The Efficacy of a Technology‐based System in a Short‐term Behavioral Weight Loss Intervention
Open accessAbstract
Objective: The objective was to examine the efficacy of adding a technology‐based program to an in‐person, behavioral weight loss intervention. Research Methods and Procedures: Fifty‐seven subjects (BMI = 33.1 ± 2.8 kg/m 2; age = 41.3 ± 8.7 years) participated in a 12‐week intervention with random assignment to Standard In‐Person Behavioral Weight Control Program (SBWP) or Intermittent or Continuous Technology‐Based Program (INT‐TECH, CON‐TECH). SBWP subjects received seven individualized weight loss sessions encouraging dietary and exercise modifications. INT‐TECH and CON‐TECH subjects received all SBWP components; additionally, these groups used a SenseWear Pro Armband (BodyMedia, Inc.) to monitor energy expenditure and an Internet‐based program to monitor eating behaviors. These features were used by INT‐TECH subjects during weeks 1, 5, and 9 and CON‐TECH subjects weekly throughout the intervention. Results: Intent‐to‐treat analysis revealed weight loss of 4.1 ± 2.8 kg, 3.4 ± 3.4 kg, and 6.2 ± 4.0 kg, for SBWP, INT‐TECH, and CON‐TECH groups, respectively (CON‐TECH > INT‐TECH, p ≤ 0.05). Discussion: These results indicate that the technology‐based program needs to be used continuously throughout the intervention period to significantly impact weight loss. Future studies should examine the long‐term and independent effect of this technology on weight loss, and for whom this intervention format is most effective.
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Two of the included studies reported a significant increase in daily steps, four reported a significant increase in MVPA, and two reported a significant increase in energy expenditure for the intervention group compared with control.
“Two of the included studies [34,44] reported a significant increase in daily steps, 4 studies [30,34,36,53] reported a significant increase in MVPA, and 2 studies [45,47] reported a significant increase in energy expenditure for the intervention group compared with control.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [45]
The relevant part of the citing sentence attributes an increase in energy expenditure relative to control to this study. In “Change in LTPA and Dietary Intake” (page unavailable), the paper reports that leisure-time physical activity, measured in kcal/week, increased within all three groups, but that differences between groups were not statistically significant. It therefore does not support the claimed significant intervention-versus-control increase. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredBlinding of outcome assessors (detection bias) was assessed as high risk for 7 studies [31,43,45-48,52] because of the use of subjective outcome measures.
“Blinding of outcome assessors (detection bias) was assessed as high risk for 7 studies [31,43,45-48,52] because of the use of subjective outcome measures.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [45]
The Assessments section (page unavailable) describes self-reported physical activity and questionnaire-based dietary intake, supporting the presence of subjective measures. It also says body weight was measured with a calibrated scale. The paper does not itself assess outcome-assessor blinding or classify the study as high risk of detection bias; that classification is the citing authors’ judgment. (LLM, conf=0.82)
Experimental — accuracy not yet measured4 studies reported low activity tracker wear time, with 1 study reporting that all participants had ceased wearing their activity tracker by the end of the intervention.
“Furthermore, 4 studies [32,37,38,45] reported low activity tracker wear time, with 1 study [32] reporting that all participants had ceased wearing their activity tracker by the end of the intervention.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [45]
The Analysis of Process Measures reports that armband time on body decreased during the intervention in the CON-TECH group, supporting a decline in wear time. Table 2 (shown under Discussion) reports nonzero wear time across weeks 9–12, but neither passage establishes that all participants had stopped wearing the tracker by the intervention’s end. This paper alone also cannot substantiate the count of four studies. (LLM, conf=0.86)
Experimental — accuracy not yet measured3 studies required participants to be proficient at using the internet and/or smartphones.
“with 3 studies requiring participants to be proficient at using the internet and/or smartphones [21,22,45].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [45]
8 studies included more than 1 intervention group.
“Overall, 8 studies included more than 1 intervention group [34,43,45-47,52-54].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [45]
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“…technology in a clinical trial of behavioral weight loss in a face-to-face intervention has previously been documented in the work of Polzien et al [46], who reported additional weight loss at 12 weeks of 2.1 kg in the group that had technological support; these data approximate those obtained in…”
InfluentialUtilizing wearable technology to increase physical activity in future physicians: A randomized trial
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“Only 4 of 7 studies were deemed effective with a mean weight loss ≥5% [24-28].”
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“For example, the use of a wearable device in a group weight management treatment led to lower long-term weight loss outcomes compared to participants that did not receive a device (Polzien et al., 2007).”
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“Furthermore, technology devices have been effective when used to monitor dietary intake and energy expenditure for weight loss programs (Polzien et al., 2007).”
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“This study, consistent with related research, found no evidence to suggest that a negative response to data sharing occurred (9,12,13,21).”
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State of Technology in Aging Services
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“Moreover, this finding is in accordance with previous studies utilizing this technology in less obese individuals which reported an additional 2% weight loss in SBWL+TECH compared to SBWL [10, 14].”
ResultA PROGRAMME TO ENCOURAGE PARTICIPATION OF HAEMODIALYSIS PATIENTS IN AN EXERCISE REGIMEN
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Self-Powered Wearable IoT Devices for Health and Activity Monitoring
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- Authors
- Polzien, K. M., Jakicic, J. M., Tate, D. F., & Otto, A. D.
- Affiliations
- University of Pittsburgh (US)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Jakicic, John M.
- Venue
- Obesity
- Publisher
- Wiley
- Published
- 2007-04
- Volume
- 15
- Issue
- 4
- Pages
- 825-830
- ISSN
- 1930-7381 (ISSN-L)
- 1930-739X
- OpenAlex
- W2072088591
- Cited by
- 154
- References
- 16
- Citations by year
- 2026: 2 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 6 · 2020: 9 · 2019: 9 · 2018: 10 · 2017: 7 · 2016: 7 · 2015: 12 · 2014: 10 · 2013: 14 · 2012: 15
- FWCI
- 18.36
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Obesity (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Keywords
- weight loss, behavioral weight control, technology-based interventions, dietary change, exercise modification, overweight adults
- MeSH terms
- Adolescent, Adult, Behavior Therapy, Body Weight, Diet, Reducing, Feeding Behavior, Female, Humans, Male, Middle Aged, Technology, Weight Loss, Exercise, Body Mass Index, Monitoring, Ambulatory, Internet
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