Use of Technology-Based Interventions in the Treatment of Patients with Overweight and Obesity: A Systematic Review

Introduction: Obesity is one of the most important health problems worldwide. The prevalence of obesity has increased dramatically in the last decades and is now recognized as a global epidemic. Given the dramatic consequences of obesity, new intervention approaches based on the potential of technologies have been developed. Methods: We conducted a systematic review of studies using PubMed, ScienceDirect, Cochrane Library, and MedLine databases to assess how different types of technologies may play an important role on weight loss in obese patients. Results: Forty-seven studies using different types of technologies including smartphones, app, websites, virtual reality and personal digital assistant were included in the review. About half of interventions (47%) found a significant effect of the technology-based interventions for weight lost in obese patients. The provision of feedback could also be effective as a complement to interventions carried out using technology to promote weight loss. Conclusions: The use of technologies can be effective to increase weight loss in patients with obesity improving treatment adherence through self-monitoring.


Introduction
Obesity has been defined by the World Health Organization as an abnormal or excessive accumulation of fat that poses a health risk, considered as the "epidemic of the 21st century" [1]. Obesity is one of the most important health problems, both in developed and developing countries, due to its prevalence, costs, and health effects [2]. Currently, it is accepted as a chronic and progressive disease with a high morbidity and mortality due to the likelihood of suffering comorbidities, social problems, and poor quality of life [3].
The prevalence of obesity has almost doubled worldwide over the past three decades [4]. Between 1975 and 2014, the prevalence of obesity increased from 3.2% to 10.8% in adult men, and from 6.4% to 14.9% in adult women [5].
One of the countries with the highest prevalence of obesity is the United States. This prevalence there among adults over 20 years of age is approximately 36%, with a breakdown of 38.3% for women, and 34.3% for men [4,6]. As for Spain, the prevalence of obesity among people aged 25 to 64, according to the 2014 and 2015 data from the Spanish Population Nutrition Study (ENPE), is 21.6%, and higher in men than in women, 22.8% and 20.5%, respectively [7]. Moreover, in Spain, there were around 24 million cases of overweight or obesity in 2016, that is, 70% of the adult population and three million

Methodology and Quality Assessment
This study uses a systematic review methodology, based on the PRISMA statement. The quality of each primary study was assessed with the Cochrane Collaboration Risk of Bias (ROB) tool [20], which includes seven items covering six domains of bias. Each item is judged as having a high, low, or unclear ROB. A summary assessment is calculated based on the number of items assessed as high, low, and unclear ROB. Besides the standard summary assessment of ROB for each primary study, a summary assessment of ROB was calculated without the items related to blinding of assessor.
The first and second authors from paper rated each included article independently, and discrepancies were resolved by agreement with the third author. The Cohen's Kappa statistic was calculated to assess interrater reliability for the ROB without items assessing blinding of participants or assessors, as all studies were rated as high ROB by the two raters when all the items were analysed.
The Cohen's Kappa statistic was calculated to assess interrater reliability for the ROB without items assessing blinding of participants or assessors. The results showed an agreement between two raters between 0.6 to 0.85.

Data Sources
The systematic search was carried out in the PubMed, ScienceDirect, Cochrane Library, and MedLine databases. Additional articles were identified by searching the references of another article.

Search Strategy
The search strategy aimed to identify the published studies available in full text. A bulk search strategy was used, using both the MeSH descriptors and terms in the titles or abstracts, which were as follows: "virtual reality exposure therapy", "virtual reality", "virtual world", "virtual environment", "3D vision", "smartphone", "cell phone", "technology", "obesity", "overweight", "diet therapy", and "weight loss" joined by Boolean operators (AND, OR) as follows: (virtual reality exposure therapy OR virtual reality OR virtual world OR virtual environment OR 3D vision OR smartphone OR cell phone OR technology) AND (obesity OR overweight) AND (diet therapy OR weight loss). The date of the last search was 26 February 2020, and no time restrictions were made about the year of publication of the studies. Table 1 shows the search strategy used in the Pubmed database.

Selection of Articles
Abstracts identified through the bibliographic search were independently evaluated by two authors to confirm the inclusion criteria. The quality of each study was independently evaluated by two authors, using the Crombie criteria adapted by Petticrew and Roberts [21]. Disagreements were resolved by a third author.

Inclusion and Exclusion Criteria
Inclusion criteria were: (I) articles that were available in full text and written in English or Spanish; (II) articles whose participants were 18 years of age or older, overweight or obese; (III) articles that presented at least two groups for comparison, one of them with a weight management intervention through some type of technology; and (IV) articles in which the weight was reported with a numerical value before, during, and/or after the intervention.
The exclusion criteria were: (I) articles not related to the subject of the study or articles that were protocols of intervention without results; (II) articles that were reviews or meta-analyses; (III) documents that were summaries for conferences; and (IV) presence of major pathologies such as mental illnesses, eating disorders, and cancer.

Type of Technology and Provision of Feedback
As for whether or not feedback was available (i.e., whether or not participants received some kind of response, either via email, short text message or SMS, or phone call), only one study did not present this aspect [22].

Virtual Reality
Four studies (Table 3) included an intervention based on the potential of virtual reality techniques, using 3D avatars (Second Life or similar ones) [12,15,46,47]. Two of the four articles did not provide feedback [15,47].

Website
In 4 articles, the intervention was carried out with the help of a website; two of them used it to monitor dietary intake, weight, and/or physical activity [50,51]. One article used it for video-conferences [31] and another study, in addition to using a website, used a pedometer [48] (Table 3). All of them provided feedback.

Personal Digital Assistant (PDA) or Electronic Journal (EJ)
Four articles used a (PDA) or an electronic journal (EJ) to monitor dietary intake, weight, and/or physical activity, and all of them provided feedback [52][53][54][55].

Other Types of Technology
Seven of the articles analyzed used a different type of technology. Of these seven, three articles used a physical activity monitor [56][57][58], two of them used online software [59,60], one study used DVDs [61], and the last one used Facebook, an App, text messages, emails, a website, and technology-mediated communication with a health coach [62]. Of these articles, only one of them did not provide feedback [41].   Six of the articles that used or supplemented the intervention with an App exclusively or together with some physical activity monitor, reported evidence of weight loss compared to the control or comparison groups (Table 4) [28] (p < 0.05); [11] (p < 0.05); [31](p < 0.001); [17] (p = 0.042); [26] (p = 0.026); [41] (p < 0.05). In He et al.'s work. [22], the differences were significant for men (p < 0.001) but not for women. In contrast, in five articles, the control or comparison groups lost more weight, but the differences did not reach significance in any of them [16] (p = 0.19); [47] (p = n.s); [34] (p = 0.0997); [23] (p = n.s); [24] (p > 0.05) Finally, in one study, both groups lost about 2.6 kg (p = 0.88) [27]. The average weight lost by the App groups was 3.82 kg, with 7.9 kg and 0.03 kg, respectively, the highest and lowest average amounts lost.
In seven articles, adherence was greater in the groups that used or complemented the intervention with an App, with significant differences in three of them [32] (p < 0.001); [17] (p < 0.05); [23] (p < 0.001). In Spring et al.'s work [23], adherence to self-monitoring contributed to weight loss (r (84) = 0.36-0.51, p < 0.001) and in that of Ross and Wing. [17], the percentage change in weight was significantly associated with adherence to intake control (r = −0.48, p < 0.001) and weight (r = −0.42, p = 0.085). Only in the work of Rogers et al. [34], the standard group monitored their diet for a longer average number of days than the technology groups.
As for adherence, two of the studies reported the existence of an association between increased adherence and greater weight loss [37,38]. In contrast, in another study, weight loss at 6 months did not correlate with the total of the follow-up days (r = 0.14, p = 0.27) [43]. In four studies, it was noted that despite the inclusion of technology, adherence decreased over time [40,42,44,45]. For example, in one study, it was 66% at the start of the intervention and 52% at the end of the intervention [42]. Table 4 shows two studies where groups that used virtual reality lost more weight, with significant group differences in one of them [47] (p = 0.04). On the other hand, in two articles [12,46], the control groups lost more weight, and the differences were significant in one of them [46] (p < 0.05). However, in this same study [46], weight maintenance was significantly higher in the virtual reality group (14% vs. 9.5%, p < 0.05). Manzoni et al. [12] stated that the virtual reality group was more likely to further maintain or improve weight loss at a one-year follow-up. Groups that used virtual reality lost an average of 4.7 kg, with 7.3 kg and 0.79 kg being the highest and lowest average amounts lost. Table 4 shows that all groups that used a website lost significantly more weight than the control or comparison groups [48] (p < 0.001); [50] (p = 0.001); [49] (p = 0.0002), except for one group where the differences did not reach significance [51] (p = 0.408). The average weight loss was 3.75 kg, with 5.3 kg and 1.4 kg being the highest and lowest weight amounts lost by the groups that used a website. Table 4. Results of the intervention regarding changes in weight and adherence.

Authors, Year. [Reference]
Weight Results

Adherence Results
He et al., 2017 [22] Weight loss: the control group lost (−1.78 kg) and the intervention group (−2.09 kg). -Significant weight loss at 6 months for men, but not for women (p < 0.001). Men in WeChat group: higher probability of maintaining weight, Weight loss of 1 to 2 kg or Weight loss 1 of more than 2 kg than the control group.
Adherence to self-monitoring: larger in App group than in standard (p < 0.001) and it covaried with weight loss (r(84) = 0.36-0.51, p < 0.001). Correlations did not differ depending on the treatment condition. No significant differences between technology group and self-group (control). Adherence to self-monitoring: greater in Tech + Phone group than in Tech and standard (p < 0.05), and standard group showed lower adherence. In both technology groups: Significant association between the percentage change in weight and adherence to intake control (r = −0.48, p < 0.001) and weight (r = −0.42, p = 0.002). No association between adherence to the use of the activity monitor and weight change (p = 0.085).
Apiñaniz et al., 2019 [13] No significant group differences in weight (0.357 kg, p = 0.7).   Weight, changes from the start: Adherence was significantly higher in the App group (92 days) compared to the web group (35 days), and the paper group (29 days). (p < 0.001). No significant differences between App group and paper diary group (p = 0.12) Hernández-Reyes et al., 2020 [33] Weight loss: intervention group lost (−7.9 kg), and the control group lost (−7.1 kg).

Authors, Year. [Reference]
Weight Results
The standard group monitored their diet an average of 84.6 days, the technology group 80.0 days, and the enhanced technology group 70.1 days. No significant group differences (p = 0.0997).

Lewis et al., 2019 [36]
Participants who started the intervention achieved significant decreases in: weight (−4.87 kg) at 4 months, maintaining these losses after switching to the control group. The addition of telephone and texting support to a community obesity management program improved behavioral adherence compared to standard care. In participants who started the control group, no significant changes were observed at 4 months. After the intervention, significant reductions were achieved in: weight (−2.76 kg), at 8 months. Significant group differences (p = 0.01) Steinberg et al., 2013 [37] Changes in weight: Control group participants gained an average of 1.14 kg, while intervention group lost an average of 1.27 kg.
Trend towards greater adherence to text messages associated with a higher percentage of weight loss (r = −0.36, p = 0.08), but this did not reach statistical significance. Significant group differences (p = 0.09) Shapiro et al., 2012 [38] Weight loss 12 months later: control group (−2.27 lb) and intervention group (−3.64 lb); control group lost an average of 0.8% of the weight, and the intervention group 1.8%.

Godino et al., 2019 [40]
Weight loss 12 months later: control group (−.61%), SMS group (−1.6%), and SMS+Coaching group (−3.63%). The median of the average daily commitment rate decreased slightly over time: 28.69 at 6 months and 24.91 at 12 months. A unit increase in the average percentage of daily participation throughout the study was associated with a higher percentage of weight loss (−0.08%, p < 0.05).
At 12 months, Weight loss the average percentage, adjusted for baseline BMI, was significantly different between SMS + coaching and the control group −3.0, but not between SMS alone and the control group −1.07; (p = 0.291).

Newton et al., 2018 [41]
Weight loss: intervention group lost (−1.4 kg), and the control group gained (0.2 kg). The correlation between the number of SMS text messages sent and the change in weight loss was not statistically significant. Significant group difference in the Weight loss (p = 0.03). Table 4. Cont.

Authors, Year. [Reference]
Weight Results

Adherence Results
Bouhaidar et al., 2013 [42] Weight loss: intervention group lost (−5.96 lb) and the control group (−1.41 lb). At the beginning of the intervention, participants' response rate to SMS requests was 66%. This percentage decreased to 52% at the end of the intervention. Significant group differences (no p-value is specified).
Lin et al., 2014 [43] Weight changes at 6 months: g. intervention lost (−1.6 kg) and control group gained (+0.24 kg), with a group difference of 1.83 kg. Significant group differences (p < 0.0001) No significant correlation between weight loss at 6 months and total follow-up days (r = 0.14, p = 0.27), nor did it correlate significantly with the average percentage of follow-up days (r = 0.14, p = 0.27).

Haapala et al., 2009 [44]
Weight loss at 12 months, the intervention group lost (−4.5 kg), and the control group (−1.1 kg) The overall frequency of use of the program decreased from 8 times per week to 3-4 times per week in 12 months. Those with more than 5% weight loss at 12 months reported more frequent weekly contact at 3 months than those who had lost less than 5%. Significant group differences (p = 0.006). Weight loss: the face-to-face group lost (−1.8%), and the virtual reality group (−7.6%). -Significant group differences (p < 0.05). Weight maintenance: virtual reality group (14%) compared to face-to-face group (9.5%). Significant group differences (p < 0.05). Weight loss: virtual world group (−3.9 kg) and face-to-face group (−2.8 kg).
-No significant group differences (p > 0.05) The RV group is more likely to maintain or further improve weight loss at the 1-year follow-up than the SBP group (48% vs. 11%; p = 0.004) and than the CBT group (48% vs. 29%; p = 08). Table 4. Cont.

Authors, Year. [Reference]
Weight Results
Significant differences between the two intervention groups with technology and the control group (p < 0.001) but no significant differences in the intervention groups (p > 0.05).

Azar et al., 2015 [49]
Weight loss: the intervention group lost (−3.6 kg), and the control group (−0.4 kg). Intervention group lost on average 3.2 kg more than the control group.
While not statistically significant, the downward slope of both the assistance/weight loss and self-monitoring/weight loss curves suggests a weight loss trend with greater participation. Significant group differences (p = 0.0002). Weight loss 24 months later: the PDA+FEEDBACK group lost (−2.17 kg), the paper group lost (−1.77 kg), and the PDA group lost (−1.18 kg).
Significant differences between PDA and PDA + Feedback groups and paper group (p = 0.03). No significant differences between PDA + Feedback groups and PDA group (p = 0.49). A higher proportion of the PDA groups, compared to the paper group was adherent 60% or more of the time (PDA + Feedback vs. paper, p = 0.01) and (PDA vs. paper, p = 0.03).
18 months: 19−20% of PDA groups remained adherent 30% or more of the time, compared to 8% of the paper group. No significant group differences (p = 0.33). Compared to paper register, the PDA to control diet (p = 0.027) and PA (p = 0.014) had significant direct effects on weight loss at 12 months. And a significant indirect effect on results through better adherence to self-monitoring (p < 0.001). No reference to whether there are significant group differences. Chung et al., 2014 [54] Weight loss: The +mobile participants who attended 80% or more of the treatment sessions lost significantly more weight than the less adherent participants of the +mobile group and, than the adherent or non-adherent participants of the standard group. Significant group differences (no p-values).
The self-monitoring of food intake was considerably higher in technology compared to standard group (86.2% vs. 71.5%), but did not reach significance (p = 0.098). The technology group wore the bracelet for 91.3% of the days. No significant group differences (p = 0.46). Shuger et al., 2011 [57] Weight loss: Adherence to wearing the bracelet was greater than 55%, suggesting that weight loss participants may adhere better to self-monitoring protocols that use technology, compared to standard protocols. In terms of adherence, one study observed significant correlations between weight change at 12 months and the number of days of diet entries (r = 0.69; p < 0.001), number of daily exercise entries (r = 0.54; p = 0.004), and number of weekly weight entries (r = 0.56; p = 0.004) [51]. In another study, each additional target set and each weight measurement recorded were associated with greater weight loss, of 0.32 kg and 0.21 kg, respectively [48].

Personal Digital Assistant (PDA) or Electronic Journal (EJ)
Among the four studies that used this type of technology, just in one of them, the PDA group lost significantly more weight than the control group (−2.9 kg vs. −0.02 kg; p = n.s.) [55]. The groups that used this technology lost an average of 2.0 kg, with 2.9 kg and 1.18 kg being the highest and lowest average amounts lost by the PDA groups.
In two studies, adherence was higher in the PDA groups [52]. However, it decreased as of the third week [52]. Wang et al. [53] stated that, compared to the paper control, using PDA to control diet (p = 0.027) and physical activity (p = 0.014) had significant direct effects on weight loss.

Discussion
The results found in this work indicate that weight loss was greater in the groups whose intervention was performed or complemented by one of the aforementioned types of technology, although in 13 studies [13,15,26,29,32,33,38,51,52,54,56,61,62], the differences with the control or comparison groups were not statistically significant. However, the same cannot be concluded regarding weight maintenance, since most of the studies did not include this outcome. In another study, the two groups that used a smartphone lost more weight than the control group, with significant differences between the SMS + Coaching group and the control group but not between the SMS group alone and the control group [40]. At the same time, adherence was better in the technology groups, except for one study where the standard group monitored their diet for a greater average number of days than the technology groups [34]. Except for two studies [11,43], adherence was associated with the weight changes that took place in the technology groups, and in all the works in which the association was studied, it was observed that greater adherence led to greater weight loss.
In general, these results suggest that the use of different types of technology for self-monitoring of diet, physical activity, and/or weight is effective in promoting weight loss among people who are overweight or obese.
In this systematic review, about half of interventions (47%) performed or complemented by some kind of technology helped participants to achieve significant weight losses, compared to the control or comparison groups. These results follow a very similar line to those obtained in other systematic reviews. For example, Raaijmakers et al. [63] found that half of the technology-based interventions (54%) significantly helped participants lose weight, compared to the lack of attention or habitual attention. Similarly, Allen et al. [64] found that in more than half of the studies analyzed (53%), statistically significant weight loss was evident in the intervention group, compared to that of the control group. Another study comparing weight changes between eHealth interventions and control groups without intervention found a significantly greater decrease in weight in eHealth interventions (M = −2.70 kg, p < 0.00001) than in the control group. Also, when comparing eHealth interventions and control groups that received a minimal intervention, a significantly greater decrease was observed in eHealth interventions (M = −1.40 kg, p < 0.0001) [65].
The provision of feedback could be effective as a complement to interventions carried out using technology to promote weight loss [52,53]. This might suggest that receiving feedback in the form of text messages or emails could improve adherence to self-monitoring and, as a result, lead to increased weight loss. Nevertheless, more research is needed on this topic since the evidence found in this systematic review is not strong enough. In one study, adherence to self-monitoring was higher in those receiving feedback (78%) compared to those who did not receive it (78% vs. 64%; p < 0.001), and also, participants who received feedback lost more weight than those who did not receive it (7.0 kg vs. 5.0 kg (p < 0.05) [66]. It has also been observed that participants who received personalized feedback had an average weight loss of 2.13 kg more (p < 0.00001) at 3 and 6 months, compared to the control groups. However, this was not observed in interventions lasting 12 months or more [67].
Based on the results obtained, using some kind of technology also implies that people who are overweight or obese will show better adherence to treatment because the new technologies allow a much faster and more efficient recording of data related to dietary intake, physical activity, and weight, as well as their analysis in real time [17][18][19]68]. Semper et al. [69] stated that participants who used an App were more likely to adhere to the self-monitoring of dietary intake.
Of all the methods analyzed, physical activity monitors were the type of technology that achieved the greatest weight loss (M = 6.21 kg), followed by virtual reality (4.7 kg), website (3.75 kg), smartphone (3.44 kg), and PDA (2.0 kg) (Table S1). However, only seven studies of those analyzed used these types of technology to perform the intervention, and therefore, it is impossible to know exactly whether these mean weight losses would remain so high after being evaluated in more groups of people.
This review presents a series of limitations. First, the wide variability in the design of the studies included limits the conclusions that can be reached. Second, the search only included English and Spanish publications, which may not have represented all the available evidence. Thirdly, heterogeneity of the time periods of the intervention was high, ranging from a few weeks to 24 months, which can affect the strength of our results and conclusions. Fourth, the presence of studies that used a small sample size may be associated with greater uncertainty about the measured effect. And, fifth, heterogeneity in the type of intervention performed and the groups with which the comparison was made, which can make the comparison of effectiveness difficult to investigate. However, it has a main strength, which is the fact that it is one of the few systematic reviews that encompasses studies that used different types of technology to carry out the intervention and it does not focus solely on one of them.

Conclusions
Weight loss programs for people who are overweight or obese, carried out or supplemented by some kind of technology, seem to lead to greater weight loss compared to traditional programs. Physical activity monitors and virtual reality were the types of technology that lead to increased weight loss, although further research is needed on the use of these types of technology, as the evidence found is scarce. The use of technology also seems to allow improvement in adherence to treatment, as it allows a simpler and faster self-monitoring. In addition, although more research is needed, this could improve more when the technology is accompanied by immediate feedback. However, future research should focus on this, as, despite the use of technology, adherence to dietary-nutritional treatment often decreases over time, resulting in less weight loss as time passes.
Finally, research on this issue should continue to be carried out, as overweight and obesity are currently very present worldwide, and also, as technologies are part of the day-to-day life of today's society, these could be of great help in weight loss programs, as suggested by the results of this systematic review.  Funding: TIN2017-89069-R funded by the Ministry of Economy, Industry and Competitiveness and the European Regional Development Fund (FEDER).

Conflicts of Interest:
The authors declare no conflict of interest.