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Obesity is an endemic problem with significant health and financial consequences. Text messaging has been shown to be a simple and effective method of facilitating weight reduction. In addition, waist-to-hip ratio (WHR) has emerged as a significant anthropometric measure. However, few studies have examined the effect of serial anthropometric self-measurement combined with text messaging.
The primary aim of this study was to assess whether an 8-week program, consisting of weekly serial self-measurements of waist and hip circumference, combined with motivational text messages, could reduce WHR among Australian workers.
This was a community-based, participant-blinded, staggered-entry, parallel group study. Adult workers with access to mobile phones were eligible and recruited through an open access Web-based survey. Participants were randomly allocated to receive intervention or control messages for 8 weeks. Outcome data were self-assessed through a Web-based survey.
A total of 60 participants were randomized with 30 participants each allocated to a control and an intervention group. There was no significant change in WHR (
This study is an innovative pilot trial using text messaging and serial anthropometric measurements in weight management. No change was detected in WHRs in Australian workers over 8 weeks; therefore, it could not be concluded whether the intervention affected the primary outcome. However, these results should be interpreted in the context of limited sample size and decreasing intervention uptake over the course of the study. This pilot trial is useful for informing and contributing to the design of future studies and the growing body of literature on serial self-measurements combined with text messaging.
Australian New Zealand Clinical Trials Registry ACTRN12616001496404; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371696&isReview=true (Archived by WebCite at http://www.webcitation.org/73UkKFjSw)
Obesity is an endemic problem worldwide with significant health consequences to the individual [
Exercise is a key element in achieving weight loss goals; however, there are many influences on an individual’s level of exercise, including perceptions of support [
There is no consensus with respect to the most effective text message content. Interventions to increase physical activity and healthy eating vary widely. Despite this, there are few systematic reviews evaluating factors that influence the effectiveness of text message interventions. There is a taxonomy of behavioral change techniques created to improve the effectiveness of interventions aiming at increasing physical activity and healthy eating [
Potential harms of text messaging are generally limited but could potentially depend on the context and frequency of text messages. These might include, for example, perceptions of privacy invasion, and emotional trauma as a result of negative body image. This can be addressed by providing participant information before consent and access to services and resources designed to assist individuals in these issues.
Some reviews found that regular self-weighing was associated with weight loss. Despite variations in the frequency and size of correlation, the association with weight loss was consistent [
The primary aim of this pilot study was to assess whether an 8-week program, consisting of weekly serial self-measurements of waist and hip circumference, combined with motivational text messages, could reduce WHR among Australian workers. Secondary aims were to examine the effects of the program on weight loss, exercise, eating behavior, and work-related well-being measures.
This pilot study evaluated the impact of an 8-week program consisting of motivational text messages and serial anthropomorphic measurements on reducing the WHR, other anthropometric measurements, health behaviors, and occupational health-related outcomes. It was a community-based, participant-blinded, staggered entry, parallel group study with balanced randomization (1:1) conducted in Australia using convenience sampling.
Eligibility criteria were being above 18 years or older, being employed, and having access to a mobile phone in Australia. Exclusion criteria were people receiving weight-altering medications or participating in other weight loss programs. Participants were provided with a participant information sheet providing them with the length of the study, purpose, and affiliations of the study before enrollment into the study. Ethics approval was received from the Western Sydney Human Research Ethics Committee H11327.
Study recruitment ran from October 2016 to January 2017 via a Facebook page, emails to the researchers’ contacts, flyers to public notice boards and local businesses in the Northern Rivers, New South Wales, and information in councils’ newsletters in the Northern Rivers and Western Sydney region. Flyers and emails contained a link to an open a Web-based survey for participant enrollment and baseline data collection. The initial contact with the potential participants was thus made via the internet. Institutional affiliation to Western Sydney University was indicated in our materials. The recruitment materials advertised the study as a weight loss program, but there were no incentives offered to participants and participation was voluntary.
The survey was pretested on 18 volunteers to assess usability and technical functionality. Each participant completed identical baseline surveys, which consisted of 29 items over 7 pages. Items were not randomized or alternated. Adaptive questioning was not used. Only submitted surveys were considered as participant consent to the study. Respondents were able to review and change their answers while completing the survey but not after submission. No participant submitted more than 1 survey. No identifying information was linked to the data. ID numbers were used to analyze the data on password-protected computers.
Participants were randomly assigned to receive intervention or control messages for 8 weeks using a Web-based short message service SMS company. The intervention was a composite of motivational and self-monitoring messages. The 25 motivational messages sent every second day were based on promotion messages from another text-based study regarding nutrition [
Participants were able to opt out of the intervention anytime by texting
Fortnightly control messages were sent with health information from the national guidelines on physical activity, diet, and nutrition [
Participants were followed up with a final Web-based survey 8 weeks after the start of their intervention. Final surveys were identical for all participants except for those completing it after Jan 23, 2017, when 2 open-ended questions were added to gather a more in-depth understanding about the pilot study. The final survey consisted of 23 items over 5 pages. Reminder emails and text messages were sent a week and a fortnight after completion. Two sets of participants were asked to complete the final survey outside of this protocol as a result of researcher error. This affected 10 participants; 6 participants were able to complete the survey 3 weeks after program completion instead of 2 weeks, whereas 4 participants were invited to complete the final survey 2 weeks before the completion of their intervention.
Outcome data was self-assessed and collected on the Web using SurveyMonkey at the beginning and end of the study. Questions were mainly derived from existing scales. The invitation to the final survey was sent in the last text message and email.
The primary outcome was WHR change from baseline to 8 weeks collected by participants measuring their waist and hip circumference in centimeters with help from instructive pictures and videos. Secondary outcomes were changes in anthropometric measurements, health behaviors, and occupational health-related outcomes. Self-reported health was measured with the global health question from the Short Form-36 (
Process measures were also assessed to measure levels of engagement and intervention uptake. These were as follows:
The number of replies the intervention group made to the weekly request messages for self-measurement
The time between finishing the study and completing the final survey
In addition, to elicit feedback on the program, the following 2 open-ended questions were added:
Do you feel that taking part in the study made you live or feel healthier? Can you explain?
Do you have any further comments on the program?
To detect a difference in our participants’ WHR of 0.03 with a 5% significance level and assuming an SD of 0.064, 72 participants per group were required to provide the study with a power of 80%. However, our study included 30 participants at baseline per group because of unexpected difficulties in recruitment.
Participants were randomized in blocks of 10 to intervention or control through a computer-generated random number list on Excel created by a researcher (SWP) not involved in allocation. All other researchers were involved in allocation. Although there was no allocation concealment, enrollment of the participants occurred automatically during the baseline survey with no direct contact from the researchers.
Participants were allocated an ID number based on the order in which they completed the baseline survey. They were allocated to control or intervention on the Sunday after enrollment and started the intervention on the Monday in either the intervention or control group.
Data analysts and researchers undertaking randomization were not blinded during the trial; however, there was no direct contact between participants and researchers throughout the entirety of the trial, and ID numbers were used for participant anonymity during analysis. Participants were blinded to group allocation by concealing the frequency and content of text messages.
Baseline descriptive analyses examined variable distribution for sample characteristics. Continuous variables were presented as mean and SDs, and nonparametric data as median and interquartile ranges. Binomial and categorical variables were reported as proportions. Statistical analyses were performed on SPSS Version 22.0 (SPSS Inc, Chicago, IL, USA) and SAS version 9.4 (SAS Institute, Cary, NC, USA).
This study recruited members between October 2016 and January 2017. There were 9 weekly sets of participants who entered the trial throughout this recruitment period, with the final set of participants completing the intervention in March 2017. Participant numbers each week varied from 1 to 18. The trial was ended as per the scheduled date of closure. The participant flow is summarized in
Participant flowchart.
A total of 55 participants entered the trial, 33 completed the trial and were included in the final analyses. Baseline characteristics appear to vary between the intervention and control group (
Of the 60 participants randomized, 5 participants were randomized in error (3 intervention and 2 control group participants), 5 participants withdrew during the program and 22 participants were lost to follow-up (ee
Baseline participant characteristics.
Characteristics | Intervention (n=23) | Control (n=27) | Total (n=50) | |
Age (years), median (Q1, Q3) | 45 (30, 53) | 33 (25, 46) | 38 (27,51) | |
Female, n (%) | 19 (83) | 23 (85) | 42 (84) | |
Hours spent doing paid work, median (Q1, Q3) | 32 (20, 40) | 35 (30, 40) | 33.5 (24, 40) | |
In a relationship or married or engaged or de factoa | 11 (50) | 14 (52) | 25 (51) | |
Single or divorced or widowed or separateda | 11 (50) | 13 (48) | 24 (49) | |
Height, cmb, mean (SD) | 164.9 (8.3) | 166.0 (9.2) | 165.5 (8.7) | |
Weight, kgb, mean (SD) | 76.9 (20.4) | 69.9 (21.4) | 73.2 (21.0) | |
Body mass indexb, kg/m2, mean (SD) | 28.2 (6.7) | 25.1 (6.1) | 26.6 (6.5) | |
Overweight statusb, n (%) | 11 (52) | 9 (39) | 20 (45.5) | |
Waist circumference, cmc, mean (SD) | 89.4 (16.1) | 80.4 (17.2) | 85 (17.0) | |
Hip circumference, cmc, mean (SD) | 106.1 (13.4) | 95.7 (13.5) | 101.0 (14.3) | |
Waist-to-hip ratioc, mean (SD) | 0.84 (0.08) | 0.84 (0.10) | 0.83 (0.09) | |
Number of serves of cooked vegetables, median (Q1, Q3) | 2 (1, 3) | 1 (1, 2) | 2 (1, 3) | |
Number of serves of raw vegetables, median (Q1, Q3) | 1 (1, 1) | 2 (1, 2) | 1 (1, 2) | |
Met vegetables requirement [ |
4 (18) | 5 (19) | 9 (18) | |
Number of serves of fruit, median (Q1, Q3) | 2 (1, 2) | 1 (1, 2) | 1 (1, 2) | |
Number of glasses of fruit juiced, median (Q1, Q3) | 0 (0, 0) | 0 (0, 0) | 0 (0, 0) | |
Met fruit requirement [ |
12 (55) | 13 (48) | 25 (51) | |
Hours spent sitting per day, mean (SD)e | 8 (7, 10) | 8 (6, 12) | 8 (7, 10) | |
Mild physical activity per week (min)f, median (Q1, Q3) | 60 (14, 240) | 60 (10, 120) | 60 (10, 180) | |
Moderate physical activity per/week (min)g, median (Q1, Q3) | 60 (10, 180) | 30 (20, 60) | 60 (10, 120) | |
Vigorous physical activity per/week (min)h, median (Q1, Q3) | 2 (0, 60) | 20 (0, 60) | 7 (0, 60) | |
Proportion meeting physical activity guidelines [ |
12 (55) | 14 (52) | 26 (53) | |
Accountability partner, n (%) | 6 (27) | 7 (26) | 13 (27) |
an=49 (control: 27 vs intervention: 22)
bn=44 (intervention: 21 vs control: 23).
cn=39 (intervention: 20 vs control: 19).
dn=47 (intervention: 20 vs control: 27).
en=50.
fn=47 (intervention: 21 vs control: 26).
gn=46 (intervention: 21 vs control: 25).
hn=48 (intervention: 21 vs control: 27).
Baseline occupational health-related outcomes.
Outcomes | Intervention (n=23) | Control (n=27) | Total (n=50) | |
General health, n (%)a | ||||
Excellent or very good | 6 (27) | 8 (31) | 14 (29) | |
Good | 10 (46) | 13 (50) | 23 (48) | |
Fair or poor | 6 (27) | 5 (19) | 11 (23) | |
Work ability lifetime best (0 to 10), median (Q1, Q3) | 8 (7, 9) | 8 (7, 9) | 8 (7, 9) | |
Work ability mental demands, n (%) | ||||
Very good | 3 (14) | 7 (26) | 10 (20) | |
Rather good | 12 (55) | 14 (52) | 26 (53) | |
Moderate or rather poor or very poor | 7 (32) | 6 (22) | 13 (27) | |
Work ability physical demands, n (%) | ||||
Very good, n (%) | 9 (41) | 14 (52) | 23 (47) | |
Rather good, n (%) | 10 (46) | 10 (37) | 20 (41) | |
Moderate or rather poor or very poor, n (%) | 3 (14) | 3 (11) | 6 (12) | |
Productivity (0 to 10), median (Q1, Q3) | 7 (6, 8) | 8 (6, 9) | 7 (6, 8) | |
Burnout Score (0 to 10), mean (SD) | 4.8 (2.6) | 4.7 (2.6) | 4.8 (2. 7) | |
Maslach burnout inventory—emotional exhaustion, mean (SD) | 31.0 (13.6) | 30.4 (11.5) | 30.7(12.4) |
an=48 (intervention: 22 vs control: 26).
Comparison between control group and intervention group anthropometric measures and work-related health.
Outcomes | Intervention | Control | Time effect | Group × time effect | Group effect | ||||
Baseline, mean (SE) | At 8 weeks, mean (SE) | Baseline, mean (SE) | At 8 weeks, mean (SE) | ||||||
Waist-to-hip ratio | 0.84 (0.02) | 0.86(0.02) | 0.83(0.02) | 0.82(0.03) | .68 | .30 | .43 | ||
Body mass index (kg/m2) | 28.25 (1.34) | 28.14 (1.34) | 25.11 (1.29) | 25.26 (1.29) | .85 | .22 | .12 | ||
Waist circumference (cm) | 89.95 (3.73) | 90.28 (3.83) | 80.76 (3.88) | 77.00 (4.26) | .45 | .36 | .04 | ||
Hip circumference (cm) | 107.08 (3.24) | 104.12 (3.34) | 96.39 (3.36) | 93.31 (3.76) | .17 | .97 | .02 | ||
Burnout score (0 to 10) | 4.81 (0.57) | 3.11 (0.63) | 4.77 (0.52) | 3.60 (0.67) | .004 | .57 | .75 | ||
Maslach burnout inventory—emotional exhaustion | 25.50 (2.72) | 30.82 (2.74) | 30.37 (2.37) | 31.00 (2.62) | .08 | .11 | .39 | ||
Work ability (0 to 10) | 7.91 (0.36) | 7.65 (0.45) | 8.11 (0.32) | 8.31 (0.41) | .91 | .41 | .35 | ||
Productivity (0 to 10) | 7.18 (0.39) | 6.65 (0.45) | 7.25 (0.35) | 7.92 (0.47) | .86 | .15 | .14 |
The changes in anthropometric measures and work-related health are summarized in
Comparison between control group and intervention group for health behaviors, representing the number (%) of participants that reported changes in health behaviors from baseline to 8-week follow-up.
Health behaviors | Less, n (%) | Same, n (%) | More, n (%) | ||
Intervention | 4 (24) | 10 (59) | 3 (18) | .26 | |
Control | 2 (13) | 6 (40) | 7 (47) | —a | |
Intervention | 0 (0) | 7 (39) | 11 (61) | .08 | |
Control | 3 (20) | 7 (47) | 5 (33) | — | |
Intervention | 2 (11) | 10 (56) | 6 (33) | .41 | |
Control | 0 (0) | 7 (47) | 8 (53) | — | |
Intervention | 1 (6) | 14 (88) | 1 (6) | .79 | |
Control | 1 (7) | 12 (80) | 2 (13) | — | |
Intervention | 6 (33) | 3 (17) | 9 (50) | .38 | |
Control | 6 (40) | 0 (0) | 9 (60) | — | |
Intervention | 6 (33) | 3 (17) | 9 (50) | .63 | |
Control | 7 (40) | 2 (0) | 8 (60) | — |
aNot applicable.
No statistically significant differences were detected for health behaviors between the 2 groups (
The pattern of intervention uptake is shown in
A total of 15 people responded to the qualitative question (intervention=8 vs control=7).
A total of 11 participants felt that the study did not make them live or feel healthier and had
...
In total, 5 of 8 participants who responded commented that the study did not make them live or feel healthier. They commented:
Unfortunately no. Although I found the texts very informative, I didn’t make an effort to put them into practice
No, not really. The texts were too easy for me to ignore, or forget about. I’m not in the habit of checking my phone regularly
In total, 3 participants thought the intervention had a positive impact, for example:
Yes as I thought about my health more often
It has been positive to have daily texts and reminders even if I took little action from them
In total, 6 of 7 responses were negative. Some felt that:
...it would have been better to have more frequent texts
I don’t know think one quick fact every couple of weeks can change a whole attitude. For me, it requires more regular reminders and having someone like an accountability partner who can follow you up often works best
In total, 1 had a positive response to the study:
yes it was a good reminder to eat healthy and exercise
No significant changes over time were found between the WHR of the intervention and control group over time. Single item burnout showed a significant decrease over time. No weight gain or other anthropometric measurements, health behaviors, and occupational health measures showed significant changes over time.
A number of mechanisms might account for the results of this study. First, the study ran over the holiday season in Australia, which is traditionally a time in which individuals gain weight [
The decrease in burnout independent of allocation might similarly be a reflection of upcoming major holidays. There is little evidence to suggest that upcoming holidays decrease burnout; however, a study found that if an individual had a trip planned for their holiday time, they were more likely to report being happier [
The diversity of interventions makes direct numerical comparisons difficult in technological weight loss studies. However, text messaging use for reminders, such as those we used to induce self-monitoring or to promote behavior change, does have an evidence basis. One systematic review found that although a relatively new area of research, text messaging as a lifestyle intervention was promising in its feasibility and acceptability [
Burnout reduction using text messages among workers has, to the researchers’ knowledge, never been investigated before in a randomized controlled trial (RCT) setting. This suggests that this maybe an area of further research to further explore its impact given that it significantly reduced overtime in both groups. This might have been a type 2 error though. Other intervention studies have tested the efficacy of guided Web-based and mobile-based stress management training for employees and found that emotional exhaustion was reduced in the intervention group [
This study had several limitations which must be considered when reviewing the results and in the development of future research. The restricted recruitment time limited the number of participants and contributed to a low power. Participant enrollment in the study was also limited by access to tools such as a tape measure. However, we compensated for this by the provision of videos explaining how to use string and a ruler to measure WHR. Another limitation of this study was the differing baseline characteristics between groups. The intervention group had a higher proportion of overweight and obese BMIs than the control group (52% vs 39%), a higher weight (76.9 kg vs 69.9 kg), and a wider hip circumference (106.1 cm vs 95.7 cm) in baseline characteristics. Furthermore, there was a significant difference between the waist and hip measurements averaged over time for the 2 groups, with the intervention group having significantly greater waist and hip measurements (
Although our lost to follow-up rates were relatively high 40% (22/55), a review focusing on Web-based weight loss interventions showed most had an attrition rate that was higher [
Another reason for the unequal attrition rates was suggested by 1 study that examined the reasons behind dropout [
All partial completers of the final survey (n=5) dropped out when asked to provide their weight and waist and hip circumference. It might be useful for future studies to consider placing questions known to lead to low response rates at the end of the survey. However, in our case, it was the primary outcome measure, so in future trials other methods of collecting weight and WHR data might need to be considered to ensure valid and complete data are collected.
Process measures to test engagement in the study were used to assist with the development of further research into this area. Follow-up response times were a part of these, and we found the intervention group had a shorter response time than the control group (mean days [SD]: 3.17 [3.50] vs 8.80 [6.27]). This presents an important aspect to consider when running similar trials in the future as it suggests that altering the content rather than the frequency of the messages between the groups might be a more effective option.
The other process measure of this study was the replies from the intervention group to the request messages. Serial self-measurement was a key intervention in this study, and strong uptake would be needed to measure its efficacy. However, replies to these messages were shown to decrease over time, revealing a decreasing level of engagement. Reasons for this could be similar to reasons for lost to follow-up events as discussed previously. This decreasing intervention uptake might have contributed to our negative findings and should be considered when interpreting results.
Some aspects of this study limit its application to the wider Australian context. First, 84% of the population was female, which, although a common problem with many weight loss studies [
This study also had a limited, primarily young, age range. This might be because of the nature of our recruitment via social media and by restricting this study population to workers. Younger participants might also feel more comfortable participating in a study involving a relatively new aspect of technology. Another study limitation is selfreported measurements. We included several strategies for accuracy for the primary outcome measure. First, before starting the survey, we advised people we would ask them to measure their waist and hip and asked them to be in a comfortable place to measure themselves. Second, we showed them a picture and a video during the Web-based survey on how to measure hip and waist circumference to assist people in completing their measurements. Nonetheless, it is likely that some people will have estimated their hip and waist circumference, which might have biased the results. Secondary outcome measures were mainly based on validated scales for work ability [
This study is an innovative pilot trial using text messaging and serial self-measurement in weight management. The results did not detect a change in WHR ratio in Australian workers over 8 weeks. However, these results should be interpreted in the context of limited sample size and decreasing intervention uptake over the course of the study. We are unable to conclude this intervention is not effective. A larger sample would be necessary to see if the combination of these interventions is effective. The findings around study design and participant interaction with the interventions are useful for informing and contributing to the design of future studies and the growing body of literature on serial self-measurements combined with text messaging.
Text messages.
Process measures.
CONSORT-EHEALTH checklist (V 1.6.1).
body mass index
randomized controlled trial
waist-to-hip ratio
This study was self-funded. The research team would like to thank Western Sydney University and the University Centre for Rural Health for their practical support. The authors also thank all the study participants.
None declared.