Manipulating Self-Avatar Body Dimensions in Virtual Worlds to Complement an...

[Full title: Manipulating Self-Avatar Body Dimensions in Virtual Worlds to Complement an Internet-Delivered Intervention to Increase Physical Activity in Overweight Women]

International Journal of Environmental Research and Public Health Article Manipulating Self-Avatar Body Dimensions in Virtual Worlds to Complement an Internet-Delivered Intervention to Increase Physical Activity in Overweight Women Jessica Navarro 1,2, *, Ausi à s Cebolla 1,2 , Roberto Llorens 3,4 , Adri á n Borrego 3 and Rosa M. Baños 1,2,5 1 Department of Personality, Evaluation and Psychological Treatment, University of Valencia, 46010 Valencia, Spain; ausias.cebolla.marti@gmail.com (A.C.); Rosa.Banos@uv.es (R.M.B.) 2 CIBER Physiopathology of Obesity and Nutrition (CIBEROBN), Carlos III Institute, 28029 Madrid, Spain 3 Neurorehabilitation and Brain Research Group, Instituto de investigaci ó n e Innovaci ó n en Bioingenieria, Universitat Polit é cnica de Valencia, 46022 Valencia, Spain; rllorens@i 3 b.upv.es (R.L.); aborrego@lableni.com (A.B.) 4 NEURORHB, Servicio de Neurorrehabilitaci ó n de Hospitales Vithas, 46007 Valencia, Spain 5 Polibienestar Institute, 46022 Valencia, Spain * Correspondence: jessica.navarro@uv.es; Tel.: + 34-96-386-44-12 Received: 17 May 2020; Accepted: 2 June 2020; Published: 5 June 2020 Abstract: Virtual reality has been found to be a useful tool for positively influencing relevant psychological variables in order to increase physical activity (PA), especially in the overweight population. This study investigates the use of avatars and their physical variations to extend the e ff ectiveness of existing interventions to promote PA. The main objective is to analyze the influence of the avatars’ body dimensions on the e ffi cacy of an Internet intervention to increase PA levels and improve other relevant variables (motivation toward PA, enjoyment, anxiety, self-e ffi cacy, and PA goals). A total of 42 overweight women received a brief online intervention, and they were randomly assigned to one of three conditions: the “Ideal avatar” (IAC: participants are represented by avatars with ideal body dimensions); the “Real avatar” (RAC: participants are represented by avatars with participants’ current body dimensions); and the “Non avatar” (NAC: participants are not represented by avatars). Results showed that the online intervention was e ff ective in increasing PA practice and self-e ffi cacy expectations. However, manipulating the body dimensions of avatars did not improve this intervention, although ideal avatars helped to reduce the anxiety experienced during PA in this population Keywords: physical activity; overweight; virtual reality; virtual environments; avatars; intervention 1. Introduction Physical inactivity and sedentariness are considered serious health problems with great economic, social, and individual impact [ 1 ]. National and worldwide associations and institutions have proposed a series of recommendations for the minimum amount of physical activity (PA) required for health [ 2 ]. However, the majority of overweight people do not meet these minimums [ 3 ]. Empirical evidence has shown relationships between low PA levels and several psychological variables, such as low self-e ffi cacy expectations, low motivation, low enjoyment, negative body representations, or anxiety during PA, among others [ 4 – 14 ]. In addition, di ff erent interventions have been designed to change this tendency, including Internet-delivered interventions [ 15 ]. Int. J. Environ. Res. Public Health 2020 , 17 , 4045; doi:10.3390 / ijerph 17114045 www.mdpi.com / journal / ijerph

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 2 of 14 These interventions have been found to increase PA motivation in normal and overweight populations [ 15 ], although their long-term e ff ectiveness has not been established [ 15 , 16 ]. Other technologies, such as virtual reality (VR), have also been proposed as helpful tools for learning healthy behaviors, such as PA habits [ 17 , 18 ], and there is evidence that virtual experiences can promote PA practice [ 18 – 20 ]. The use of VR has several advantages, such as the ability to manipulate body representations [ 21 – 23 ] and increase self-e ffi cacy expectations, motivation, or adherence. For instance, some studies have shown that using avatars that physically resemble the user can increase expectations of self-e ffi cacy toward PA and motivate adherence to the practice [ 18 , 24 ] in normal-weight individuals. These results can be explained by Bandura’s social cognitive theory [ 25 ], which assumes that individuals vicariously learn new behaviors by observing these behaviors in others [ 25 ]. In VR scenarios, avatars can have a strong physical resemblance to individual users [ 26 ], and individuals are more likely to learn a behavior if they identify with the model [ 25 ]. Regarding the overweight and body dissatisfied population, research shows that avatar resemblance increases awareness of a negative body image and anxiety during PA practice. Song and colleagues [ 23 ] found that when participants with body image dissatisfaction embodied avatars representing their ideal body, they showed greater enjoyment and decreased anxiety levels during PA practice. Therefore, using avatars with di ff erent body dimensions could help individuals to overcome body representation di ffi culties during PA practice [ 21 , 22 ] and, consequently, encourage them to exercise [ 23 ]. Several studies have pointed out that manipulation of the body dimensions of virtual avatars can influence PA practice [ 24 , 27 – 29 ]. Specifically, participants embodying normal-weight avatars showed more PA on a virtual task, compared to overweight avatars [ 27 – 29 ]. These results can be explained by the “Proteus e ff ect” [ 30 ], which assumes that individuals change their behavior in accordance with the characteristics and appearance of their avatars, in order to conform to the expectations and stereotypes of these avatars. Some research has found support for this e ff ect in di ff erent VR experiences [ 17 , 31 ]. To date, studies on the influence of avatars on PA practice have consisted of sessions where the avatar’s physical characteristics were manipulated and the impact on the execution of a PA task was analyzed at that moment [ 24 , 27 – 29 ] or in the subsequent practice of PA within a short period of time [ 18 ]. However, no studies have tested whether the use of avatars and their physical variations can enhance the e ff ectiveness of existing interventions to increase the level of PA The aim of the present study is to analyze the influence of avatars’ body dimensions on the e ffi cacy of an Internet-delivered intervention specifically designed to increase PA levels in overweight and obese sedentary women. In order to test this objective, participants receive a brief online intervention [ 32 ] enriched with a virtual task using avatars. Three conditions are compared, according to the virtual task participants have to perform: (a) the “Ideal avatar condition” (IAC: participants are represented by avatars with body dimensions they rated as “ideal”); (b) the “Real avatar condition” (RAC: participants are represented by avatars with their own current body dimensions); and (c) the “Non avatar condition” (NAC: participants are not represented by avatars while performing PA). The influence of these experimental conditions on several relevant psychological variables (motivation, enjoyment, anxiety, self-e ffi cacy, and PA goals) are analyzed We hypothesize that all participants will improve their PA levels after the intervention. In addition, we hypothesize that participants represented by avatars (IAC and RAC conditions) will show a significantly higher PA level and achievement of PA goals than NAC participants. We also hypothesize that IAC and RAC participants will increase their scores on motivation, enjoyment, and self-e ffi cacy, and this increase will be higher than in NAC participants. In addition, we expect that IAC participants will choose more ambitious PA goals and show lower anxiety while performing PA, compared to RAC participants. Finally, we hypothesize that similarity to the avatar and self-e ffi cacy expectations will mediate between the conditions and the increase in PA levels after the intervention.

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 3 of 14 2. Materials and Methods 2.1. Participants The final sample was composed of 42 overweight and obese women (BMI, M = 28.7; SD = 3.1) who were sedentary and had high body dissatisfaction (see participants’ recruitment flow in Figure 1 ) Their ages ranged from 19 to 61 years ( M = 31.9; SD = 11.7). Participants were recruited in nutrition clinics and gyms. Because participants had to show low activity levels, the gyms only contacted women who had dropped out. Flyers and in-person presentations were used to publicize the study. The eligibility criteria were: being a woman from 18–64 years old; being overweight (BMI > 25); having high body dissatisfaction (Body Schema Questionnaire—BSQ— > 80); being physically inactive; and not having any physical condition that could keep them from practicing PA. Of the total 216 participants excluded from the study, 70% of the them were excluded because they were not overweight, and 30% of the remaining participants were excluded for reasons related to PA practice (e.g., they were physically active) or body dissatisfaction (e.g., they showed no body dissatisfaction). Participants were informed about the study, and they signed informed consent documents. This study was approved by the Ethical Committee of the University of Valencia (Spain) Figure 1. Flow chart of participants’ recruitment 2.2. Procedure After the participants contacted us, they were informed about the contents of the study by telephone, and they signed the informed consent by email. Participants who met the criteria were randomly assigned to one of the three conditions (IAC: 14; RAC: 14; NAC; 14), using the Random Allocation Software 2.0 (This software has been developed by M. Saghaei, MD., Department of Anesthesia, Isfahan University of Medical Sciences, Isfahan, Iran). First, they were sent an email with the link to fill out the questionnaires online. Then, they received a link with the online intervention they had to follow for a week to increase PA. The specific time spent on this online intervention was registered for each participant. After seven days, participants were individually invited to the laboratory, where the virtual PA task was applied for about 10 min. The virtual task varied in the three conditions.

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 4 of 14 (a) IAC participants were asked to create an avatar with their ideal body dimensions and their own face. They were shown a default avatar and were able to change its body dimensions. Then, they performed a running task for 4 min in a VR scenario where they were represented by this avatar. The VR task performance was video-recorded, and participants received this video on their mobile phones and were asked to watch it every day of the week (b) RAC participants received the same instructions, but they were asked to change the avatar (with their face) to fit their real body dimensions (c) NAC participants were asked to perform the PA task in the VR scenario for 4 min, but participants were not represented by an avatar. They ran in front of a fixed image corresponding to the VRE. They did not receive any video-recordings Finally, all participants were asked to choose a weekly PA goal (walking or running three times a week). A week later, they received an email with the link to answer the questionnaires online. Finally, all participants came back to the lab to report on the achievement of the PA goals and receive their reward for completing the study (an invitation to a gymnasium where they could participate in sports activities and study their physical condition). All participants were met by blinded study sta ff 2.3. Materials 2.3.1. VR Program The VR scenario consisted of a 3 D graphical environment representing a park where an avatar runs. Avatars’ characteristics varied depending on the experimental condition (IAC and RAC). In the IAC and RAC conditions, the participant’s face was tracked by the Kinect. All participants ran in place in a room, and their movements were captured by a Kinect and projected on a 150 × 150 cm screen During the PA task, participants could see the time and distance they had run on the screen 2.3.2. Online Intervention This brief one-session intervention is based on the trans-theoretical model components of behavior change [ 33 ], and it has shown its e ff ectiveness in previous studies [ 32 ]. It consists of two parts: the first one, “Motivation for Change”, provides information on PA, recommendations, consequences of physical inactivity, and possible barriers; the second part, “Move it”, focuses on helping participants to find their own motivation and set their specific PA goals for the future. For a more detailed description, see [ 32 ]. The entire intervention lasted about 45 min, and the specific time spent on the intervention screen was recorded for each participant 2.4. Measures Anthropometric and sociodemographic data. An ad-hoc questionnaire was created to collect information about sociodemographic data, height, and weight Body Shape Questionnaire (BSQ [ 34 ]). It consists of 34 items, rated on a scale from 1 to 6 (1 = “never” to 6 = “always”), that evaluate the dissatisfaction produced by one’s body, the fear of gaining weight, self-devaluation due to physical appearance, the desire to lose weight, and avoidance of situations where one’s physical appearance could attract the attention of others. The measure is the composite sum of the items, and higher scores reflect greater body dissatisfaction in the past four weeks. There are four categories of concern: “no concern” ( < 81), “mild concern” (81–110), “moderate concern” (111–140), and “extreme concern” ( > 140) [ 34 ]. The cut-o ff point for inclusion in this study was 81. The Spanish version used in this study showed adequate internal consistency [ 35 ]. International physical activity questionnaire (IPAQ [ 36 ]): Through 31 items, this questionnaire collects data on PA performed in the past 7 days. It identifies the frequency and duration of moderate and vigorous leisure, transportation and occupational PA, walking PA, and inactivity during the past

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 5 of 14 week. The IPAQ has reported test-retest reliability correlations of 0.81 and validity correlations with accelerometers of 0.33 [ 37 ]. Weekly PA goal registration: This ad hoc record collects data on the weekly achievement of the specific PA goal in all the conditions, as well as the video display for the IAC and RAC conditions. The two possible goals were walking or running three times a week. All participants were free to choose one of these two goals Behavioral Regulation in Exercise Questionnaire (BREQ-2 [ 38 ]). This questionnaire is based on the theory of self-determination, which provides insight into the reasons people adopt and maintain healthy behaviors [ 39 , 40 ]. It consists of 19 items, rated on a scale from 0 to 5 (0 = “Not at all true for me” to 5 = “absolutely true for me”), that measure stages on the continuum of self-determination in PA behavior. This questionnaire assesses external regulation, introjected regulation, identified regulation, and intrinsic regulation, and it adds demotivation. The BREQ-2 has shown acceptable internal consistency [ 41 ]. Self-efficacy to regulate exercise (ESE [ 42 ]). It consists of 18 items, rated on a scale from 0 to 100 (0 = “not at all sure” to 100 = “Very sure”), that evaluate how sure the person is about regularly performing an exercise routine (three or more times per week). The measure is the composite mean of the items, and higher scores reflect greater PA self-e ffi cacy. This scale has been shown to be a useful measure of exercise self-e ffi cacy expectations in several populations [ 43 – 45 ]. Enjoyment (PACES [ 46 ]): This questionnaire consists of 16 items, rated on a scale from 1 to 5 (1 = “Strongly disagree” to 5 = “Strongly agree”), that evaluate the degree of enjoyment of PA The measure is the composite mean of the items, and higher scores reflect more enjoyment of PA PACES has been a useful instrument to measure enjoyment in di ff erent fields of PA [ 47 ]. The physical activity and sport anxiety scale (PASAS [ 48 ]). This is a 16-item self-report that assesses social fear and avoidance of sports and PA on a scale from 1 (“not at all characteristic of me”) to 5 (“extremely characteristic of me”). This measure has demonstrated good internal consistency, test-retest reliability, and convergent and divergent validity [ 48 ]. Avatar identification modified questionnaire [ 49 ]. It consists of 17 items, rated on a scale from 1 (“Strongly disagree”) to 5 (“Strongly agree”), that assess the degree of embodied presence, perceived similarity, and the participant’s desire to identify with the avatar. This self-report has been shown to be a reliable measure of identification in online games [ 49 ]. 2.5. Data Analyses Statistical analyses were conducted using the SPSS for Windows (version 24) (This software has been developed by Norman H. Nie, Dale H. Bent, and C. Hadlai Hull., University of Stanford, United states). First, to assess the influence of the avatars’ body dimensions on PA, repeated-measures ANOVA were performed on each variable (motivation, enjoyment, anxiety, self-e ffi cacy, and PA levels), with condition (3: IAC, RAC, and NAC) as between factor and time (2: pre versus post intervention) as within factor. In addition, univariate ANOVAs were carried out to analyze the di ff erences between conditions in the time spent on the intervention, video display during the week, and the achievement of PA goals. When a significant interaction was found, post-hoc analyses using Bonferroni adjustment were conducted to determine which group comparisons were significant Second, to check di ff erences between conditions in the PA goal chosen, a chi-square test was performed, using Monte Carlo with 10,000 samples as a 99% level of confidence. When the absolute value of the adjusted standardized residual was greater than 1.96, there were significant di ff erences between conditions. Subsequently, e ff ect sizes (Cohen’s d) and confidence intervals were calculated for within-group changes, given that e ff ect sizes are the best indicator of the magnitude of the observed changes, which is essential information that cannot be obtained by focusing exclusively on p -values [ 50 ]. Finally, using Model 6 from PROCESS 3.3, we performed two serial multiple mediation analyses to test whether the e ff ects of condition on the change in PA were mediated by self-e ffi cacy and perceived similarity to the avatar. The procedure described by Hayes [ 51 ] was performed using the PROCESS

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 6 of 14 macro for SPSS. Significance tests ( p < 0.05) or a confidence interval (not including zero) for the interaction answered this question 3. Results 3.1. Adherence to Tasks Time spent on the online intervention. Descriptive statistics can be found in Table 1 . For the time spent on the intervention, the results showed a wide range from 1 to 372 min ( M = 46.71; SD = 68.49) Results did not show di ff erences between conditions F (2, 40) = 0.25, p = 0.779, η = 0.01 Table 1. ANOVA results for baseline measures and intervention adherence Measure Condition N M (SD) Baseline p PA levels NAC 14 2499.81 (2231.45) 0.571 RAC 14 1902.33 (971.67) IAC 14 2552.98 (1927.08) Total 42 2318.37 (1773.36) Intrinsic Regulation NAC 14 10.57 (3.41) 0.413 RAC 14 9.64 (1.82) IAC 14 10.93 (2.34) Total 42 10.38 (2.60) Identified Regulation NAC 14 10.93 (3.22) 0.091 RAC 14 11.71 (3.27) IAC 14 13.29 (1.64) Total 42 11.98 (2.92) Introjected Regulation NAC 14 9.00 (1.62) 0.423 RAC 14 8.71 (1.07) IAC 14 9.43 (1.55) Total 42 9.05 (1.43) External Regulation NAC 14 10.57 (3.41) 0.634 RAC 14 10.71 (1.86) IAC 14 11.36 (0.93) Total 42 10.88 (2.28) Demotivation NAC 14 10.07 (4.32) 0.264 RAC 14 8.36 (3.65) IAC 14 7.93 (2.67) Total 42 8.79 (3.65) Enjoyment NAC 14 60.64 (11.47) 0.323 RAC 14 63.79 (10.89) IAC 14 66.86 (9.91) Total 42 63.76 (10.82) Anxiety NAC 14 47.93 (13.08) 0.253 RAC 14 40.93 (16.34) IAC 14 38.71 (15.65) Total 42 42.52 (15.24) Self-e ffi cacy NAC 14 469.28 (185.45) 0.111 RAC 14 646.43 (317.29) IAC 14 752.14 (483.23) Total 42 622.62 (361.68) Body Mass Index NAC 14 29.39 (3.57) 0.627 RAC 14 28.42 (2.69) IAC 14 28.35 (3.22) Total 42 28.72 (3.13)

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 7 of 14 Table 1. Cont Measure Condition N M (SD) Baseline p Motivational Intervention NAC 14 38.69 (38.37) 0.779 RAC 14 57.43 (96.23) IAC 14 44.76 (65.00) Total 42 46.71 (68.49) Avatar Video NAC 14 —– 0.552 RAC 14 5.79 (1.93) IAC 14 6.14 (1.09) Total 28 5.96 (1.55) Body Dissatisfaction NAC 14 117.07 (23.45) 0.817 RAC 14 116.57 (30.61) IAC 14 110.86 (31.15) Total 42 114.83 (28.06) Note. PA levels (for a week) = IPAQ; Intrinsic Regulation = BREQ-2 (20); Identified Regulation = BREQ-2 (20); Introjected Regulation = BREQ-2 (15); External Regulation = BREQ-2 (20); Demotivation = BREQ-2 (20); Enjoyment = PACES (80); Anxiety = PASAS (80); Self-e ffi cacy = ESE (1800); Body Mass Index = BMI; Motivational Intervention = minutes dedicated to the online intervention; Avatar Video = days a week of viewing; Levels of Body Dissatisfaction = BSQ (204). The score in brackets is the maximum score in the questionnaire Watching the avatar video during the week. Descriptive statistics can be found in Table 1 . Most of the participants watched the video daily ( M = 5.96; SD = 1.55). There were no di ff erences across conditions F (1, 27) = 0.36, p = 0.552, η = 0.01 3.2. E ffi cacy Results: Di ff erences between Conditions Descriptive statistics and within-group e ff ect sizes (measured by Cohen’s d ) can be found in Table 2 . PA levels (IPAQ [ 37 ]): Regarding the ANOVA results, there was a main e ff ect of time on PA levels F (1, 39) = 15.82, p = 0.000, η = 0.29. All participants showed higher PA levels after the intervention However, the interaction between time and condition was not significant F (1, 39) = 0.05, p = 0.949, η = 0.00 Table 2. Descriptive statistics and within-group e ff ect sizes for outcomes Measure Condition N M (SD) Pre M (SD) Post p Within-Group E ff ect Size, d [95% CI] Pre-post Intervention Intrinsic Regulation NAC 14 10.57 (3.41) 10.29 (2.61) 0.076 0.08 [ − 0.58, 0.73] RAC 14 9.64 (1.82) 11.07 (1.64) − 0.74 [ − 1.47, − 0.01] IAC 14 10.93 (2.34) 9.93 (2.09) 0.40 [ − 0.28, 1.08] Identified Regulation NAC 14 10.93 (3.22) 11.21 (2.08) 0.347 − 0.08 [ − 0.56, 0.39] RAC 14 11.71 (3.27) 13.00 (3.03) − 0.37 [ − 0.87, 0.13] IAC 14 13.29 (1.64) 13.21 (2.78) 0.05 [ − 0.43, 0.52] Introjected Regulation NAC 14 9.00 (1.62) 9.43 (0.85) 0.736 − 0.25 [ − 0.85, 0.35] RAC 14 8.71 (1.07) 9.00 (1.30) − 0.26 [ − 0.86, 0.35] IAC 14 9.43 (1.55) 9.43 (1.34) − 0.00 [ − 0.59, 0.59] External Regulation NAC 14 10.57 (3.41) 10.07 (2.09) 0.811 0.14 [ − 0.46, 0.73] RAC 14 10.71 (1.86) 10.50 (1.95) 0.11 [ − 0.49, 0.69] IAC 14 11.36 (0.93) 10.57 (1.34) 0.80 [0.11, 1.48] Demotivation NAC 14 10.07 (4.32) 7.86 (2.32) 0.139 0.48 [ − 0.08, 1.04] RAC 14 8.36 (3.65) 8.29 (2.37) 0.02 [ − 0.50, 0.54] IAC 14 7.93 (2,67) 7.57 (2.28) 0.13 [ − 0.39, 0.65]

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 8 of 14 Table 2. Cont Measure Condition N M (SD) Pre M (SD) Post p Within-Group E ff ect Size, d [95% CI] Pre-post Intervention Enjoyment NAC 14 60.64 (11.47) 62.71 (12.02) 0.776 − 0.17 [ − 0.73, 0.39] RAC 14 63.79 (10.89) 63.43 (9.34) 0.03 [ − 0.52, 0.58] IAC 14 66.86 (9.91) 69.14 (7.37) − 0.22 [ − 0.77, 0.34] Anxiety NAC 14 47.93 (13.08) 37.71 (12.09) 0.016 0.74 [0.29, 1.18] RAC 14 40.93 (16.34) 40.43 (16.95) 0.03 [ − 0.29, 0.35] IAC 14 38.71 (15.65) 32.57 (16.49) 0.37 [0.01, 0.73] Self-e ffi cacy NAC 14 469.2857 (185.45015) 760.7143 (355.77574) 0.38 − 1.48 [ − 2.32, − 0.64] RAC 14 646.4286 (317.28675) 775.7143 (416.75882) − 0.38 [ − 0.96, 0.19] IAC 14 752.1429 (483.22918) 852.8571 (389.72236) − 0.20 [ − 0.75, 0.36] PA levels NAC 14 2499.807 (2231.4511) 3884.9214 (2671.75408) 0.949 − 0.58 [ − 1.14, − 0.03] RAC 14 1902.329 (971.6688) 3065.2357 (1924.58215) − 1.13 [ − 1.81, − 0.44] IAC 14 2552.979 (1927.0837) 3733.8714 (2428.44219) − 0.58 [ − 1.13, − 0.02] Note. Intrinsic Regulation = BREQ-2; Identified Regulation = BREQ-2; Introjected Regulation = BREQ-2; External Regulation = BREQ-2; Demotivation = BREQ-2; Enjoyment = PACES; Anxiety = PASAS; Self-e ffi cacy = ESE; PA levels (for a week) = IPAQ Bold letter = e ff ect of sizes of greater magnitude PA goals (walking or running three times a week). No significant effects were found on the achievement of the PA goal F (2, 41) = 0.36, p = 0.702, η = 0.02. Regarding the specific PA goal chosen, despite the trends found, chi-square analyses showed no differences between conditions χ 2 (2, N = 42) = 3.20, p = 0.202, Cramer’s V = 0.28. The percentages of the specific PA goals chosen in each condition are shown in Table 3 . The specific PA goal of walking was chosen by 73.8% of the participants Table 3. Chi-square test results NAC RAC IAC Total Walking Count 12 11 8 31 Expected count 10.3 10.3 10.3 30.9 % 38.7 35.5 25.8 100 ASR 1.2 0.5 − 1.7 – Running Count 2 3 6 11 Expected count 3.7 3.7 3.7 11.1 % 18.2 27.3 54.5 100 ASR − 1.2 − 0.5 1.7 – Note. Count = number of participants who choose the PA goal; Expected count = number of participants expected to choose the PA goal; % = percentage of participants who choose the PA goal; ASR = Adjusted standardized residuals Motivation toward PA (BREQ-2 [ 38 ]). No effect of time was found on any subscale (intrinsic regulation F (1, 39) = 0.12, p = 0.913, η = 0.00, identified regulation F (1, 39) = 1.65, p = 0.207, η = 0.04, introjected regulation F (1, 39) = 1.10, p = 0.300, η = 0.03, external regulation F (1, 39) = 1.93, p = 0.173, η = 0.05, and demotivation F (1, 39) = 3.57, p = 0.066, η = 0.08). No interactions between time and condition were significant for any subscale (intrinsic regulation F (2, 39) = 2.76, p = 0.076, η = 0.12, identified regulation F (2, 39) = 1.09, p = 0.347, η = 0.05, introjected regulation F (2, 39) = 0.31, p = 0.736, η = 0.02, external regulation F (2, 39) = 0.21, p = 0.811, η = 0.01, and demotivation F (2, 39) = 2.07, p = 0.139, η = 0.09).

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 9 of 14 Enjoyment (PACES [ 46 ]). No time effect was found on enjoyment ( F (1, 39) = 0.63, p = 0.432, η = 0.02), and the interaction e ff ect between time and condition was not significant either ( F (2, 39) = 0.25, p = 0.776, η = 0.01) Anxiety (PASAS [ 48 ]). There was a main effect of time on total anxiety during PA practice ( F (1, 39) = 18.18, p = 0.000, η = 0.32). All participants showed lower anxiety levels during PA after the intervention. In addition, the interaction between time and condition was also significant ( F (2, 39) = 4.57, p = 0.016, η = 0.19). Posthoc comparisons using Bonferroni correction revealed that IAC and NAC participants showed lower anxiety levels during PA after the intervention ( p = 0.010 and p = 0.000), compared to RAC participants Self-e ffi cacy (ESE [ 42 ]). There was a main e ff ect of time on self-e ffi cacy toward PA (F (1, 39) = 8.49, p = 0.006, η = 0.18). However, despite the trends found, the interaction between time and condition was not significant (F (2, 39) = 0.99, p = 0.380, η = 0.05) 3.3. Similarity to the Avatar and Self-E ffi cacy Expectations as Mediators: Do Similarity to the Avatar and Self-e ffi cacy Influence PA Practice? Two serial multiple mediation analyses were carried out to test whether the effects of condition on the change in PA (PA levels and achievement of PA goals) were mediated by similarity to the avatar and self-e ffi cacy expectations Regarding the effects on the achievement of the PA goal (Figure 1 ), the indirect effect of “Condition → change in similarity to the avatar → achievement of PA goal was significant, implying that similarity to the avatar mediated the relationship between the condition and achievement of the PA goal, b = − 0.40, SE = 0.25, 95% CI [ − 1.15, − 0.07]. This result means that participants who perceived the avatar as similar to themselves showed greater achievement of the PA goal. In contrast, the other two indirect effects tested in this serial multiple mediation model were not significant: (a) Indirect e ff ect of “Condition → change in self-e ffi cacy → achievement of PA goal”, b = 0.03, SE = 0.18, 95% CI [ − 0.14, 0.62]; (b) Indirect e ff ect of “Condition → change in similarity to the avatar → change in self-e ffi cacy → achievement of PA goal”, b = − 0.05, SE = 0.09), 95% CI [ − 0.48, 0.01] Regarding the e ff ects on PA levels (Figure 2 ), none of the indirect e ff ects were significant: (a) Indirect e ff ect of “Condition → change in similarity to the avatar → changes in PA levels”, b = − 646.29, SE = 588.49, 95% CI [ − 2142.42, 103.55]: (b) Indirect e ff ect of “Condition → change in self-e ffi cacy → change in PA levels”, b = 82.18, SE = 304.67, 95% CI [ − 692.18, 563.01]: (c) Indirect effect of “Condition → change in similarity to the avatar → change in self-efficacy → change in PA levels, b = − 137.06, SE = 163.95, 95% CI [ − 512.75, 131.89] Figure 2. Serial multiple mediation analysis. Note. * p < 0.05.

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 10 of 14 4. Discussion This study was conducted to analyze the influence of avatars’ body dimensions on the e ffi cacy of an online intervention to increase PA levels, as well as the influence on other relevant variables (motivation toward PA, enjoyment, anxiety, self-e ffi cacy, and PA goals), in a sample of overweight and body dissatisfied women. A second aim was to explore whether the e ff ects of the condition on the change in PA (PA levels and achievement of PA goals) were mediated by the similarity to the avatar and self-e ffi cacy expectations The first hypothesis assumed that the intervention would be e ff ective in increasing PA levels in all participants, regardless of the condition. This hypothesis was confirmed because significant increases were found in PA levels and self-e ffi cacy expectations after the intervention in all participants Previous studies with this intervention showed its e ff ectiveness in a sample of university students [ 32 ]. Specifically, previous results revealed that it had been e ff ective in increasing awareness of the positive consequences of PA practice, influencing the strategies used to modify the PA habit, increasing enjoyment during PA practice, and, consequently, increasing the number of weekly steps. The results of this study confirm the e ffi cacy of this brief online intervention in overweight and obese populations These data are quite promising because it is a very short, self-applied intervention and can be quite cost e ff ective in increasing PA in di ff erent populations. It would be interesting to include a follow-up measure to show the mediumand long-term e ff ects of this intervention The second hypothesis proposed that participants represented by avatars (IAC and RAC) would show higher levels of PA, achievement of goals, motivation, self-e ffi cacy, and enjoyment, compared to NAC participants. In addition, we expected that IAC participants would choose more ambitious goals and show lower anxiety while performing PA because using avatars with di ff erent body dimensions has been shown to help individuals to overcome body representation di ffi culties during PA practice [ 21 , 22 ]. This hypothesis was only confirmed for anxiety scores. As expected, the IAC participants showed lower levels of anxiety compared to RAC participants. However, it is important to highlight that the NAC participants scored the lowest on anxiety. NAC participants were not represented by any avatar or exposed to their body during the virtual PA task, and they performed the PA task in front of an image of a park, which could act as a distracting stimulus from their own body. Our results suggest that the use of avatars in virtual scenarios can elicit anxiety in overweight and body dissatisfied individuals by increasing self-body image awareness [ 23 ], and this anxiety induction could be higher with avatars representing their real body dimensions rather than ideal body dimensions. According to the literature, dissatisfaction with body image acts as a barrier to PA practice [ 9 , 10 ] especially in contexts where body image is more prominent, such as group PA or mirror environments [ 11 , 13 , 14 , 52 ]. Our results seem to support this line of research. The use of avatars in the context of overweight and dissatisfied women may enhance the anxiety experienced towards PA since the avatar highlights the individual’s body image, especially when the avatar represents the real self Regarding the lack of significant di ff erences in PA levels and the goal chosen across conditions, our manipulation failed to bring about a major change in PA levels or the choice of a more ambitious goal in IAC participants. First, a high percentage of participants (61.9%) reported that they had successfully achieved their objective. Because they reported this achievement at a face-to-face meeting, social desirability may have had an e ff ect on this report [ 53 ]. Perhaps it would have been preferable to record the achievement online rather than in a face-to-face visit. Regarding the choice of the PA goal, 73.8% of the participants chose to walk, that is, the less ambitious goal. These results are not surprising, as the evidence shows that brisk walking is the preferred PA type for overweight women [ 54 ]. Therefore, it would have been more appropriate not to compare two such di ff erent objectives (running versus walking) but to measure the intensity of the PA performed, for example, by providing participants with an accelerometer during the PA practice that measures the intensity of walking. It seems that manipulating the avatar while performing the intervention has no e ff ect on promoting a more ambitious goal in the participants.

Int. J. Environ. Res. Public Health 2020 , 17 , 4045 11 of 14 Despite the lack of di ff erences, it is important to highlight the changes observed in the RAC condition. According to standardized e ff ect sizes (Cohen’s d ), this group obtained a large e ff ect size ( > 0.80) for their change in PA levels, and they increased their weekly practice the most. Similarly, the results also showed: a medium e ff ect size ( < 0.50) for intrinsic motivation in the RAC participants, who increased their intrinsic motivation scores the most; a large e ff ect size ( > 0.80) for external motivation in the IAC participants, who increased their external motivation scores the most; and a large e ff ect size ( > 0.80) for self-e ffi cacy expectations in participants in the NAC condition, who increased their self-e ffi cacy expectations scores the most. Given these results, although through this study no significant di ff erences between the groups can be concluded, it would be interesting to increase the statistical power of the study. It is possible that increasing the sample size, greater di ff erences might be found The third hypothesis proposed that similarity to the avatar and self-e ffi cacy expectations would mediate between the condition and PA practice. This hypothesis was partially confirmed in the case of achievement of the PA goal. Participants who had judged their avatar to be more similar to themselves were more likely to reach the PA goal. These results are in line with the literature, showing that virtual self-models can be e ff ective instigators of PA change [ 18 ]. In general, research shows that when individuals personalize their avatars they self-report higher behavioral intentions, as measured by the percentage of time they intended to spend on maintaining good health [ 55 , 56 ]. However, intentions and actual behavior associated with such intention did not always correlate and results did not always go in the same direction [ 57 ], which could explain the absence of di ff erences in weekly PA levels The lack of significance of self-e ffi cacy expectations as a mediator between the condition and the achievement of the PA goal could be due to the characteristics of the sample. Other studies have concluded that, although an increase in self-e ffi cacy in normal weight participants has an impact on PA, in obese or overweight people, this e ff ect is not significant [ 58 ]. Some limitations of the current study should be mentioned. The first is that, due to technical limitations, NAC participants did not use a dynamic VR scenario, but rather a fixed image. It would be desirable for all participants to use a VR scenario, with or without an avatar. Second, assessments were only carried out before and after the intervention, and it would be preferable to have more assessments moments (e.g., di ff erent times throughout the PA task), as well as follow-ups As future lines, it would be desirable to include follow-ups to analyze the long term e ff ects of the intervention as well as to include women without body dissatisfaction 5. Conclusions In conclusion, the online intervention used in this study was e ff ective in increasing PA practice and self-e ffi cacy expectations in overweight women. Manipulating the body dimensions of avatars did not improve this intervention. Using ideal avatars seems to reduce the anxiety experienced during PA in this population. However, the use of avatars similar to the person him / herself could have a greater impact on PA and variables related to its long-term practice Author Contributions: J.N., A.C. and R.M.B. designed the study, performed the data analysis, and wrote the manuscript. R.L. and A.B. designed the virtual reality scenario. All authors have read and agreed to the published version of the manuscript Funding: This study was funded by “INTERSABIAS” project (PROMETEO / 2018 / 110, Conselleria d’Educaci ó n, Investigaci ó , Cultura i Esport de la Generalitat Valenciana) and by CIBER of Physiopathology of Obesity Nutrition, an initiative of ISCII (ISCII CB 0603 / 0052) Conflicts of Interest: The authors declare no conflicts of interest References 1 Ding, D.; Lawson, K.D.; Kolbe-Alexander, T.L.; Finkelstein, E.A.; Katzmarzyk, P.T.; Van Mechelen, W.; Pratt, M. Lancet physical activity series 2 executive committee. The economic burden of physical inactivity: A global analysis of major non-communicable diseases Lancet 2016 , 388 , 1311–1324. [ CrossRef ]

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Avatara, Enjoyment, Anxiety, Physical activity, Positive consequences, Motivation, Informed consent, Indirect effect, Long-term practice, Physical condition, Significant difference, Ethical committee, Significant effect, Body mass index, Self efficacy, BMI, Chi square test, Physical Inactivity, Randomly assigned, Significant increase, Confidence interval, Table 1, Table 2, Table 3, Brisk walking, Statistical analyses, Random allocation, Health problem, Anxiety Score, Time effect, Body image, Social cognitive theory, Behavioral intention, Social desirability, Statistical power, Exercise self-efficacy, Virtual Reality, Virtual Reality Experience, Neurorehabilitation, Bonferroni correction, Repeated-measures ANOVA, External motivation, Body dissatisfaction, Significant interaction, Intrinsic motivation, Body image dissatisfaction, Overweight women, ANOVA result, Post-hoc analyses, Exercise behavior, External regulation, Intrinsic regulation, Introjected regulation, Identified regulation, Negative body image, Figure 2, Online intervention, Internet intervention, Virtual world, Behavioral regulation, Virtual environment, Baseline measure, Physical activity goals, Body dimension, University of Valencia, Chi-square analyses, Mediation analyses, PA practice, Physical Activity Practice, Relevant variables, PA type, PA level, Medium Effect Size, Large effect size, Self-e ff icacy, Valencia, Spain, Psychological variable.