535) and reported in accordance with the CONSORT-EHEALTH checklist [33].”
MethodThe consideration of future consequences: Weighing immediate and distant outcomes of behavior.
Strathman, A., Gleicher, F., Boninger, D. S., & Edwards, C. S. (1994) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.66.4.742 · Cited by 1,782 · see citing works
Self-monitoring in weight loss: a systematic review of the literature
Burke, L. E., Wang, J., & Sevick, M. A. (2011) · Journal of the American Dietetic Association · doi:10.1016/j.jada.2010.10.008 · Cited by 1,203 · cited 1× · see citing works
“Adherence to self-monitoring is an important process outcome because it has been consistently linked to weight loss [39].”
BackgroundConsolvo, S., McDonald, D. W., Toscos, T., Chen, M. Y., Froehlich, J. E., Harrison, B. L., Klasnja, P., LaMarca, A., LeGrand, L., Libby, R., et al. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357335 · Cited by 1,133 · see citing works
CONSORT 2010 statement: Updated guidelines for reporting parallel group randomised trials
Schulz, K. F., Altman, D. G., & Moher, D. (2011) · International Journal of Surgery · doi:10.1016/j.ijsu.2011.09.004 · Cited by 1,044 · see citing works
Healthcare in the pocket: Mapping the space of mobile-phone health interventions
Klasnja, P., & Pratt, W. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.08.017 · Cited by 970 · see citing works
Foresight. Tackling obesities: future choices. Project report.
Butland, B. K., Jebb, S. A., Kopelman, P., McPherson, K., Thomas, S., Mardell, J., & Parry, V. G. (2007) · Cited by 832 · see citing works
A Text Message–Based Intervention for Weight Loss: Randomized Controlled Trial
Patrick, K., Raab, F., Adams, M. A., Dillon, L., Zabinski, M., Rock, C. L., Griswold, W. G., & Norman, G. J. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1100 · Cited by 671 · see citing works
Douketis, J. D., Macie, C., Thabane, L., & Williamson, D. F. (2005) · International Journal of Obesity · doi:10.1038/sj.ijo.0802982 · Cited by 665 · see citing works
Hurling, R., Catt, M., De Boni, M., Fairley, B. W., Hurst, T., Murray, P., Richardson, A., & Sodhi, J. S. (2007) · Journal of Medical Internet Research · doi:10.2196/jmir.9.2.e7 · Cited by 536 · see citing works
Neve, M., Morgan, P. J., Jones, P. R., & Collins, C. E. (2010) · Obesity Reviews · doi:10.1111/j.1467-789x.2009.00646.x · Cited by 459 · see citing works
Jolly, K., Lewis, A., Beach, J., Denley, J., Adab, P., Deeks, J. J., Daley, A., & Aveyard, P. (2011) · BMJ · doi:10.1136/bmj.d6500 · Cited by 359 · see citing works
Burke, L. E., Conroy, M. B., Sereika, S. M., Elci, O. U., Styn, M. A., Acharya, S. D., Sevick, M. A., Ewing, L. J., & Glanz, K. (2011) · Obesity · doi:10.1038/oby.2010.208 · Cited by 329 · see citing works
Truby, H., Baic, S., deLooy, A., Fox, K. R., Livingstone, M. B. E., Logan, C. M., Macdonald, I. A., Morgan, L. M., Taylor, M. A., & Millward, D. J. (2006) · BMJ · doi:10.1136/bmj.38833.411204.80 · Cited by 284 · see citing works
Weight loss by mobile phone: a 1-year effectiveness study
Haapala, I., Barengo, N. C., Biggs, S., Surakka, L., & Manninen, P. (2009) · Public Health Nutrition · doi:10.1017/s1368980009005230 · Cited by 280 · see citing works
Tsai, C. C., Lee, G., Raab, F., Norman, G. J., Sohn, T. Y., Griswold, W. G., & Patrick, K. (2007) · Mobile Networks and Applications · doi:10.1007/s11036-007-0014-4 · Cited by 267 · see citing works
Turner-McGrievy, G., & Tate, D. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1841 · Cited by 263 · see citing works
MobileMums: A Randomized Controlled Trial of an SMS-Based Physical Activity Intervention
Fjeldsoe, B. S., Miller, Y. D., & Marshall, A. L. (2010) · Annals of Behavioral Medicine · doi:10.1007/s12160-010-9170-z · Cited by 244 · see citing works
Emotion rating from short blog texts
Gill, A. J., Gergle, D., French, R. M., & Oberlander, J. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357229 · Cited by 232 · see citing works
Interpreting Incomplete Data in Studies of Diet and Weight Loss
Ware, J. H. (2003) · New England Journal of Medicine · doi:10.1056/nejme030054 · Cited by 205 · see citing works
Joo, N.-S., & Kim, B.-T. (2007) · Journal of Telemedicine and Telecare · doi:10.1258/135763307783064331 · Cited by 161 · see citing works
Text4Diet: A randomized controlled study using text messaging for weight loss behaviors
Shapiro, J. R., Koro, T., Doran, N., Thompson, S., Sallis, J. F., Calfas, K., & Patrick, K. (2012) · Preventive Medicine · doi:10.1016/j.ypmed.2012.08.011 · Cited by 151 · see citing works
Carter, M. C., Burley, V. J., Nykjaer, C., & Cade, J. E. (2013) · British Journal of Nutrition · doi:10.1017/s0007114512001353 · Cited by 144 · see citing works
Self-citationTurner-McGrievy, G. M., Campbell, M. K., Tate, D. F., Truesdale, K. P., Bowling, J. M., & Crosby, L. (2009) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2009.06.010 · Cited by 112 · see citing works
Evaluation of a mobile phone-based diet game for weight control
Lee, W., Chae, Y. M., Kim, S., Ho, S. H., & Choi, I. (2010) · Journal of Telemedicine and Telecare · doi:10.1258/jtt.2010.090913 · Cited by 92 · see citing works
Yon, B. A., Johnson, R. K., Harvey‐Berino, J., & Gold, B. C. (2006) · Journal of the American Dietetic Association · doi:10.1016/j.jada.2006.05.004 · Cited by 89 · see citing works
Consumer Preferences in Format and Type of Community-Based Weight Control Programs
Sherwood, N. E., Morton, N., Jeffery, R. W., French, S. A., Neumark-Sztainer, D., & Falkner, N. H. (1998) · American Journal of Health Promotion · doi:10.4278/0890-1171-13.1.12 · Cited by 86 · see citing works
Empowering Citizens for Well-being and Chronic Disease Management With Wellness Diary
Mattila, E., Korhonen, I., Salminen, J. H., Ahtinen, A., Koskinen, E., Sarela, A., Parkka, J., & Lappalainen, R. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2009.2037751 · Cited by 86 · see citing works
Obesity: Mechanisms and Clinical Management
Kennel, K. A. (2004) · Mayo Clinic Proceedings · doi:10.4065/79.2.280-d · Cited by 75 · see citing works
Use of a mobile phone diary for observing weight management and related behaviours
Mattila, E., Lappalainen, R. I., Pärkkä, J., Salminen, J., & Korhonen, I. (2010) · Journal of Telemedicine and Telecare · doi:10.1258/jtt.2009.091103 · Cited by 47 · see citing works
Tsai, C. C., Lee, G., Raab, F., Norman, G. J., Sohn, T. Y., Griswold, W. G., & Patrick, K. (2006) · doi:10.1109/pcthealth.2006.361659 · Cited by 13 · see citing works
Flagged first, then by citations
1 of the 40 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- National Institute for Health and Clinical ExcellenceNational Collaborating Centre for Primary CareObesity: the prevention, identification, assessment and management of overweight and obesity in adults and children2006122013-02-08http://www.ncbi.nlm.nih.gov/books/NBK63696/pdf/TOC.pdf6EHmUsiDu
- Kellow, J, 2011, Calorie, Carb & Fat Bible
- 10.1038/oby.2010.208 · DOI · Paper page
Cited by
Sorted by citations
Perski, O., Blandford, A., West, R., & Michie, S. (2017) · Translational Behavioral Medicine · doi:10.1007/s13142-016-0453-1 · Cited by 1,210 · see citing works
The Rise of Consumer Health Wearables: Promises and Barriers
Piwek, L., Ellis, D. A., Andrews, S., & Joinson, A. (2016) · PLoS Medicine · doi:10.1371/journal.pmed.1001953 · Cited by 1,298 · see citing works
Smartphones for smarter delivery of mental health programs: A systematic review
Donker, T., Petrie, K., Proudfoot, J., Clarke, J., Birch, M.-R., & Christensen, H. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2791 · Cited by 1,136 · see citing works
Gill, S., & Panda, S. (2015) · Cell Metabolism · doi:10.1016/j.cmet.2015.09.005 · Cited by 894 · see citing works
Can Mobile Phone Apps Influence People’s Health Behavior Change? An Evidence Review
Zhao, J., Freeman, B., & Li, M. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5692 · Cited by 618 · see citing works
Flores Mateo, G., Granado-Font, E., Ferré-Grau, C., & Montaña-Carreras, X. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4836 · Cited by 540 · see citing works
Burke, L. E., Ma, J., Azar, K. M. J., Bennett, G. G., Peterson, E. D., Zheng, Y., Riley, W., Stephens, J., Shah, S. H., Suffoletto, B., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000232 · Cited by 516 · see citing works
A qualitative study of user perceptions of mobile health apps
Peng, W., Kanthawala, S., Yuan, S., & Hussain, S. A. (2016) · BMC Public Health · doi:10.1186/s12889-016-3808-0 · Cited by 465 · see citing works
Payne, H., Lister, C., West, J. H., & Bernhardt, J. M. (2015) · JMIR mhealth and uhealth · doi:10.2196/mhealth.3335 · Cited by 525 · see citing works
The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial
Arean, P. A., Hallgren, K. A., Jordan, J. T., Gazzaley, A., Atkins, D. C., Heagerty, P. J., & Anguera, J. A. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6482 · Cited by 376 · see citing works
Jakob, R., Harperink, S., Rudolf, A. M., Fleisch, E., Haug, S., Mair, J. L., Salamanca-Sanabria, A., & Kowatsch, T. (2022) · Journal of Medical Internet Research · doi:10.2196/35371 · Cited by 446 · see citing works
Does monitoring goal progress promote goal attainment? A meta-analysis of the experimental evidence.
Harkin, B., Webb, T. L., Chang, B. P. I., Prestwich, A., Conner, M., Kellar, I., Benn, Y., & Sheeran, P. (2016) · Psychological Bulletin · doi:10.1037/bul0000025 · Cited by 564 · see citing works
Weight-loss intervention adherence and factors promoting adherence: a meta-analysis
Rogers, M., Lemstra, M., Bird, Y., Nwankwo, C., & Moraros, J. (2016) · Patient Preference and Adherence · doi:10.2147/ppa.s103649 · Cited by 345 · see citing works
Laing, B. Y., Mangione, C. M., Tseng, C.-H., Leng, M., Vaisberg, E., Mahida, M., Bholat, M., Glazier, E., Morisky, D. E., & Bell, D. S. (2014) · Annals of Internal Medicine · doi:10.7326/m13-3005 · Cited by 353 · see citing works
Smartphone Applications for Patients' Health and Fitness
Higgins, J. P. (2015) · The American Journal of Medicine · doi:10.1016/j.amjmed.2015.05.038 · Cited by 357 · see citing works
Cradock, K. A., ÓLaighin, G., Finucane, F. M., Gainforth, H. L., Quinlan, L. R., & Ginis, K. A. M. (2017) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-016-0436-0 · Cited by 343 · see citing works
Mobile Applications for Weight Management
Azar, K. M. J., Lesser, L. I., Laing, B. Y., Stephens, J., Aurora, M. S., Burke, L. E., & Palaniappan, L. P. (2013) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2013.07.005 · Cited by 334 · see citing works
Sieverink, F., Kelders, S. M., & van Gemert-Pijnen, J. E. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.8578 · Cited by 331 · see citing works
Prescribable mHealth apps identified from an overview of systematic reviews
Byambasuren, O., Sanders, S., Beller, E., & Glasziou, P. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0021-9 · Cited by 291 · see citing works
Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement
Nadal, C., Sas, C., & Doherty, G. (2020) · Journal of Medical Internet Research · doi:10.2196/17256 · Cited by 320 · see citing works
Smartphones and Health Promotion: A Review of the Evidence
Bert, F., Giacometti, M., Gualano, M. R., & Siliquini, R. (2013) · Journal of Medical Systems · doi:10.1007/s10916-013-9995-7 · Cited by 314 · see citing works
Villinger, K., Wahl, D. R., Boeing, H., Schupp, H. T., & Renner, B. (2019) · Obesity Reviews · doi:10.1111/obr.12903 · Cited by 290 · see citing works
mHealth and Mobile Medical Apps: A Framework to Assess Risk and Promote Safer Use
Lewis, T., & Wyatt, J. C. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3133 · Cited by 281 · see citing works
The impact of post-adoption beliefs on the continued use of health apps
Cho, J. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.12.016 · Cited by 277 · see citing works
Prevention of stroke: a strategic global imperative
Feigin, V. L., Norrving, B., George, M. G., Foltz, J. L., Roth, G. A., & Mensah, G. A. (2016) · Nature Reviews Neurology · doi:10.1038/nrneurol.2016.107 · Cited by 250 · see citing works
Vashist, S. K., Schneider, E. M., & Luong, J. H. T. (2014) · Diagnostics · doi:10.3390/diagnostics4030104 · Cited by 245 · see citing works
The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment
Chen, J., Cade, J. E., & Allman-Farinelli, M. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4334 · Cited by 219 · see citing works
Self-citationHan, M., & Lee, E. (2018) · Healthcare Informatics Research · doi:10.4258/hir.2018.24.3.207 · Cited by 247 · see citing works
Cho, J., Dong-Jin, P., & Lee, H. E. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3283 · Cited by 236 · see citing works
Mobile App-Based Health Promotion Programs: A Systematic Review of the Literature
Lee, M., Lee, H., Kim, Y., Kim, J.-H., Cho, M., Jang, J., & Jang, H. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15122838 · Cited by 237 · see citing works
Réda, A., Wassil, M., Meriem, M., Alexia, P., Abdelmalik, H., Sabine, B., & Nassir, M. (2020) · Nutrients · doi:10.3390/nu12123770 · Cited by 189 · see citing works
Eldridge, A. L., Piernas, C., Illner, A., Gibney, M. J., Gurinović, M. A., de Vries, J. H. M., & Cade, J. E. (2018) · Nutrients · doi:10.3390/nu11010055 · Cited by 212 · see citing works
Self-citationBelisario, J. S. M., Jamšek, J., Huckvale, K., O’Donoghue, J., Morrison, C. P., & Car, J. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.mr000042.pub2 · Cited by 216 · see citing works
The use of mobile apps to improve nutrition outcomes: A systematic literature review
DiFilippo, K. N., Huang, W. D., Andrade, J. E., & Chapman‐Novakofski, K. (2015) · Journal of Telemedicine and Telecare · doi:10.1177/1357633x15572203 · Cited by 210 · see citing works
A Novel Diabetes Prevention Intervention Using a Mobile App
Fukuoka, Y., Gay, C. L., Joiner, K. L., & Vittinghoff, E. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2015.01.003 · Cited by 204 · see citing works
Adherence to Endocrine Therapy in Breast Cancer Adjuvant and Prevention Settings
Chlebowski, R. T., Kim, J., & Haque, R. (2014) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-13-0389 · Cited by 190 · see citing works
The history and future of digital health in the field of behavioral medicine
Arigo, D., Jake‐Schoffman, D. E., Wolin, K. Y., Beckjord, E. B., Hekler, E. B., & Pagoto, S. (2019) · Journal of Behavioral Medicine · doi:10.1007/s10865-018-9966-z · Cited by 189 · see citing works
McCarroll, M. L., Armbruster, S., Pohle-Krauza, R. J., Lyzen, A. M., Min, S., Nash, D. W., Roulette, G. D., Andrews, S. J., & von Gruenigen, V. E. (2015) · Gynecologic Oncology · doi:10.1016/j.ygyno.2014.12.025 · Cited by 170 · see citing works
Kim, J. Y., Wineinger, N. E., & Steinhubl, S. R. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5429 · Cited by 180 · see citing works
Gibson, A., & Sainsbury, A. (2017) · Behavioral Sciences · doi:10.3390/bs7030044 · Cited by 181 · see citing works
Asbjørnsen, R. A., Smedsrød, M. L., Solberg Nes, L., Wentzel, J., Varsi, C., Hjelmesæth, J., & van Gemert-Pijnen, J. E. (2019) · Journal of Medical Internet Research · doi:10.2196/14265 · Cited by 150 · see citing works
Quante, M., Kaplan, E. R., Rueschman, M., Cailler, M., Buxton, O. M., & Redline, S. S. (2015) · Sleep Health · doi:10.1016/j.sleh.2015.09.002 · Cited by 167 · see citing works
Ivanova, E., Lindner, P., Ly, K. H., Dahlin, M., Vernmark, K., Andersson, G., & Carlbring, P. (2016) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2016.09.012 · Cited by 165 · see citing works
Lee, H. E., & Cho, J. (2016) · Health Communication · doi:10.1080/10410236.2016.1167998 · Cited by 163 · see citing works
Feasibility and validity of mobile phones to assess dietary intake
Sharp, D. B., & Allman-Farinelli, M. A. (2014) · Nutrition · doi:10.1016/j.nut.2014.02.020 · Cited by 156 · see citing works
Big Data and Disease Prevention: From Quantified Self to Quantified Communities
Barrett, M., Humblet, O., Hiatt, R. A., & Adler, N. E. (2013) · Big Data · doi:10.1089/big.2013.0027 · Cited by 158 · see citing works
Palmer, M., Sutherland, J., Barnard, S., Wynne, A., Rezel, E., Doel, A., Grigsby-Duffy, L., Edwards, S., Russell, S., Hotopf, E., et al. (2018) · PLOS ONE · doi:10.1371/journal.pone.0189801 · Cited by 136 · see citing works
Mobile Health Applications in Weight Management: A Systematic Literature Review
Dounavi, K., & Tsoumani, O. (2019) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2018.12.005 · Cited by 154 · see citing works
Smartphone Applications for Promoting Healthy Diet and Nutrition: A Literature Review.
Coughlin, S. S., Whitehead, M. S., Sheats, J. Q., Mastromonico, J., Hardy, D. S., & Smith, S. A. (2015) · PubMed · Cited by 152 · see citing works
Schippers, M., Adam, P. C. G., Smolenski, D. J., Wong, H. T. H., & de Wit, J. B. F. (2017) · Obesity Reviews · doi:10.1111/obr.12492 · Cited by 150 · see citing works
Measuring diet in the 21st century: use of new technologies
Cade, J. E. (2016) · Proceedings of The Nutrition Society · doi:10.1017/s0029665116002883 · Cited by 159 · see citing works
Self-citationGuertler, D., Vandelanotte, C., Kirwan, M., & Duncan, M. J. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4339 · Cited by 147 · see citing works
Naslund, J. A., Aschbrenner, K. A., Barre, L. K., & Bartels, S. J. (2015) · Telemedicine and e-Health · doi:10.1089/tmj.2014.0105 · Cited by 144 · see citing works
Chin, S. O., Keum, C., Woo, J., Park, J., Choi, H. J., Woo, J., & Rhee, S. Y. (2016) · Scientific Reports · doi:10.1038/srep34563 · Cited by 138 · see citing works
Dute, D. J., Bemelmans, W. J. E., & Breda, J. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.3559 · Cited by 142 · see citing works
Abaza, H., & Marschollek, M. (2017) · Methods of Information in Medicine · doi:10.3414/me17-05-0003 · Cited by 138 · see citing works
Sherifali, D., Nerenberg, K. A., Wilson, S., Semeniuk, K., Ali, M. U., Redman, L. M., & Adamo, K. B. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.8006 · Cited by 122 · see citing works
Use of Mobile Phone App Interventions to Promote Weight Loss: Meta-Analysis
Islam, M. M., Poly, T. N., Walther, B. A., & (Jack) Li, Y.-C. (2020) · JMIR mHealth and uHealth · doi:10.2196/17039 · Cited by 114 · see citing works
Hussain, M., Al-Haiqi, A., Zaidan, A. A., Zaidan, B. B., Kiah, M. L. M., Anuar, N. B., & Abdulnabi, M. S. H. (2015) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2015.08.015 · Cited by 131 · see citing works
Controlling Your “App”etite: How Diet and Nutrition-Related Mobile Apps Lead to Behavior Change
West, J. H., Belvedere, L. M., Andreasen, R., Frandsen, C., Hall, C. P., & Crookston, B. T. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.7410 · Cited by 129 · see citing works
Patel, M. L., Hopkins, C. M., Brooks, T. L., & Bennett, G. G. (2019) · JMIR mhealth and uhealth · doi:10.2196/12209 · Cited by 130 · see citing works
Mobile Apps for Weight Management: A Review of the Latest Evidence to Inform Practice
Ghelani, D. P., Moran, L., Johnson, C. S., Mousa, A., & Naderpoor, N. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.00412 · Cited by 109 · see citing works
Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives
Miron‐Shatz, T., Lau, A. Y. S., Paton, C., & Hansen, M. M. (2014) · Yearbook of Medical Informatics · doi:10.15265/iy-2014-0004 · Cited by 127 · see citing works
Overview of smartphone applications for sleep analysis
Ong, A. A., & Gillespie, M. B. (2016) · World Journal of Otorhinolaryngology - Head and Neck Surgery · doi:10.1016/j.wjorl.2016.02.001 · Cited by 124 · see citing works
Cavero‐Redondo, I., Martínez‐Vizcaíno, V., Fernández-Rodríguez, R., Saz‐Lara, A., Pascual‐Morena, C., & Álvarez‐Bueno, C. (2020) · Nutrients · doi:10.3390/nu12071977 · Cited by 123 · see citing works
Lyzwinski, L. N. (2014) · Journal of Personalized Medicine · doi:10.3390/jpm4030311 · Cited by 120 · see citing works
Using a Smartphone Application to Promote Healthy Dietary Behaviours and Local Food Consumption
Gilliland, J., Sadler, R., Clark, A., O’Connor, C., Milczarek, M., & Doherty, S. (2015) · BioMed Research International · doi:10.1155/2015/841368 · Cited by 112 · see citing works
Khoury, C. F. E., Karavetian, M., Halfens, R. J. G., Crutzen, R., Khoja, L., & Schols, J. M. G. A. (2019) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2018.11.010 · Cited by 114 · see citing works
Get with the program: Adherence to a smartphone app for smoking cessation
Zeng, E. Y., Heffner, J. L., Copeland, W. K., Mull, K. E., & Bricker, J. B. (2016) · Addictive Behaviors · doi:10.1016/j.addbeh.2016.07.007 · Cited by 117 · see citing works
Smartphone apps and the nutrition care process: Current perspectives and future considerations
Chen, J., Gemming, L., Hanning, R. M., & Allman-Farinelli, M. A. (2017) · Patient Education and Counseling · doi:10.1016/j.pec.2017.11.011 · Cited by 116 · see citing works
Mason, A. E., Jhaveri, K., Cohn, M., & Brewer, J. A. (2018) · Journal of Behavioral Medicine · doi:10.1007/s10865-017-9884-5 · Cited by 106 · see citing works
Zhou, M., Fukuoka, Y., Mintz, Y., Goldberg, K., Kaminsky, P., Flowers, E., & Aswani, A. (2018) · JMIR mHealth and uHealth · doi:10.2196/mhealth.9117 · Cited by 111 · see citing works
Diet and Physical Activity Apps: Perceived Effectiveness by App Users
Wang, Q., Egelandsdal, B., Amdam, G. V., Almli, V. L., & Oostindjer, M. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.5114 · Cited by 112 · see citing works
Technology-based interventions in the treatment of overweight and obesity: A systematic review.
Raaijmakers, L. C. H., Pouwels, S., Berghuis, K., & Nienhuijs, S. (2015) · Appetite · doi:10.1016/j.appet.2015.07.008 · Cited by 103 · see citing works
BinDhim, N. F., McGeechan, K., & Trevena, L. J. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-017105 · Cited by 111 · see citing works
Naimark, J. S., Madar, Z., & Shahar, D. R. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3682 · Cited by 108 · see citing works
Samoggia, A., & Riedel, B. (2019) · Food Research International · doi:10.1016/j.foodres.2019.108766 · Cited by 116 · see citing works
IT-Enabled Self-Monitoring for Chronic Disease Self-Management: An Interdisciplinary Review
Jiang, J., & Cameron, A. (2020) · MIS Quarterly · doi:10.25300/misq/2020/15108 · Cited by 108 · see citing works
Pope, Z., Lee, J. E., Zeng, N., Lee, H. Y., & Gao, Z. (2019) · Translational Behavioral Medicine · doi:10.1093/tbm/iby002 · Cited by 97 · see citing works
Commercially Available Mobile Phone Headache Diary Apps: A Systematic Review
Hundert, A. S., Huguet, A., McGrath, P. J., Stinson, J., & Wheaton, M. (2014) · JMIR mhealth and uhealth · doi:10.2196/mhealth.3452 · Cited by 103 · see citing works
Effective strategies for weight loss in post‐partum women: a systematic review and meta‐analysis
Lim, S. S., O'Reilly, S. L., Behrens, H., Skinner, T. C., Ellis, I., & Dunbar, J. (2015) · Obesity Reviews · doi:10.1111/obr.12312 · Cited by 103 · see citing works
Hutchesson, M., Rollo, M. E., Callister, R., & Collins, C. E. (2014) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2014.07.036 · Cited by 102 · see citing works
Measuring diet in the 21st century: use of new technologies
Cade, J. E. (2017) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 102 · see citing works
Self-citationPatient-Driven Diabetes Care of the Future in the Technology Era
Ashrafzadeh, S., & Hamdy, O. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2018.09.005 · Cited by 111 · see citing works
Smartphone Medical Applications for Women’s Health: What Is the Evidence-Base and Feedback?
Derbyshire, E. J., & Dancey, D. (2013) · International Journal of Telemedicine and Applications · doi:10.1155/2013/782074 · Cited by 99 · see citing works
Semper, H., Povey, R. C., & Clark-Carter, D. D. (2016) · Obesity Reviews · doi:10.1111/obr.12428 · Cited by 98 · see citing works
Rangan, A., O'Connor, S., Giannelli, V., Yap, M. L., Tang, L. M., Roy, R., Louie, J. C. Y., Hebden, L., Kay, J., & Allman-Farinelli, M. A. (2015) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4613 · Cited by 94 · see citing works
Ahmed, A. H., Roumani, A. M., Szucs, K., Zhang, L., & King, D. (2016) · Journal of Obstetric, Gynecologic & Neonatal Nursing · doi:10.1016/j.jogn.2015.12.001 · Cited by 86 · see citing works
Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review
Elaheebocus, R., Weal, M. J., Morrison, L. G., & Yardley, L. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8342 · Cited by 93 · see citing works
Patients’ and Nephrologists’ Evaluation of Patient-Facing Smartphone Apps for CKD
Singh, K., Diamantidis, C. J., Ramani, S., Bhavsar, N. A., Mara, P., Warner, J., Rodriguez, J., Wang, T., & Wright-Nunes, J. (2019) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.10370818 · Cited by 79 · see citing works
A systematic review of mHealth interventions for the support of eating disorders
Anastasiadou, D. T., Folkvord, F., & Lupiáñez‐Villanueva, F. (2018) · European Eating Disorders Review · doi:10.1002/erv.2609 · Cited by 87 · see citing works
Vision-Based Approaches for Automatic Food Recognition and Dietary Assessment: A Survey
Subhi, M. A., Ali, S. H. M., & Mohammed, M. A. (2019) · IEEE Access · doi:10.1109/access.2019.2904519 · Cited by 89 · see citing works
A Review of Image-Based Food Recognition and Volume Estimation Artificial Intelligence Systems
Konstantakopoulos, F. S., Georga, E. I., & Fotiadis, D. I. (2023) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2023.3283149 · Cited by 95 · see citing works
Fino, E., & Mazzetti, M. (2018) · Sleep And Breathing · doi:10.1007/s11325-018-1661-3 · Cited by 87 · see citing works
Nutrition Concepts for the Treatment of Obesity in Adults
Wiechert, M., & Holzapfel, C. (2021) · Nutrients · doi:10.3390/nu14010169 · Cited by 95 · see citing works
McCarroll, R., Eyles, H. C., & Mhurchú, C. N. (2017) · Preventive Medicine · doi:10.1016/j.ypmed.2017.08.022 · Cited by 87 · see citing works
Kozak, A. T., Buscemi, J., Hawkins, M. A. W., Wang, M. L., Breland, J. Y., Ross, K. M., & Kommu, A. (2016) · Journal of Behavioral Medicine · doi:10.1007/s10865-016-9805-z · Cited by 84 · see citing works
The SMARTER pilot study: Testing feasibility of real-time feedback for dietary self-monitoring
Burke, L. E., Zheng, Y., Ma, Q., Mancino, J., Loar, I., Music, E., Styn, M. A., Ewing, L. J., French, B. F., Sieworek, D., et al. (2017) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2017.03.017 · Cited by 87 · see citing works
Antoun, J., Itani, H., AlArab, N., & Elsehmawy, A. (2022) · JMIR mhealth and uhealth · doi:10.2196/35479 · Cited by 86 · see citing works
‘I Just Want It to Be Done, Done, Done!’ Food Tracking Apps, Affects, and Agential Capacities
Lupton, D. A. (2018) · Multimodal Technologies and Interaction · doi:10.3390/mti2020029 · Cited by 85 · see citing works
- Authors
- Carter, M. C., Burley, V. J., Nykjaer, C., & Cade, J. E.
- Affiliations
- University of Leeds (GB)
- Corresponding author
- Carter, Michelle Clare
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2013-04-15
- Volume
- 15
- Issue
- 4
- Pages
- e32
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC3636323
- OpenAlex
- W2016679476
- Cited by
- 666
- References
- 40
- Citations by year
- 2026: 20 · 2025: 19 · 2024: 29 · 2023: 30 · 2022: 53 · 2021: 36 · 2020: 66 · 2019: 72 · 2018: 63 · 2017: 76 · 2016: 85 · 2015: 71 · 2014: 40 · 2013: 6
- FWCI
- 121.96
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- Locations
- Journal of Medical Internet Research (publishedVersion, public-domain)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile application, weight loss, obesity, self-monitoring, dietary self-monitoring, paper diaries, intervention adherence, acceptability, feasibility, weight management, goal setting, overweight adults, trial retention, weight change, physical activity, self-guided intervention, information and communication technologies
- MeSH terms
- Adult, Female, Humans, Male, Middle Aged, Obesity, Patient Acceptance of Health Care, Patient Compliance, Pilot Projects, Diet Records, Telemedicine, Internet, Cell Phone, Weight Reduction Programs, Mobile Applications
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