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The Impact of Telemonitoring and Health Coaching on Depression, Anxiety and Stress Scales in Overweight and Obese Individuals

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30 October 2024

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31 October 2024

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Abstract
(1) Background: The literature has demonstrated several pathways which links obesity and stress. Thus, new approaches of weight management programs must also integrate health coach-ing and telemonitoring for overall health and wellbeing. The aim of the study is to measure stress, anxiety, and depression scales (DASS-21) in overweight and obese participants who joined a pilot randomized controlled trial (RCT) and the association between changes in DASS-21 scores and changes in anthropometric measures.; (2) Methods: 50 participants have been enrolled in a ran-domized controlled trial and divided in two groups; Intervention group who received a hy-pocaloric diet remotely, weekly telemonitoring and monthly health coaching; Control group who only followed a the hypocaloric diet without any support. The Arabic version of the Depression Anxiety Stress Scale (DASS-21) was used to measure depression, anxiety, and stress scales; (3) Results: Data revealed that participants from the intervention group had a significant decrease in anxiety scales after 3months when compared to the control group. In addition, correlation be-tween depression, anxiety, stress, and all anthropometric measures in the intervention group showed a moderate significant positive correlation between changes in waist circumference and depression. (4) Conclusions: Findings confirms that integrating health coaching and telemonitor-ing have a strong potential in improving wellbeing and weight loss.
Keywords: 
Subject: Public Health and Healthcare  -   Public Health and Health Services

1. Introduction

Integrative nutrition combines the principles of traditional nutrition guidelines and functional nutrition to provide a more individualized approach to eating [1]. The Academy of Nutrition and Dietetics has recognized telenutrition as useful to implement in a dietician’s activity and defines it as “The interactive use by an RDN of electronic information and telecommunications technologies to implement the Nutrition Care Process with patients or clients at a remote location, within the provisions of the RDN’s state license as applicable” [2]. Telenutrition has recently spread since the pandemic due to its convenience and accessibility to many populations. The literature has also revealed that monitoring physical activity and diet significantly improves weight loss and metabolic risks [3,4] and enhances patients’ motivation. Thus, an integrated approach between nutrition, health coaching and telemonitoring for weight management may have a stronger impact on changing behavior to a healthier approach. Previous research has shown that supporting healthcare with health coaching exhibits long-term and sustainable weight loss due to continuous follow-up, feedback, and guidance [5] to improve behavior and well-being [6], weight management and physical activity as well [7]. In fact, in the year 2022, lifestyle coaching delivered via digital channels showed significant long term weight loss [8]. In fact, primary outcomes from our pilot study have revealed that weight management programs when supported with telemonitoring and integrative nutrition health coaching, significant reductions in weight, BMI, fat%, visceral fat, and an increase in muscle. In addition to improvements in waist circumference measures and in blood lipids profile in comparison with the control group [9].
Remarkably, epidemiological studies on the prevalence of obesity in Saudi Arabia have been increasing in the past four decades [10], indicating that obesity still remains a burden among the population [11]. In addition, the WHO has indicated that 30% of deaths worldwide will be associated with lifestyle-related illnesses by the year 2030 and may be stopped by working on specific risk factors, including stress and depression [12]. In 2021 recent study was carried on Saudi adolescent in Abha city highlighted that obesity was a significant risk factor for and depression, which requires dietary and lifestyle intervention [13]. Stress has spread among the Saudi population, but little attention has been given to stress management during dietary consultations by integrative nutrition approaches [14]. Stress and depression have been proven to result from stressful circumstances during childhood and adolescence [15]. The strong link between obesity and stress was seen to be associated with overeating, unhealthy diets, and weight gain [16]. A study revealed that interpersonal stress may be more harmful to girls with overweight/obesity than boys due to body image sensitivities [17]. Moreover, stress is linked with overweight patients with binge-eating disorder (BED) [18]. A study examined the impact of integrating self-monitoring using self-monitoring apps and health coaching, where promising results were seen in both anthropometric measurements and lifestyle outcomes [7,19]. Thus, changes in lifestyle patterns and quality of life reduce stress, anxiety, and potential depressive episodes. In other words, applying integrative nutrition, or so-called holistic nutrition, via health coaching in dietary consultations can alter behaviors and overcome challenges and struggles to reduce stress and promote weight management [20,21]. Quality of life (QOL) is an additional measure that may be related to stress and the prevalence of obesity. A study has shown[22] that medical students suffer from both anxiety and stress and low quality of life, which may impact eating habits and weight management [20,23,24].
Recent studies have highlighted the impact of text-based mental health coaching in reducing symptoms of depression, anxiety, and stress in working individuals [25,26]. According to a systematic review, digital mental health interventions were effective in reducing symptoms of depression, anxiety, and psychological well-being among college students. Still, few studies have looked at the impact of telehealth or telehealth coaching on Depression, Anxiety, and Stress Scales. Hence, results suggest conducting intervention trials to assess the impact of telemedicine and telehealth coaching on depression, anxiety, and stress. An integrative approach that combines both clinical dietitians and health coaches to support clients in tackling factors associated with their stress during weight loss interventions. Therefore, the current study aim was to investigate the influence of a telenutrition weight loss program supported by telemonitoring and health coaching on Depression Anxiety Stress Scales (DASS-21) among overweight and obese adults living in Saudi Arabia. In addition, we aimed to study the correlation between Depression Anxiety Stress Scales (DASS-21) and anthropometric measures.

2. Materials and Methods

2.1. Study Design, Setting, and Participants

A 6-month two-arm pilot randomized controlled trial was conducted in 2022, starting in January 2022 to August 2023. A detailed study protocol is described previously [22]. This study was approved by the Research Ethics Committee (REC) at the Unit of Biomedical Ethics, the Faculty of Medicine, at King Abdul-Aziz University (approval number: HA-02-j-008), and written informed consent was obtained from all the participants. The inclusion criteria included adults who were aged 20-50 years, female, or male, and obese or overweight. The exclusion criteria included participants who were not familiar with or did not have access to online applications and those who had a history of chronic diseases, such as diabetes, cardiovascular diseases, thyroid dysfunction, or any other endocrine abnormality. Moreover, all participants who joined any dietary interventions or used any type of medication or injections for weight loss in the past 3 months were excluded. Once the eligibility requirements were met, participants were randomly divided into two groups using a randomization website (http://www.randomization.com) and each participant had a specific code and got informed about which group they will be joining. Both the intervention group and the control group have received a hypocaloric tailored diet via telenutrition (remotely) by a registered dietitian (RD) and had several remote follow ups (10 to 14 consultations) until weight loss goals were achieved. Additionally, the intervention group have been provided with integrative nutrition support by an integrative nutrition health coach via Zoom platforms and smartphones (total of 6 sessions). Main aim of the telehealth coaching sessions is to address lifestyle factors associated with obesity and overweight status via a health history session, followed by a goal setting session and continuous guidance and recommendations to tackle specific lifestyle factors that may influence their commitment to the diet [27]. In alignment with telehealth coaching, participants in the intervention group were weekly telemonitored, to record their weights by end of each week (total of 36 weeks). During the 6-month duration of this study, participants from both groups were invited to a total of 3 physical visits at the Food, Nutrition, and Lifestyle unit at the King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia. Their anthropometric measurements and scores on the Depression Anxiety Stress Scales (DASS-21) were collected during each visit.
The sample size was calculated for our primary outcomes of the study, which is changes in weight and anthropometric measures that was shared recently in the Clinical Nutrition ESPEN congress in Milan, 2024 [9]. Sample size calculation was based on a published three-armed randomised controlled study that was carried to measure effectiveness of telemedical coaching on weight loss [5], which was similar to our primary outcome. The present study demonstrates secondary outcomes of the same participants enrolled in the study. Calculation used a power of 80%, significance level of 5%, and a dropout rate of 25%. Thus each group requires a minimum of 35 participant, to achieve significant differences between groups (3.7 kg (2.5 SD) in body weight in comparison with the control group [5]. Thus, we recruited 70 Participants via the university and research center's official social media platforms and then invited for an assessment visit to ensure they met the eligibility requirements via medical and anthropometric measures. Since the current study is a pilot study, we examined between 10% to 30% of the calculated sample size following evident recommendations on pilot study sample size [28]. The reason of conducting a pilot study is due to the nature of the study, which is the first study that conduct a telehealth intervention supported with a holistic approach in weight management, or so called “Integrative nutrition”, to tackle stress in overweight and obese participants. Thus, a total of 50 participants were enrolled in the study to ensure we have a representable sample considering possible attrition rate in both groups. Therefore, a total number of 50 participants were enrolled (25 participants in each group). On Completion of the study, 18 and 12 participants were retained in the control and intervention groups, respectively. Showing that attrition rate was less in the intervention group than in the control group which will be discussed later in the discussion section However, number of participants have been varied in each time point, of which 29 participants have completed 3 months of the trial (18 in the intervention group and 12 in the control group) and 25 participants have completed 6 months of the trial (16 in the intervention group and 9 in the control group). The total of all time-point completers (baseline, 3 months and 6 months) were 15 participants in the intervention group and 8 participants in the control group.

2.2. Depression Anxiety Stress Scales (DASS-21)

This study used the translated Arabic version of the Depression Anxiety Stress Scales (DASS-21) [13] to assess symptoms related to depression, anxiety, and stress. The DASS-21 measured the rating of each symptom present in participants at different time points in this study: at baseline, 3-month, and 6-month visits, respectively. The DASS-21 comprises three subscales: depression, anxiety, and stress. Each subscale includes 7 items to be assessed using a Likert-type scale ranging from 0, which means "does not apply to me at all", and 3, which means "applies to me all the time". High scores on the DASS-21 scale are associated with clinical cases based on the DSM-V (Diagnostic and Statistical Manual of Mental Disorders). Depression is classified as normal (0-9), mild (10-13), moderate (14-20), severe (21-27), or extremely severe (≥ 28); anxiety is classified as normal (0-7), mild (8-9), moderate (10-14), severe (15-19), or extremely severe (≥ 20); and stress is classified as normal (0-14), mild (15-18), moderate (19-25), severe (26-33), and highly severe (≥ 34).

2.3. Statistical Analysis

Data were analyzed using the SPSS program, version 26.0. Continuous data are reported as means and SDs. Categorical variables are reported as frequencies and percentages (%). Independent t-test was used in the descriptive analysis of continuous variables and Chi-square test was used for categorical variables. Repeated measures analysis of variance (ANOVA) was conducted on all time-point completers as the primary analysis. The within-subjects factor was time (baseline, 3 months and 6 months). The between-subjects factor was intervention group (intervention and control) with pairwise comparisons between the time points (baseline vs. 3 months, baseline vs. 6 months). Bonferroni correction was used to adjust p-values for pairwise comparisons. Secondary analysis was done on completers at any time-point to maximize utilization of data. Between-group differences were examined at all time-points using independent t-test. The relationships between changes in the stress, anxiety, and depression scales and various anthropometric measurements were assessed using Spearman’s correlation coefficients. A value of <0.05 (two-sided test) was statistically significant.

3. Results

1. Participants' baseline characteristics
A total of 50 participants started this study, of which 29 completed 3 months of the trial (18 in the intervention group and 12 in the control group) and 25 completed 6 months of the trial (16 in the intervention group and 9 in the control group). The total of all time-point completers (baseline, 3 months and 6 months) were 15 participants in the intervention group and 8 participants in the control group.
Table 1. Participants' baseline characteristics.
Table 1. Participants' baseline characteristics.
Any time-point completers All time-point completers
Intervention
(n = 18)		 Control
(n = 12)		 Intervention
(n = 15)		 Control
(n = 8)
Age (years) mean ± SD 33 ± 11 36 ± 10 33 ± 12 39 ± 9
Gender n (n%)
Men 5 (28%) 6 (54.5%) 5 (33.3%) 5 (62.5%)
Women 13 (72%) 5 (45.5%) 10 (66.7%) 3 (37.5%)
Weight (kg) mean ± SD 90.1 ± 20.7 90.9 ± 21.9 90.5 ± 22.3 94.7 ± 23.9
BMI (kg/m2) mean ± SD 33.2 ± 6.15 33.9 ± 5.58 33.6 ± 6.5 34.4 ± 5.7
BMI (kg/m2) n (n%)
<30 7 (39%) 3 (27%) 6 (40)% 2 (25%)
≥30 11 (61%) 8 (73%) 9 (60%) 6 (75%)
2. Weight, BMI, and WC at all time-points for all time-point completers
While the primary focus of this manuscript is on the psychological outcomes, a brief summary of the weight-related outcomes is provided here (Table 2). Briefly, participants in the intervention group only showed significant reductions in weight, BMI and WC at 3 months from baseline but not at 6 months [9]. The effect of intervention on weight loss and anthropometric measurements will be reported in detail in a separate manuscript [Eid et al., under review].
3. Stress, anxiety, and depression scales at all time-points for all time-point completers
The repeated measures ANOVA for stress, anxiety, and depression scores as measured by the DASS-21 for all time-point completers in the intervention (n=15) and the control groups (n=8) at baseline, 3 months, and 6 months showed that there no significant differences within groups over time for stress, anxiety, or depression (Table 3). In the intervention group, stress and anxiety scores decreased from baseline to 6 months, but these changes were not statistically significant. There was a significant between-group difference in anxiety (p = 0.037, Table 3), however, there were no significant time by intervention interactions for any of the variables.
4. Stress, anxiety, and depression scales at all time-points for completers at any time-point
The analysis of between-group differences in stress, anxiety, and depression scales (Table 1) revealed no significant differences between groups at baseline for any of stress, anxiety or depression. At the 3-month follow-up, the interventiongroup had significantly lower anxiety scores compared to the control group (6.3 ± 6.5 vs. 11.3 ± 6.4, P = 0.047; Table 4), though differences in stress and depression remained non-significant. By the 6-month follow-up, differences in stress, anxiety, and depression between the groups were not statistically significant.
4. Changes in Stress, anxiety, and depression scales at all time points
The changes in the stress, anxiety, and depression scales did not significantly differ between the groups at either 3 or 6 months. The intervention group exhibited reduced stress and anxiety levels, and these changes were not significantly different from the changes observed in the control group. The depression scores showed minor changes over time, with no statistically significant differences between the groups at both follow-up points (Table 4).
5. Correlations between changes in stress, anxiety, and depression scales and anthropometric measurements
The correlations between changes in the stress, anxiety, and depression scales and various anthropometric measurements were mostly weak and non-significant. Changes in weight, BMI, fat percentage, muscle percentage, and visceral fat percentage showed negligible correlations with changes in stress, anxiety, and depression. The only notable finding was the moderate and significant positive correlation between changes in waist circumference and depression (r = 0.455; P = 0.015; Table 5), suggesting that a decrease in waist circumference was associated with a decrease in depression.

4. Discussion

This study examined the effect of a telenutrition program supported by telemonitoring and health coaching on Depression Anxiety Stress Scales (DASS) among overweight and obese adults living in Saudi Arabia. The repeated measures analysis for participants who completed all study time-points revealed no significant differences within groups over time for stress, anxiety, or depression scores. While stress and anxiety scores decreased slightly in the intervention group, these changes were not statistically significant. A significant reduction in anxiety scores only at the 3-month visit in the intervention group compared with the control group in the any-time completers (6.3 ± 6.5 vs. 11.3 ± 6.4; P = 0.047; Table 3). Consistent with this study, a randomized controlled trial was conducted at the International Medical University of Malaysia among workers and students, showing a significant decrease in depression and anxiety scores in the intervention group, who had received text-based coaching from certified mental health professionals [25]. In another study, mobile applications for health coaching and telemonitoring showed significant weight loss and reductions in the Generalized Anxiety Disorder-2 Scale score, including improved sleep patterns after 12 months of intervention [29]. On the contrary, the Whole Health study that measured symptoms of depression among veterans indicates that interventions show more positive outcomes when participants have complex symptom presentations [30]. This explains why only anxiety scores were improved, because anxiety is a more commonly found symptom than depression [31]. The literature also confirms that even though both depression and anxiety are frequent among overweight and obese populations, anxiety is still considered more frequent among overweight/obese women [32]. This may be due to the larger number of women enrolled in our study that were retained in the intervention group (n=13 (72% of the total intervention group); Table 1). While significant improvement within the intervention group after 3 months was observed, the differences between the control and intervention groups were insignificant. This may be because the weight loss method is not necessarily the cause of reduced anxiety, depression, or stress; rather, the cause may be the weight loss itself. Recent research has explained the effect of weight loss and how it may alleviate depression and anxiety by improving metabolic and vascular dysfunction, reducing inflammation, and enhancing neuroimmune status, thereby positively influencing mood and emotional states. Researchers have studied different approaches to weight loss, which have successfully shown that significant weight loss is associated with a significant decrease in depression and anxiety (20). Our findings only show a moderate and significant positive correlation between changes in waist circumference and depression (r = 0.455; P = 0.015; Table 4) among the intervention group. In agreement with our findings, another study have also confirmed such findings A statistically significant association was found between BDI scores, BMI (r=0.16; p=0.018) and WC (r=0.20; p=0.004), which is due to the fact that WC is the anthropometric indicator of obesity and fat distribution in the body [33]. This was also evident in cross sectional studies, such as the Gutenberg Health Study (GHS) were the association of depression and several anthropometric measure (BMI, WC, WHR, WHtR) have shown that the somatic-affective symptoms of depression were significantly associated to changes in anthropometric measures [34] . Indeed, obesity is a significant risk factor for anxiety and depression. Previous cross-sectional studies with larger sample sizes (n= 1624) in Saudi Arabia have shown a significant relation between weight gain and depression, anxiety, and stress scale scores among adolescents and young adults [35]. Another study in Saudi Arabia also confirmed the correlation test carried out in this study, where obese male adolescents had high percentages of stress (44.4%), anxiety (73.2%), and depression (65.7%) compared with normal-weight participants [13]. In addition, researchers who studied different modalities of weight loss successfully showed that significant weight loss was associated with a significant decrease in depression and anxiety [36]. This is the first study conducted in Saudi Arabia that aimed to investigate the effect of remotely integrative nutrition (telenutrition, telemonitoring, and health coaching) on depression, anxiety, and stress scales among overweight and obese participants. Even though a positive attitude toward health-coaching practices by public health students in Saudi Arabia has been revealed, a lack of awareness and insufficient knowledge about health coaching remains [37].
This pilot study had several imitations, which may be considered when implementing the actual study to ensure reliable results. This study had two arms: control and intervention arms. The intervention arm has integrated a holistic strategy or so-called integrative nutrition approach for weight management, which may have impacted the outcomes' accuracy. Surprisingly, attrition rate was also revealed to be lower in the intervention group than the control group, which confirms the intervention postive impact. One of the common reasons to increaes drop out rates from a weight loss study is difficulty to lose weight [38], young age, psychological and behavioural factors [39]. As mentioned previously in our primary outcomes that the intervention group had significant reduction in weight, BMI, fat%, visceral fat, and an increase in muscle % after 3 months when compared to the control group [9]. In addition most of our particioants were adults and also getting holistic support from health coaches on bothpsychological and behaviour aspects of life, following the Institute for Integrative Nutrition [40], which focus on main aspects of life defined as “the circle of life”, which include spirituality, creativity, finances, career, education, health, physical activity, home cooking, home environment, relationships, social life, and joy. This may be the reasons behind lower attrition rate in the intervention group, which resulted in committed particioants. Thus, a three-arm study should be conducted, consisting of telenutrition, telemonitoring, and health coaching, separately, for more applicable conclusions. The sample size was not complete due to this being a pilot study. Hence, a larger number of participants and a longer trial duration (12 months) are suggested, alongside the use of existing telemedicine platforms and telemonitoring devices to empower this study with advanced technology. Furthermore, quality of life (QOL) is worth examining in future work to investigate the specific impact of health coaching on participants. Despite its limitations, this study represents a new and novel approach targeting depression, anxiety, and stress scales, which has never been implemented before. This study also supports previous studies' recommendations emphasizing the importance of introducing health professionals and health-related degrees to telemedicine and health coaching [37] to be aligned with the Health Sector Transformation Program of Vision 2030 [41].

5. Conclusions

In conclusion, this study's findings demonstrate that anxiety scores were significantly improved by integrating telemonitoring and health coaching into dietetic consultations. Additionally, a significant positive correlation was found between changes in waist circumference and depression, which suggests that a reduction in waist circumference results in a reduction in depression among participants who have been telemonitored and health coached. Thus, providing the intervention group with monthly personalized health coaching and weekly telemonitoring had a positive influence on the attrition rate which was lower when comparted to the control group. This will help support participants joining weight loss programs to tackle factors associated with stress that may impact weight loss struggles, in addition to improving the quality of dietetic consultations and enhancing awareness of integrative nutrition and health coaching for health professionals to have a stronger outcome on health and wellbeing of patients and clients. Future studies must investigate the effectiveness of telenutrition, health coaching, and telemonitoring for depression, anxiety, and stress scores in separate arms to obtain a more accurate and clear understanding of the integrative nutrition approach.

Author Contributions

Conceptualization, Noura MS Eid, Ebtisam Al-ofi, Sumia Enani, Raneem Saqr, and Karimah Qutah; data curation, Sumia Enani; formal analysis, Sumia Enani; funding acquisition, Noura MS Eid, Ebtisam Al-ofi, Sumia Enani, Rana Mosli, Raneem Saqr, Karimah Qutah, and Sara Eid; investigation, Ebtisam Al-ofi, Karimah Qutah, and Sara Eid; methodology, Noura MS Eid, Sumia Enani, Raneem Saqr, and Sara Eid; project administration, Noura MS Eid; resources, Rana Mosli; supervision, Noura MS Eid; validation, Rana Mosli and Raneem Saqr; visualization, Rana Mosli; writing—original draft, Noura MS Eid; writing—review and editing, Noura MS Eid, Ebtisam Al-ofi, Sumia Enani, Rana Mosli, Raneem Saqr, Karimah Qutah, and Sara Eid. All authors have read and agreed to the published version of this manuscript.

Funding

This research was funded by the Institutional Fund Projects under grant no. IFPRC-206-141-2020.

Institutional Review Board Statement

This study was conducted per the Declaration of Helsinki and approved by the Institutional Review Board of the Research Ethics Committee (REC) at the Unit of Biomedical Ethics, the Faculty of Medicine, at King Abdul-Aziz University, Jeddah, Saudi Arabia (HA-02-j-008).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The data presented in this study are available upon reasonable request from the corresponding author (ooaeid2@kau.edu.sa).

Acknowledgments

This research work was funded by Institutional Fund Projects under grant no (IFPRC-206-141-2020). Therefore, authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz University, Jeddah, Saudi Arabia.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. J., R., Integrative Nutrition: A Whole-Life Approach to Health and Happiness. 5th ed. 2021: Integrative Nutrition LLC.
  2. Gnagnarella, P.;Ferro, Y.;Monge, T.;Troiano, E.;Montalcini, T.;Pujia, A.;Mazza, E. Telenutrition: Changes in Professional Practice and in the Nutritional Assessments of Italian Dietitian Nutritionists in the COVID-19 Era. Nutrients. 2022, 14.
  3. Noah, B.;Keller, M.S.;Mosadeghi, S.;Stein, L.;Johl, S.;Delshad, S.;Tashjian, V.C.;Lew, D.;Kwan, J.T.;Jusufagic, A.;Spiegel, B.M.R. Impact of remote patient monitoring on clinical outcomes: an updated meta-analysis of randomized controlled trials. NPJ Digit Med. 2018, 1, 20172.
  4. Luley, C.;Blaik, A.;Götz, A.;Kicherer, F.;Kropf, S.;Isermann, B.;Stumm, G.;Westphal, S. Weight loss by telemonitoring of nutrition and physical activity in patients with metabolic syndrome for 1 year. J Am Coll Nutr. 2014, 33, 363-74.
  5. Kempf, K.;Röhling, M.;Martin, S.;Schneider, M. Telemedical coaching for weight loss in overweight employees: a three-armed randomised controlled trial. BMJ Open. 2019, 9, e022242.
  6. Conn, S.;Curtain, S. Health coaching as a lifestyle medicine process in primary care. Aust J Gen Pract. 2019, 48, 677-680.
  7. Johnson, K.E.;Alencar, M.K.;Coakley, K.E.;Swift, D.L.;Cole, N.H.;Mermier, C.M.;Kravitz, L.;Amorim, F.T.;Gibson, A.L. Telemedicine-Based Health Coaching Is Effective for Inducing Weight Loss and Improving Metabolic Markers. Telemed J E Health. 2019, 25, 85-92.
  8. Hesseldal, L.;Christensen, J.R.;Olesen, T.B.;Olsen, M.H.;Jakobsen, P.R.;Laursen, D.H.;Lauridsen, J.T.;Nielsen, J.B.;Søndergaard, J.;Brandt, C.J. Long-term Weight Loss in a Primary Care-Anchored eHealth Lifestyle Coaching Program: Randomized Controlled Trial. J Med Internet Res. 2022, 24, e39741.
  9. Eid, N.;Al-ofi, E.;Enani, S.;Mosli, R.;Saqr, S.;Qutah, K.;Eid, S. Corrigendum to :A pilot randomized controlled trial of a telenutrition weight loss program supported with telemonitoring and health coaching in overweight and obese adults. Clinical Nutrition ESPEN. 2024, 63, 1312-1322.
  10. Almubark, R.A.;Alqahtani, S.A. Epidemiology of obesity and control interventions in Saudi Arabia. East Mediterr Health J. 2023, 29, 987-994.
  11. Alhusseini, N.;Alsinan, N.;Almutahhar, S.;Khader, M.;Tamimi, R.;Elsarrag, M.I.;Warar, R.;Alnasser, S.;Ramadan, M.;Omair, A. Dietary trends and obesity in Saudi Arabia. Frontiers in Public Health. 2024, 11, 1326418.
  12. Safaei, M.;Sundararajan, E.A.;Driss, M.;Boulila, W.;Shapi'i, A. A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity. Comput Biol Med. 2021, 136, 104754.
  13. Alsaleem, M.A. Depression, Anxiety, Stress, and Obesity among Male Adolescents at Abha City, Southwestern Saudi Arabia. The Journal of Genetic Psychology. 2021, 182, 488-494.
  14. Alosaimi, F.D.;Kazim, S.N.;Almufleh, A.S.;Aladwani, B.S.;Alsubaie, A.S. Prevalence of stress and its determinants among residents in Saudi Arabia. Saudi Med J. 2015, 36, 605-12.
  15. Kappes, C.;Stein, R.;Körner, A.;Merkenschlager, A.;Kiess, W. Stress, Stress Reduction and Obesity in Childhood and Adolescence. Hormone Research in Paediatrics. 2023, 96, 88-96.
  16. Dakanalis, A.;Mentzelou, M.;Papadopoulou, S.K.;Papandreou, D.;Spanoudaki, M.;Vasios, G.K.;Pavlidou, E.;Mantzorou, M.;Giaginis, C. The Association of Emotional Eating with Overweight/Obesity, Depression, Anxiety/Stress, and Dietary Patterns: A Review of the Current Clinical Evidence. Nutrients. 2023, 15, 1173.
  17. Dougherty, E.N.;Goldschmidt, A.B.;Johnson, N.K.;Badillo, K.;Engel, S.G.;Haedt-Matt, A.A. Gender differences in the relation between interpersonal stress and momentary shape and weight concerns in youth with overweight/obesity. Body Image. 2022, 40, 249-255.
  18. Pearl, R.L.;White, M.A.;Grilo, C.M. Weight bias internalization, depression, and self-reported health among overweight binge eating disorder patients. Obesity. 2014, 22, E142-E148.
  19. Chew, H.S.J.;Rajasegaran, N.N.;Chin, Y.H.;Chew, W.S.N.;Kim, K.M. Effectiveness of Combined Health Coaching and Self-Monitoring Apps on Weight-Related Outcomes in People With Overweight and Obesity: Systematic Review and Meta-analysis. J Med Internet Res. 2023, 25, e42432.
  20. Sieczkowska, S.M.;de Lima, A.P.;Swinton, P.A.;Dolan, E.;Roschel, H.;Gualano, B. Health coaching strategies for weight loss: a systematic review and meta-analysis. Advances in nutrition. 2021, 12, 1449-1460.
  21. Ramos-Lopez, O.;Martinez, J.A.;Milagro, F.I. Holistic Integration of Omics Tools for Precision Nutrition in Health and Disease. Nutrients. 2022, 14.
  22. Lattie, E.G.;Adkins, E.C.;Winquist, N.;Stiles-Shields, C.;Wafford, Q.E.;Graham, A.K. Digital Mental Health Interventions for Depression, Anxiety, and Enhancement of Psychological Well-Being Among College Students: Systematic Review. J Med Internet Res. 2019, 21, e12869.
  23. Gan, G.G.;Yuen Ling, H. Anxiety, depression and quality of life of medical students in Malaysia. Med J Malaysia. 2019, 74, 57-61.
  24. Sherman, R.P.;Petersen, R.;Guarino, A.J.;Crocker, J.B. Primary care–based health coaching intervention for weight loss in overweight/obese adults: A 2-year experience. American Journal of Lifestyle Medicine. 2019, 13, 405-413.
  25. Lim, Y.S.;Quek, J.H.;Ching, X.W.;Lim, D.T.R.;Lim, K.G.;Thuraisingham, C.;George, P.P. Efficacy of a Text-Based Mental Health Coaching App in Improving the Symptoms of Stress, Anxiety, and Depression: Randomized Controlled Trial. JMIR Form Res. 2023, 7, e46458.
  26. Zhang, R.;Nicholas, J.;Knapp, A.A.;Graham, A.K.;Gray, E.;Kwasny, M.J.;Reddy, M.;Mohr, D.C. Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study. J Med Internet Res. 2019, 21, e15644.
  27. Rosenthal, J., Integrative Nutrition: A Whole-Life Approach to Health and Happiness. 2024: Greenleaf Book Group.
  28. Kunselman, A.R. A brief overview of pilot studies and their sample size justification. Fertility and Sterility. 2024, 121, 899-901.
  29. Ju, H.;Kang, E.;Kim, Y.;Ko, H.;Cho, B. The Effectiveness of a Mobile Health Care App and Human Coaching Program in Primary Care Clinics: Pilot Multicenter Real-World Study. JMIR Mhealth Uhealth. 2022, 10, e34531.
  30. Reed, D.E., 2nd;Chen, C.;Harvey, K.;Engel, C.C.;Kroenke, K.;Defaccio, R.;Coggeshall, S.;Taylor, S.L.;Bokhour, B.G.;Zeliadt, S.B. Utilization of Whole Health and Longitudinal Outcomes After Screening Positive for Possible Depression Documented in Veterans Health Administration's Electronic Health Record. J Integr Complement Med. 2023, 29, 781-791.
  31. Katon, W.;Roy-Byrne, P.P. Mixed anxiety and depression. Journal of abnormal Psychology. 1991, 100, 337.
  32. Sharafi, S.E.;Garmaroudi, G.;Ghafouri, M.;Bafghi, S.A.;Ghafouri, M.;Tabesh, M.R.;Alizadeh, Z. Prevalence of anxiety and depression in patients with overweight and obesity. Obesity Medicine. 2020, 17, 100169.
  33. Moreira, R.O.;Marca, K.;Appolinario, J.;Coutinho, W. Increased waist circumference is associated with an increased prevalence of mood disorders and depressive symptoms in obese women. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity. 2007, 12, 35-40.
  34. Wiltink, J.;Michal, M.;Wild, P.S.;Zwiener, I.;Blettner, M.;Münzel, T.;Schulz, A.;Kirschner, Y.;Beutel, M.E. Associations between depression and different measures of obesity (BMI, WC, WHtR, WHR). BMC psychiatry. 2013, 13, 1-7.
  35. Ali, A.A.;Aqeel, A.A.;Shami, M.O.;Khodari, B.H.;Alqassim, A.Y.;Alessa, A.M.;Alhazm, F.I.;Alhazmi, Y.A.;Sumayli, A.Y.;Arishi, F.H.;Muaddi, M.A.;Alharbi, A.A.;Almaghrabi, H.A.;Alhazmi, A.H. Relationship Between Depression, Anxiety, Stress, and Weight Self-Stigma Among Youths in Saudi Arabia: A Nationwide Study. Cureus. 2024, 16, e54125.
  36. Pazzagli, C.;Mazzeschi, C.;Laghezza, L.;Reboldi, G.P.;De Feo, P. Effects of a Multidisciplinary Lifestyle Intervention for Obesity on Mental and Physical Components of Quality of Life: The Mediatory Role of Depression. Psychological Reports. 2013, 112, 33-46.
  37. Quronfulah, B.S.;Alhasani, S.A.;Alzhrani, T.S.;Babalghith, R.M.;Qari, L.E.;Nour, M.O. Awareness, Knowledge, and Attitudes Regarding Health Coaching Among Umm Al-Qura University Public Health Students. Cureus. 2023, 15, e48135.
  38. Hemmingsson, E.;Johansson, K.;Eriksson, J.;Sundström, J.;Neovius, M.;Marcus, C. Weight loss and dropout during a commercial weight-loss program including a very-low-calorie diet, a low-calorie diet, or restricted normal food: observational cohort study123. The American Journal of Clinical Nutrition. 2012, 96, 953-961.
  39. Moroshko, I.;Brennan, L.;O'Brien, P. Predictors of dropout in weight loss interventions: a systematic review of the literature. Obesity Reviews. 2011, 12, 912-934.
  40. Rosenthal, J., Integrative Nutrition: A Whole-Life Approach to Health and Happiness. 2021.
  41. Alasiri, A.A.;Mohammed, V. Healthcare Transformation in Saudi Arabia: An Overview Since the Launch of Vision 2030. Health Serv Insights. 2022, 15, 11786329221121214.
Table 2. Mean, SD and statistical significance for within and between-group differences in weight, BMI and WC at all time-points for all time-point completers.
Table 2. Mean, SD and statistical significance for within and between-group differences in weight, BMI and WC at all time-points for all time-point completers.
Baseline
Mean (SD)		 3 months
Mean (SD)		 6 months
Mean (SD)		 Within-group analysis
Baseline vs. 3 months
P-value 		Within-group analysis
Baseline vs. 6 months
P-value 		Between group analysis
Intervention vs. control
Weight
 Intervention 91.5 (22.3) 87.3 (20.7) 88.5 (22.9) 0.015 0.227 0.620
 Control 94.7 (23.9) 94.2 (25) 93.4 (24.5) 1 0.696
BMI
 Intervention 33.6 (6.5) 32 (6.6) 32.4 (7.5) 0.012 0.253 0.624
 Control 34.4 (5.7) 34.1 (6) 33.8 (5.7) 1 0.528
WC
 Intervention 97 (18) 92 (16) 93 (16) 0.002 0.112 0.23
 Control 106 (20) 103 (19) 101 (20) 0.081 0.217
Data is expressed as mean (SD) for DASS-21 scores for completers of the study (n=15) in the intervention and (n=8) in the control group.
P-values were obtained through repeated measures analysis of variance (ANOVA) with pairwise comparisons between the time points. Bonferroni correction was used to adjust p-values for pairwise comparisons.
Table 3. Mean, SD and statistical significance for within and between-group differences in stress, anxiety and depression scales at all time-points for all time-point completers.
Table 3. Mean, SD and statistical significance for within and between-group differences in stress, anxiety and depression scales at all time-points for all time-point completers.
Baseline
Mean (SD)		 3 months
Mean (SD)		 6 months
Mean (SD)		 Within-group analysis
Baseline vs. 3 months
P-value 		Within-group analysis
Baseline vs. 6 months
P-value 		Between group analysis
Intervention vs. control
Stress
 Intervention 12.93 (9.94) 12.93 (8.31) 9.33 (11.36) 1 0.621 0.09
 Control 18.5 (9.37) 16.25 (13.41) 20.25 (10.55) 1 1
Anxiety
 Intervention 8.93 (7.48) 6.53 (6.74) 6.53 (8.6) 0.415 0.51 0.037
 Control 14 (8.07) 12 (7.56) 15.5 (8.93) 1 1
Depression
 Intervention 8.8 (9.19) 8.67 (7.62) 7.2 (10.41) 1 1 0.129
 Control 11.75 (8.17) 13.25 (10.08) 15 (10.03) 1 1
Data is expressed as mean (SD) for DASS-21 scores for completers of the study (n=15) in the intervention and (n=8) in the control group.
P-values were obtained through repeated measures analysis of variance (ANOVA) with pairwise comparisons between the time points. Bonferroni correction was used to adjust p-values for pairwise comparisons.
Table 4. Mean, SD, and statistical significance for between-group differences in stress, anxiety, and depression scales at all time points for completers at any time-point.
Table 4. Mean, SD, and statistical significance for between-group differences in stress, anxiety, and depression scales at all time points for completers at any time-point.
Variable/Time Point Group n Mean SD P-Value
Stress
Baseline Intervention 18 13.1 10.1 0.327
Control 12 17 11
3 months Intervention 18 12.6 7.9 0.691
Control 12 14 11.9
6 months Intervention 16 11.3 13.4 0.222
Control 9 18 12
Anxiety
Baseline Intervention 18 8.4 7.1 0.157
Control 12 12.7 8.8
3 months Intervention 18 6.3 6.5 0.047*
Control 12 11.3 6.4
6 months Intervention 16 7.8 9.6 0.115
Control 9 14.2 9.2
Depression
Baseline Intervention 18 10.2 10.2 0.988
Control 12 10.2 8.4
3 months Intervention 18 8.7 7.4 0.407
Control 12 11.2 8.8
6 months Intervention 16 8.8 11.8 0.319
Control 9 13.6 10.3
-
Data are expressed as means (SD) for DASS-21 scores.
-
Significant differences in DASS-21 scores in each study arm at each time point are shown in bold (P-values: a P > 0·05, * P < 0·05, ** P < 0·01, and *** P < 0·001)
Table 4. Mean, SD, and statistical significance for between-group differences in changes in stress, anxiety, and depression scales from baseline at 3 and 6 months.
Table 4. Mean, SD, and statistical significance for between-group differences in changes in stress, anxiety, and depression scales from baseline at 3 and 6 months.
Variable/Time Point Group n Mean SD P-Value
Stress
Δ at 3 months Intervention 18 -0.56 10.31 0.533
Control 12 -3 10.53
Δ at 6 months Intervention 16 -2.25 11.52 0.616
Control 9 0.22 11.94
Anxiety
Δ at 3 months Intervention 18 -2.11 5.51 0.746
Control 12 -1.33 7.55
Δ at 6 months Intervention 16 -1.5 7.17 0.447
Control 9 1.11 9.6
Depression
Δ at 3 months Intervention 18 -1.56 8.91 0.449
Control 12 1 8.97
Δ at 6 months Intervention 16 -0.25 11.31 0.587
Control 9 2.22 9.72
-
Data are expressed as means (SD) for DASS-21 scores.
-
Significant differences in DASS-21 scores changes in each study arm at 3 and 6 months are shown in bold (P-values: a P > 0·05, * P < 0·05, ** P < 0·01, and *** P < 0·001).
Table 5. Correlations between changes in stress, anxiety, and depression scales and various anthropometric measurements.
Table 5. Correlations between changes in stress, anxiety, and depression scales and various anthropometric measurements.
Δ Stress Δ Anxiety Δ Depression
r P-Value r P-Value r P-Value
Δ Weight -0.021 0.915 -0.061 0.759 0.253 0.194
Δ BMI -0.07 0.724 -0.071 0.721 0.207 0.291
Δ Fat % -0.218 0.266 0.057 0.774 0.065 0.743
Δ Muscle % 0.279 0.168 -0.074 0.719 0.103 0.618
Δ Visceral fat % -0.152 0.459 -0.329 0.101 0.046 0.823
Δ WC 0.104 0.597 -0.202 0.302 0.455 0.015*
-
n = 30
-
Significant correlation analysis for the relationship between changes in stress, anxiety, and depression scores and various anthropometric measurements after 3 months of intervention
-
Significant correlation analyses are shown in bold (P-values: a P > 0·05, * P < 0·05, ** P < 0·01, and *** P < 0·001).
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