Improving Physical Activity and Psychological Well-Being in Type 2 Diabetes: An Educational Intervention in Urban Primary Care

Improving Physical Activity and Psychological Well-Being in Type 2 Diabetes: An Educational Intervention in Urban Primary Care | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Improving Physical Activity and Psychological Well-Being in Type 2 Diabetes: An Educational Intervention in Urban Primary Care Chetan M Suresh, Suraj B Manjunath, Mounika Sree Manivasagan, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8624080/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Type 2 diabetes (T2DM) is associated with physical inactivity and psychological distress. Community-based interventions addressing both physical activity and mental health remain understudied in low-resource urban settings in India. Objectives To assess the feasibility and preliminary effects of a one-on-one educational intervention promoting physical activity on psychological well-being and self-reported physical activity levels among physically inactive T2DM patients in an urban primary health center in South India. Methods A quasi-experimental pre-post study recruited 132 physically inactive (≤ 150 minutes/week moderate-intensity activity) T2DM patients from Saraswathipuram Urban Primary Health Center, Mysuru. Participants received a single one-on-one counselling session delivered via house-to-house visits using Information, Education, and Communication materials. Psychological well-being was assessed using the Psychological General Well-Being Index (PGWBI) at baseline and 4 weeks post-intervention. Physical activity was assessed via structured questionnaire based on WHO Global Physical Activity Questionnaire. Effect sizes (Cohen's d) and proportional changes in outcomes were calculated. Results Following the intervention, participant-reported physical activity engagement increased markedly (p < 0.001): the proportion reporting no activity declined from 72% to 27.3%. Across all six PGWBI domains, statistically significant improvements were observed (p < 0.001). Mean PGWBI positive well-being increased from 9.20 to 11.67 (Cohen's d = 0.59), self-control from 7.90 to 9.17 (d = 0.38), general health from 9.72 to 11.26 (d = 0.54), and vitality from 10.00 to 12.20 (d = 0.85). The proportion of participants with good psychological well-being increased from 16.7% to 42.4%. Conclusions In this study, a low-cost, single-session house-based educational intervention was associated with participant-reported increases in physical activity and improvements in psychological well-being among urban T2DM patients. Results suggest feasibility for implementation in resource-limited primary health centers. Longer-term follow-up with control groups and objective outcome measures such as HbA1c, accelerometry, are required to establish durability and clinical significance. Type 2 diabetes Physical activity Psychological well-being Urban health center Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION Diabetes mellitus represents one of the most significant non-communicable disease challenges globally, with particular severity in low- and middle-income countries (LMICs). The global diabetes epidemic continues to accelerate, approximately 537 million adults aged 20–79 years were living with diabetes in 2021, projected to reach 643 million by 2030 and 783 million by 2045 [1]. In India, approximately 101 million individuals currently live with diabetes, and this number is expected to rise to 124.9 million by 2045 [2, 3]. Alarmingly, more than 50% of affected individuals remain unaware of their condition, eventually increasing complications risk [4]. Physical inactivity is a known modifiable risk factor for both diabetes and poor glycaemic control. The World Health Organization defines physical activity as any bodily movement requiring energy expenditure, encompassing walking, cycling, sports, dancing, and structured exercise [5]. Present guidelines recommend that adults with T2DM engage in 150 to 300 minutes of moderate-intensity aerobic activity per week, or alternatively 75–150 minutes of vigorous-intensity activity [6, 7]. Despite these evidence-based recommendations, one in four adults globally fail to achieve the prescribed activity levels, with particularly high inactivity rates among diabetic individuals in urban LMIC settings [5]. Physical inactivity is not just a consequence of the condition, but it actively propels diabetes toward a severe and persistent state of mismanagement. Psychological well-being, including positive emotional states, life satisfaction, personal growth, and stress management capacity, emerges as a critical and often-neglected dimension of diabetes care, specifically in resource-constrained settings. The relationship between psychological status and diabetes outcomes is bidirectional as poor well-being predicts worse glycaemic control and higher mortality, while positive psychological states predict improved treatment adherence and better long-term health [8]. Growing evidence suggests that physical activity interventions can simultaneously improve both physical activity levels and psychological outcomes through multiple pathways: direct neurobiological effects such as enhanced neurotrophic factors, increased neural plasticity, improved self-efficacy, and enhanced social connection through activity participation [9]. However, it remains unclear exactly how these improvements occur and whether they are durable over time in the context of urban populations in LMICs. Although community-based physical activity promotion has shown promise in diabetes management, a significant gap persists in urban LMIC settings regarding integrated interventions addressing both physical and mental health outcomes. Most intervention models typically employ extended protocols or require attendance at clinical facilities. This creates a significant gap in the literature regarding minimal-contact, home-delivered strategies within resource-constrained primary care environments. This is important for urban India, where primary health centers serve predominantly socioeconomically disadvantaged populations with high disease burden but limited access to specialized behavioral health services. The present study addresses this gap by evaluating the feasibility and preliminary effects of a single-session, house-delivered educational intervention promoting physical activity on psychological well-being outcomes physically inactive T2DM patients within an urban primary health center (UPHC) in South India. We hypothesized that even modest increases in physical activity, achieved through low-cost counselling delivered within community settings, might be associated with improvements in psychological well-being, offering implementation models for resource-constrained health systems. 2. MATERIALS AND METHODS 2.1. Study Design and Setting This was a quasi-experimental pre-post feasibility study conducted in urban Mysuru, Karnataka, India. Mysuru represents a rapidly urbanizing Tier-2 city where environmental determinants play a key role in the lifestyle management of T2DM. The region has a Tropical Savanna climate, and underscores the critical need for green spaces to ensure thermal comfort and sustain adherence to physical activity patterns. The study was conducted within the Saraswathipuram UPHC catchment, a mixed-use zone featuring the restorative landscape of Kukkarahalli Lake, which offers vital opportunities for both recreation and psychological stress reduction. This setting, combined with a high effective literacy rate, provides a unique context for examining the intersection of urban planning, patient well-being, and health behaviour. The catchment area of the UPHC includes four municipal wards; Gangotri, Jayalakshmipuram, Kuvempunagar, and Saraswathipuram (Fig. 1 .) with a population of 41,377. The UPHC maintains a diabetes registry of patients receiving routine care through the National Diabetes Prevention and Control Program. The setting was selected to represent typical resource-limited urban primary care in India, with single trained health worker capacity and minimal dedicated mental health services. 2.2 Study Population and Sampling The inclusion criteria were adults aged ≥ 18 years with Type 2 Diabetes Mellitus verified by UPHC records, defined as physically inactive (performing < 75 minutes vigorous-intensity or < 150 minutes moderate-intensity physical activity weekly), able to provide informed written consent, and available for follow-up assessment. The exclusion Criteria were the individuals with physical disabilities or bedridden status that prevents physical activity participation; documented severe psychiatric conditions, those unable or unwilling to provide informed consent; or unavailable for baseline assessment. 2.3. Sampling and Recruitment: Of 621 registered diabetic patients assessed for eligibility, 430 were excluded as they did not meet the inclusion criteria; 149 were unavailable during the data collection period, 124 were already physically active, and 157 had severe physical limitations. Out of the remaining 191 eligible candidates, 51 declined participation and 8 were lost to follow-up, yielding a final analytical sample of 132 participants (Fig. 2 ). Recruitment was conducted during routine health center visits and supplementary house visits, employing a registry-based sampling approach. 2.4 Intervention Description: Participants were given a single one-on-one educational counselling session delivered during home visits, typically lasting 30–45 minutes. The intervention was grounded in Social Cognitive Theory, targeting self-efficacy, outcome expectations, and perceived barriers to physical activity [10]. Counselling content included: (1) personalized discussion of diabetes-related health benefits of physical activity, (2) identification of individually feasible activity options (primarily walking, given urban setting constraints), (3) practical strategies for integrating activity into daily routines, (4) identification and problem-solving of perceived barriers (time, fatigue, joint pain, safety concerns, social norms), and (5) discussion of accessibility of urban green spaces for activity. Visual Information, Education, and Communication (IEC) materials (1-page infographics with pictorial representations of various activity types, local green spaces, and motivational messaging) were provided in Kannada language. No ongoing follow-up contact or reinforcement sessions were provided; participants were advised to aim for progressive increases toward ≥ 150 minutes/week moderate-intensity activity. 2.5 Outcome Measures 2.5.1 Primary Outcome : Psychological Well-Being- The Psychological General Well-Being Index (PGWBI) is a validated 22-item self-report instrument assessing six domains: anxiety, depression, positive well-being, self-control, general health, and vitality [11]. Each item is scored 0–5, with domain scores calculated as item sums or means depending on domain. The PGWBI demonstrates strong reliability (Cronbach's α = 0.77–0.97) and validity in T2DM populations [12]. A PGWBI total score ≥ 73 is typically categorized as "good well-being," while < 73 indicates "moderate to severe distress". The instrument was administered in validated Kannada translation by trained health workers using structured interview format. 2.5.2 Secondary Outcome : Physical Activity- Self-reported physical activity was assessed via structured interview using questions adapted from the WHO Global Physical Activity Questionnaire (GPAQ) framework. Participants reported weekly frequency (days/week) and duration (minutes/week) of activity in categories: none, 1–2 days, 3–4 days, or 5–6 days/week; and duration in minutes. No objective physical activity measurement such as accelerometry, step counters were employed. 2.6 Study Procedures and Data Collection Trained health workers conducted baseline assessments immediately prior to intervention delivery, including demographic characteristics such as age, sex, education, occupation, marital status, and clinical history including diabetes duration, medications, and outcome measures. Interventions were delivered within 1 week of baseline assessment. Post-intervention assessments were conducted exactly 4 weeks after intervention delivery using identical instruments and procedures. All data collection occurred in participants' residence or at the health center, according to participant preference. 2.7 Statistical Analysis Descriptive statistics like frequencies, percentages, means with standard deviations for normally distributed variables; medians with interquartile ranges for non-normally distributed variables, characterized the study population and baseline-to-post-test changes. Normality was assessed using Kolmogorov-Smirnov tests. For normally distributed PGWBI domains (positive well-being, self-control, general health, vitality), paired t-tests compared baseline and post-intervention scores. For non-normally distributed domains (anxiety, depression), Wilcoxon signed-rank tests were employed. Between-group effect sizes were calculated as Cohen's d; $$\:d=\frac{(Mean\:Post-Mean\:Pre)\:\:}{SD\:Pooled}$$ Statistical significance was defined as p < 0.05 (two-tailed). Analyses were performed using SPSS version 22.0. 2.8 Ethical Considerations Ethical approval was obtained from the Institutional Ethics Committee of JSS Medical College, JSS Academy of Higher Education and Research (No. JSS/MC/PG/91/2022-23, dated March 31, 2023). Written informed consent was obtained from all participants prior to enrolment, with study information provided in Kannada and English. Confidentiality was maintained through de-identification of data and secure data storage. Participants could withdraw at any time without consequences. 3 RESULTS 3.1 Participant Characteristics Table 1 Socio-demographic characteristics of Study Participants (n = 132) Variable Category Frequency Percentage (%) Gender Female 73 55.3 Male 59 44.7 Age Group (in years) Below 46 14 10.6 46- 55 37 28 56- 65 57 43.1 Above 65 24 18.2 Educational Level Illiterates 52 39.4 Primary school 20 15.2 High school 26 19.7 Intermediate 16 13.6 Graduation 18 12.1 Current Occupation Unemployed 82 62.1 Unskilled 4 3 Skilled 21 15.9 Arithmetic skill jobs 19 14.4 Professionals 6 4.5 The sample comprised 132 T2DM patients with mean age 58.2 years (SD = 9.7), 55.3% were female (Table 1 ). Baseline educational attainment was low: 39.4% illiterate, 15.2% with primary education, and only 12.1% with college education. Occupational status reflected socioeconomic disadvantage with 62.1% unemployed, 15.9% skilled workers, and 14.4% in clerical roles. Mean diabetes duration was approximately 7.3 years (range 1–18 years). No baseline differences in demographic characteristics were detected between participants lost to follow-up (n = 8) and those completing post-intervention assessment (n = 132), though sample size precluded formal statistical comparison. 3.2 Physical Activity Outcomes Baseline physical activity levels revealed remarkable inactivity: 72% reported zero weekly physical activity, 23.5% engaged in activity 3–4 days/week, and none achieved 5–6 days/week (Table 2 ). Regarding activity duration, 72% reported no activity; only 13.6% and 14.4% engaged in 60–90 and 120–135 minutes weekly, respectively. Table 2 Distribution of the study participants based on Physical Activity Pre & Post Intervention (n = 132) Physical Activity Variable Category Before (n, %) After (n, %) Frequency of Weekly Physical Activity Engagement Not utilizing 95 (72) 36 (27.3) 1–2 days 6 (4.5) 19 (14.4) 3–4 days 31 (23.5) 61 (46.2) 5–6 days 0 (0.0) 16 (12.1) Duration of Physical Activity per week in minutes Not utilizing 95 (72) 36 (27.3) 60–90 minutes 18 (13.6) 41 (31.1) 120–135 minutes 19 (14.4) 40 (30.3) > 149 minutes 0 (0.0) 15 (11.4) Post-intervention (4 weeks), substantial self-reported improvements were observed (p < 0.001). Proportions reporting no weekly activity declined to 27.3%, while those engaging in activity 3–4 days/week increased to 46.2%, and 12.1% reported 5–6 days/week activity (a change of 46.2 percentage points). Regarding duration, physical inactivity fell to 27.3%; 31.1% reported 60–90 minutes weekly, 30.3% reported 120–135 minutes, and 11.4% exceeded 150 minutes/week. These changes represent substantial shifts in activity self-reporting, though the magnitude and sustainability remain uncertain given the self-report methodology and short follow-up. 3.3 Psychological Well-Being Outcomes Pre-post PGWBI domain changes are presented in Table 3 . Across all six domains, statistically significant improvements were observed (p < 0.001 for all domains). For anxiety (non-normally distributed), median scores increased from 10 (IQR 7–14) to 14 (IQR 9–17), corresponding to Wilcoxon signed-rank test p < 0.001. Depression median scores increased from 7 (IQR 4–10) to 9 (IQR 5–11), p < 0.001. Table 3 Comparison of pre and post-test of Psychological General Well-Being Index (n = 132) PGWBI Domain Before After p-value Anxiety 10 (7–14) 14 (9–17) < 0.001 * Depression 7 (4–10) 9 (5–11) < 0.001 * Positive Wellbeing 9.20 ± 4.24 11.67 ± 4.08 < 0.001 * Self-control 7.90 ± 3.36 9.17 ± 3.25 < 0.001 ** General Health 9.72 ± 2.85 11.26 ± 2.85 < 0.001 ** Vitality 10.00 ± 2.59 12.20 ± 2.73 < 0.001 ** Note : * Wilcoxon Signed-Rank Test was used for non-normally distributed domains (Anxiety and Depression); ** Paired t-test was applied for the normally distributed domain (Positive Wellbeing, Self-control, General Health, Vitality). For normally distributed domains, paired t-tests revealed: positive well-being increased from mean 9.20 (SD = 4.24) to 11.67 (SD = 4.08), representing an absolute increase of 2.47 points and Cohen's d = 0.59 with small-to-moderate effect size. Self-control increased from 7.90 (SD = 3.36) to 9.17 (SD = 3.25), d = 0.38 with small effect. General health increased from 9.72 (SD = 2.85) to 11.26 (SD = 2.85), d = 0.54 with small-to-moderate effect. Vitality increased from 10.00 (SD = 2.59) to 12.20 (SD = 2.73), d = 0.85 moderate effect. All differences achieved statistical significance. The proportion of participants categorized as having "good psychological well-being" (PGWBI total ≥ 73) increased from 16.7% at baseline to 42.4% post-intervention as in Fig. 3 , an absolute increase of 25.7 percentage points and relative risk increase of 2.54-fold. Conversely, those experiencing “moderate to severe distress" (PGWBI < 73) declined from 83.3% to 57.6%. 4. DISCUSSION This quasi-experimental feasibility study illustrates statistically significant associations between a single-session, home-delivered educational intervention and self-reported increases in physical activity and in psychological well-being among physically inactive T2DM patients in an urban LMIC primary health center setting. The intervention was feasible to implement with minimal resource requirements and demonstrated acceptable retention (94.3%). However, substantial methodological limitations preclude definitive causal conclusions and warrant transparent discussion. 4.1 Physical Activity Outcomes in Context The significant decline in reported inactivity (72% to 27.3%) and increases in activity frequency/duration align qualitatively with findings from similar community-based interventions in diabetic populations. Xu et al [13] observed increased urban green space utilization and physical activity engagement following behavioral counselling in a Chinese diabetes program. Hong et al [14] reported that approximately half of participants receiving structured counselling achieved 60–120 minutes of weekly activity. Zlender and Thompson [15] documented that approximately 22% of program participants progressed to daily physical activity following community-based promotion initiatives. These parallel findings suggest that culturally-adapted, community-focused behavioral strategies can mobilize physical activity among previously sedentary populations. However, it is important to acknowledge significant limitations regarding how physical activity was measured. Self-reported physical activity demonstrates known limitations such as the correlation with objective measures is weak-to-moderate (r ≈ 0.14–0.17 for moderate-vigorous activity), and interventions targeting activity behaviour systematically increase over-reporting by 8–19% due to social desirability bias and demand characteristics [16]. The WHO GPAQ framework, on which our instrument was based, is documented to systematically overestimate activity compared to accelerometer measurement [17]. Thus, reported activity improvements may substantially overestimate true behavioral change. The 4-week follow-up period is insufficient to assess sustainability as behavioral change literature indicates that activity gains often decline without ongoing reinforcement, particularly in single-contact intervention models [18]. We cannot determine whether observed changes represent genuine behaviour adoption or temporary social desirability response to study participation. Notably, the study did not measure glycaemic outcomes or other clinical markers, thus, metabolic significance of reported activity improvements remains unvalidated. Future studies must employ objective activity assessment alongside glycaemic markers to establish clinical relevance. 4.2 Psychological Well-Being and Proposed Mechanisms The statistically significant improvements across PGWBI domains, with moderate effect sizes for vitality (d = 0.85) and small-to-moderate effects for positive well-being and general health, constitute the study's most robust findings. The 25.7% point absolute increase in "good psychological well-being" classification represents a meaningful shift from a population baseline of 83.3% experiencing distress. These findings align with meta-analytic evidence that physical activity interventions produce consistent, though modest, reductions in depression and anxiety symptoms in T2DM populations [19, 20]. The mechanisms linking physical activity behaviour to psychological improvement are likely multifactorial. At the neurobiological level, physical activity is documented to increase circulating neurotrophic factors and enhance neural plasticity, changes associated with mood improvement and cognitive resilience [9]. At the behavioral level, successful activity adoption strengthens self-efficacy perceptions and generates mastery experiences, psychological constructs known to predict improved well-being. Psychosocially, increased activity exposure, particularly in urban green spaces emphasized in our counselling is associated with stress reduction, social connection, and perceived environmental improvement [21]. Additionally, provider contact and individualized attention during counselling may have generated therapeutic effects beyond activity promotion, including enhanced social support and validation of health concerns. Importantly, our findings contrast with some prior studies documenting gender-differential intervention effects. Toselli et al [21] reported that psychological benefits of park-based activity programs were statistically significant for female participants but not males, attributing this to potential differences in baseline activity levels, social support availability, or health perception pathways. Our findings demonstrated improvements across both genders, though we did not stratify outcomes by sex and thus cannot evaluate potential sex-specific patterns. Future studies should examine whether gender, social support availability, or baseline psychological profiles moderate intervention effectiveness. 4.3 Study Limitations : The study’s interpretation is primarily constrained by its quasi-experimental, single-arm design, which precludes definitive causal inference. The absence of a control group leaves the results susceptible to regression to the mean, particularly given the extreme baseline inactivity and distress levels of the sample, observed improvements may partially reflect statistical normalization rather than intervention efficacy. Furthermore, potential selection bias arising from purposive sampling and high non-enrolment suggests that participants may represent a motivated subset of the population, thereby affecting external validity. Methodologically, the reliance on subjective, self-reported physical activity without objective corroboration or clinical endpoints limits the confirmation of physiological benefits. Moreover, the brief four-week follow-up and the single-session minimal contact intervention dose contrast with standard high-intensity protocols, leaving the durability of behavioral change unverified. Consequently, while these findings establish preliminary feasibility, future research requires longitudinal randomized controlled trials with objective metabolic biomarkers to confirm the long-term clinical utility of this low-resource intervention model. 4.4 Strengths of the Study The community-based, primary care-linked design reflects real-world implementation in a resource-constrained setting, enhancing practical relevance for LMIC health systems. The intervention required minimal resources such as one trained health worker, basic IEC materials, less than an hour staff time per participant, making it scalable within existing primary health center capacity. Use of a validated psychological outcome measure with demonstrated reliability and construct validity in diabetes populations reduces measurement error in primary outcome. Intentional focus on physically inactive T2DM patients targets a high-need group with substantial disease burden. The diverse sociodemographic composition with 62.1% unemployed, 39.4% illiterate, representing economically disadvantaged urban population, reflects populations most affected by diabetes in LMIC contexts, enhancing applicability to similar settings. 4.5 Implications for Implementation and Future Research For primary care practitioners in resource-limited urban settings, these findings suggest that brief, culturally-tailored counselling delivered through accessible home-visit mechanisms can be feasibly integrated into routine diabetes care and may be associated with improvements in self-reported physical activity and psychological well-being. The low resource requirement and brief intervention duration make implementation pragmatically feasible within existing health center capacity. However, practitioners must recognize that observed improvements may not fully reflect true behavioral change given measurement limitations. Future research should employ rigorous quasi-experimental designs with matched control groups to isolate intervention effects from regression to the mean and other temporal threats. Objective outcome measurement using accelerometery for physical activity and for metabolic impact would strengthen clinical validity. Longer follow-up periods are essential to evaluate behaviour sustainability and identify need for booster sessions or ongoing support. Gender-stratified analyses should examine differential intervention effects by sex. Mechanistic investigations examining whether psychological improvements result directly from activity increases or from provider attention and social support would clarify intervention pathways and inform optimization. Cost-effectiveness analyses comparing this minimal-contact approach to standard multi-session interventions would support resource allocation decisions in LMIC health systems. 5. CONCLUSIONS This study establishes the feasibility and impact of a minimal-contact, home-delivered educational intervention, demonstrating statistically significant improvements in physical activity engagement and a twofold increase in favourable psychological well-being outcomes among urban patients. These findings highlight the critical value of integrating brief, behavioral health counselling into routine primary care to effectively bridge the gap between clinical advice and lifestyle modification. Declarations Funding statement: This research received no specific grant from any funding agency in the public, private, or non-governmental organisation. Ethical approval: The study protocol was reviewed and approved by the Institutional Ethics Committee (IEC) of JSS Medical College, Mysore under the reference number JSS/MC/PG/91/2022-23 before commencing the study. Written informed consent was obtained from all participants prior to data collection, and patient confidentiality was strictly maintained in accordance with the Declaration of Helsinki. Consent to Participate: Informed consent was obtained from all individual participants included in the study. The purpose of the research, the voluntary nature of participation, and the confidentiality of the data were explained in the local language (Kannada) or English, depending on the participant's preference. Written informed consent was secured prior to the administration of the questionnaire. Consent to Publish: The participants provided informed consent regarding the publication of anonymized aggregated data derived from this study. No personally identifiable information (PII) or individual clinical images are included in this manuscript. Competing Interests: None declared. Author Contribution: CMS -Data Curation, Formal Analysis, Investigation, Methodology, Writing-Original Draft Preparation SBM -Methodology, Visualization, Writing-Reviews and Editing, Validation MSM : Formal Analysis, Methodology CM : Methodology, Formal Analysis SBC : Writing-Reviews and Editing, Validation YA : Writing-Reviews and Editing, Validation MB - Conceptualization, Supervision Acknowledgements: The authors acknowledge the DBT BUILDER Project (Govt. of India) at JSS Academy of Higher Education & Research (JSS AHER), Mysore, for providing the licensed ArcGIS software (v10.8.2), procured under file number BT/INF/22/SP43045/2021 (dated November 22, 2021) Data Availability Statement: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. References 1. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. 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PMID: 34887271; PMCID: PMC8663073. 20. van der Heijden MM, van Dooren FE, Pop VJ, Pouwer F. Effects of exercise training on quality of life, symptoms of depression, symptoms of anxiety and emotional well-being in type 2 diabetes mellitus: a systematic review. Diabetologia. 2013 Jun;56(6):1210-25. doi: 10.1007/s00125-013-2871-7. Epub 2013 Mar 23. PMID: 23525683. 21. Toselli S, Bragonzoni L, Grigoletto A, Masini A, Marini S, Barone G, et al. Effect of a Park-Based Physical Activity Intervention on Psychological Wellbeing at the Time of COVID-19. Int J Environ Res Public Health. 2022 May 16;19(10):6028. doi: 10.3390/ijerph19106028. PubMed PMID: 35627565; PubMed Central PMCID: PMC9140357. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8624080","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587859580,"identity":"a35d5fc1-016b-469c-a869-f5a4acd2df9e","order_by":0,"name":"Chetan M Suresh","email":"","orcid":"","institution":"JSS Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chetan","middleName":"M","lastName":"Suresh","suffix":""},{"id":587859581,"identity":"536f7821-8bbc-4fe9-ab67-3378591134d7","order_by":1,"name":"Suraj B Manjunath","email":"","orcid":"","institution":"JSS Academy of Higher Education \u0026 Research","correspondingAuthor":false,"prefix":"","firstName":"Suraj","middleName":"B","lastName":"Manjunath","suffix":""},{"id":587859582,"identity":"1bce8afd-2355-4a48-8c60-aec72378d4a5","order_by":2,"name":"Mounika Sree Manivasagan","email":"","orcid":"","institution":"JSS Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mounika","middleName":"Sree","lastName":"Manivasagan","suffix":""},{"id":587859583,"identity":"d2df9a2d-a601-44ff-abcb-0fe5614b6a05","order_by":3,"name":"Chaithra M","email":"","orcid":"","institution":"JSS Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chaithra","middleName":"","lastName":"M","suffix":""},{"id":587859584,"identity":"0873261b-869f-4620-ac56-6f741269b165","order_by":4,"name":"Sulochanadevi B Chakrashali","email":"","orcid":"","institution":"JSS Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sulochanadevi","middleName":"B","lastName":"Chakrashali","suffix":""},{"id":587859590,"identity":"0b08aa02-6533-416f-9489-18f51ed4d1aa","order_by":5,"name":"Yashashwini A","email":"","orcid":"","institution":"JSS Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yashashwini","middleName":"","lastName":"A","suffix":""},{"id":587859596,"identity":"b9ff0c4e-7d66-4dc1-808a-51307e5e3909","order_by":6,"name":"Madhu Basavegowda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYHACMwbGBhtmMDOBAcgGISK0pJGu5TCcR1i9bvvhbY95d5xnl+8/Y/bgAYON7IYDzG0P8FpxJq3cmPfMbWaDGznmBgkMacYbDjC2G+DVciDHTJq3DahFgsdMIoHhcCJQS5sEXi3n34C0nGMGOQyo5T8RWm6AbTnAzAC0DqjlADFanpVJzj2TDPRLWplEgkGy8czDBB2WvE3i7Q67ZPn+w9skf1TYyfYdb3+GVwsMJEMoUFAxE6MeCOyIVDcKRsEoGAUjEQAA1bxJTcB1H5QAAAAASUVORK5CYII=","orcid":"","institution":"JSS Medical College and Hospital","correspondingAuthor":true,"prefix":"","firstName":"Madhu","middleName":"","lastName":"Basavegowda","suffix":""}],"badges":[],"createdAt":"2026-01-17 07:08:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8624080/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8624080/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102733454,"identity":"dbc7a073-8087-46c6-ae92-314599718931","added_by":"auto","created_at":"2026-02-16 05:40:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1273860,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Area Map of the Saraswathipuram UPHC Area, Mysore, India\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8624080/v1/54e799ba1ef10a2d0dcc123b.png"},{"id":102733457,"identity":"183f20b2-5cbb-46a2-be7b-28a546c460ff","added_by":"auto","created_at":"2026-02-16 05:40:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122394,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram depicting the participant recruitment and selection process.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8624080/v1/c6cc10009314aab8fee9ad24.png"},{"id":102733362,"identity":"f9b18ccf-0901-4738-9ff3-f259da2d0b18","added_by":"auto","created_at":"2026-02-16 05:40:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29298,"visible":true,"origin":"","legend":"\u003cp\u003ePre- and post-intervention comparison of psychological well-being status (n=132)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8624080/v1/f55be0f406be06edce1951f6.png"},{"id":104874254,"identity":"32f7ef38-56f8-497b-a6dd-32553f67879d","added_by":"auto","created_at":"2026-03-18 08:29:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2244162,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8624080/v1/72b4c294-cbd9-4902-8612-fa3cf126abd6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Improving Physical Activity and Psychological Well-Being in Type 2 Diabetes: An Educational Intervention in Urban Primary Care","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eDiabetes mellitus represents one of the most significant non-communicable disease challenges globally, with particular severity in low- and middle-income countries (LMICs). The global diabetes epidemic continues to accelerate, approximately 537\u0026nbsp;million adults aged 20\u0026ndash;79 years were living with diabetes in 2021, projected to reach 643\u0026nbsp;million by 2030 and 783\u0026nbsp;million by 2045 [1]. In India, approximately 101\u0026nbsp;million individuals currently live with diabetes, and this number is expected to rise to 124.9\u0026nbsp;million by 2045 [2, 3]. Alarmingly, more than 50% of affected individuals remain unaware of their condition, eventually increasing complications risk [4].\u003c/p\u003e \u003cp\u003ePhysical inactivity is a known modifiable risk factor for both diabetes and poor glycaemic control. The World Health Organization defines physical activity as any bodily movement requiring energy expenditure, encompassing walking, cycling, sports, dancing, and structured exercise [5]. Present guidelines recommend that adults with T2DM engage in 150 to 300 minutes of moderate-intensity aerobic activity per week, or alternatively 75\u0026ndash;150 minutes of vigorous-intensity activity [6, 7]. Despite these evidence-based recommendations, one in four adults globally fail to achieve the prescribed activity levels, with particularly high inactivity rates among diabetic individuals in urban LMIC settings [5]. Physical inactivity is not just a consequence of the condition, but it actively propels diabetes toward a severe and persistent state of mismanagement.\u003c/p\u003e \u003cp\u003ePsychological well-being, including positive emotional states, life satisfaction, personal growth, and stress management capacity, emerges as a critical and often-neglected dimension of diabetes care, specifically in resource-constrained settings. The relationship between psychological status and diabetes outcomes is bidirectional as poor well-being predicts worse glycaemic control and higher mortality, while positive psychological states predict improved treatment adherence and better long-term health [8]. Growing evidence suggests that physical activity interventions can simultaneously improve both physical activity levels and psychological outcomes through multiple pathways: direct neurobiological effects such as enhanced neurotrophic factors, increased neural plasticity, improved self-efficacy, and enhanced social connection through activity participation [9]. However, it remains unclear exactly how these improvements occur and whether they are durable over time in the context of urban populations in LMICs.\u003c/p\u003e \u003cp\u003eAlthough community-based physical activity promotion has shown promise in diabetes management, a significant gap persists in urban LMIC settings regarding integrated interventions addressing both physical and mental health outcomes. Most intervention models typically employ extended protocols or require attendance at clinical facilities. This creates a significant gap in the literature regarding minimal-contact, home-delivered strategies within resource-constrained primary care environments. This is important for urban India, where primary health centers serve predominantly socioeconomically disadvantaged populations with high disease burden but limited access to specialized behavioral health services.\u003c/p\u003e \u003cp\u003eThe present study addresses this gap by evaluating the feasibility and preliminary effects of a single-session, house-delivered educational intervention promoting physical activity on psychological well-being outcomes physically inactive T2DM patients within an urban primary health center (UPHC) in South India. We hypothesized that even modest increases in physical activity, achieved through low-cost counselling delivered within community settings, might be associated with improvements in psychological well-being, offering implementation models for resource-constrained health systems.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1. Study Design and Setting\u003c/h2\u003e\n\u003cp\u003eThis was a quasi-experimental pre-post feasibility study conducted in urban Mysuru, Karnataka, India. Mysuru represents a rapidly urbanizing Tier-2 city where environmental determinants play a key role in the lifestyle management of T2DM. The region has a Tropical Savanna climate, and underscores the critical need for green spaces to ensure thermal comfort and sustain adherence to physical activity patterns. The study was conducted within the Saraswathipuram UPHC catchment, a mixed-use zone featuring the restorative landscape of Kukkarahalli Lake, which offers vital opportunities for both recreation and psychological stress reduction. This setting, combined with a high effective literacy rate, provides a unique context for examining the intersection of urban planning, patient well-being, and health behaviour. The catchment area of the UPHC includes four municipal wards; Gangotri, Jayalakshmipuram, Kuvempunagar, and Saraswathipuram (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.) with a population of 41,377. The UPHC maintains a diabetes registry of patients receiving routine care through the National Diabetes Prevention and Control Program. The setting was selected to represent typical resource-limited urban primary care in India, with single trained health worker capacity and minimal dedicated mental health services.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 Study Population and Sampling\u003c/h2\u003e\n\u003cp\u003eThe inclusion criteria were adults aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years with Type 2 Diabetes Mellitus verified by UPHC records, defined as physically inactive (performing\u0026thinsp;\u0026lt;\u0026thinsp;75 minutes vigorous-intensity or \u0026lt;\u0026thinsp;150 minutes moderate-intensity physical activity weekly), able to provide informed written consent, and available for follow-up assessment. The exclusion Criteria were the individuals with physical disabilities or bedridden status that prevents physical activity participation; documented severe psychiatric conditions, those unable or unwilling to provide informed consent; or unavailable for baseline assessment.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e2.3. Sampling and Recruitment:\u003c/h2\u003e\n\u003cp\u003eOf 621 registered diabetic patients assessed for eligibility, 430 were excluded as they did not meet the inclusion criteria; 149 were unavailable during the data collection period, 124 were already physically active, and 157 had severe physical limitations. Out of the remaining 191 eligible candidates, 51 declined participation and 8 were lost to follow-up, yielding a final analytical sample of 132 participants (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Recruitment was conducted during routine health center visits and supplementary house visits, employing a registry-based sampling approach.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003e2.4 Intervention Description:\u003c/h2\u003e\n\u003cp\u003eParticipants were given a single one-on-one educational counselling session delivered during home visits, typically lasting 30\u0026ndash;45 minutes. The intervention was grounded in Social Cognitive Theory, targeting self-efficacy, outcome expectations, and perceived barriers to physical activity [10]. Counselling content included: (1) personalized discussion of diabetes-related health benefits of physical activity, (2) identification of individually feasible activity options (primarily walking, given urban setting constraints), (3) practical strategies for integrating activity into daily routines, (4) identification and problem-solving of perceived barriers (time, fatigue, joint pain, safety concerns, social norms), and (5) discussion of accessibility of urban green spaces for activity. Visual Information, Education, and Communication (IEC) materials (1-page infographics with pictorial representations of various activity types, local green spaces, and motivational messaging) were provided in Kannada language. No ongoing follow-up contact or reinforcement sessions were provided; participants were advised to aim for progressive increases toward \u0026ge;\u0026thinsp;150 minutes/week moderate-intensity activity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e2.5 Outcome Measures\u003c/h2\u003e\n\u003cstrong\u003e2.5.1 Primary Outcome\u003c/strong\u003e: Psychological Well-Being- The Psychological General Well-Being Index (PGWBI) is a validated 22-item self-report instrument assessing six domains: anxiety, depression, positive well-being, self-control, general health, and vitality [11]. Each item is scored 0\u0026ndash;5, with domain scores calculated as item sums or means depending on domain. The PGWBI demonstrates strong reliability (Cronbach's \u0026alpha;\u0026thinsp;=\u0026thinsp;0.77\u0026ndash;0.97) and validity in T2DM populations [12]. A PGWBI total score\u0026thinsp;\u0026ge;\u0026thinsp;73 is typically categorized as \"good well-being,\" while\u0026thinsp;\u0026lt;\u0026thinsp;73 indicates \"moderate to severe distress\". The instrument was administered in validated Kannada translation by trained health workers using structured interview format.\u003cbr /\u003e\u003cstrong\u003e2.5.2 Secondary Outcome\u003c/strong\u003e: Physical Activity- Self-reported physical activity was assessed via structured interview using questions adapted from the WHO Global Physical Activity Questionnaire (GPAQ) framework. Participants reported weekly frequency (days/week) and duration (minutes/week) of activity in categories: none, 1\u0026ndash;2 days, 3\u0026ndash;4 days, or 5\u0026ndash;6 days/week; and duration in minutes. No objective physical activity measurement such as accelerometry, step counters were employed.\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e2.6 Study Procedures and Data Collection\u003c/h2\u003e\n\u003cp\u003eTrained health workers conducted baseline assessments immediately prior to intervention delivery, including demographic characteristics such as age, sex, education, occupation, marital status, and clinical history including diabetes duration, medications, and outcome measures. Interventions were delivered within 1 week of baseline assessment. Post-intervention assessments were conducted exactly 4 weeks after intervention delivery using identical instruments and procedures. All data collection occurred in participants' residence or at the health center, according to participant preference.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e2.7 Statistical Analysis\u003c/h2\u003e\n\u003cp\u003eDescriptive statistics like frequencies, percentages, means with standard deviations for normally distributed variables; medians with interquartile ranges for non-normally distributed variables, characterized the study population and baseline-to-post-test changes. Normality was assessed using Kolmogorov-Smirnov tests. For normally distributed PGWBI domains (positive well-being, self-control, general health, vitality), paired t-tests compared baseline and post-intervention scores. For non-normally distributed domains (anxiety, depression), Wilcoxon signed-rank tests were employed. Between-group effect sizes were calculated as Cohen's d;\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:d=\\frac{(Mean\\:Post-Mean\\:Pre)\\:\\:}{SD\\:Pooled}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eStatistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed). Analyses were performed using SPSS version 22.0.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e2.8 Ethical Considerations\u003c/h2\u003e\n\u003cp\u003eEthical approval\u0026nbsp;was obtained from the Institutional Ethics Committee of JSS Medical College, JSS Academy of Higher Education and Research (No. JSS/MC/PG/91/2022-23, dated March 31, 2023). Written informed consent was obtained from all participants prior to enrolment, with study information provided in Kannada and English. Confidentiality was maintained through de-identification of data and secure data storage. Participants could withdraw at any time without consequences.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Participant Characteristics\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of Study Participants (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003cp\u003e(in years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBelow 46\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46- \u003cb\u003e55\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56- \u003cb\u003e65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAbove 65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEducational Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIlliterates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePrimary school\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHigh school\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIntermediate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGraduation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCurrent Occupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUnemployed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUnskilled\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSkilled\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eArithmetic skill jobs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eProfessionals\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe sample comprised 132 T2DM patients with mean age 58.2 years (SD\u0026thinsp;=\u0026thinsp;9.7), 55.3% were female (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Baseline educational attainment was low: 39.4% illiterate, 15.2% with primary education, and only 12.1% with college education. Occupational status reflected socioeconomic disadvantage with 62.1% unemployed, 15.9% skilled workers, and 14.4% in clerical roles. Mean diabetes duration was approximately 7.3 years (range 1\u0026ndash;18 years). No baseline differences in demographic characteristics were detected between participants lost to follow-up (n\u0026thinsp;=\u0026thinsp;8) and those completing post-intervention assessment (n\u0026thinsp;=\u0026thinsp;132), though sample size precluded formal statistical comparison.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Physical Activity Outcomes\u003c/h2\u003e \u003cp\u003eBaseline physical activity levels revealed remarkable inactivity: 72% reported zero weekly physical activity, 23.5% engaged in activity 3\u0026ndash;4 days/week, and none achieved 5\u0026ndash;6 days/week (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Regarding activity duration, 72% reported no activity; only 13.6% and 14.4% engaged in 60\u0026ndash;90 and 120\u0026ndash;135 minutes weekly, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of the study participants based on Physical Activity Pre \u0026amp; Post Intervention (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Activity Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBefore (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAfter (n, %)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFrequency of Weekly Physical Activity Engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot utilizing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (27.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19 (14.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61 (46.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;6 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (12.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDuration of Physical Activity per week in minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot utilizing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (27.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;90 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41 (31.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120\u0026ndash;135 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40 (30.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;149 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (11.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePost-intervention (4 weeks), substantial self-reported improvements were observed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Proportions reporting no weekly activity declined to 27.3%, while those engaging in activity 3\u0026ndash;4 days/week increased to 46.2%, and 12.1% reported 5\u0026ndash;6 days/week activity (a change of 46.2 percentage points). Regarding duration, physical inactivity fell to 27.3%; 31.1% reported 60\u0026ndash;90 minutes weekly, 30.3% reported 120\u0026ndash;135 minutes, and 11.4% exceeded 150 minutes/week. These changes represent substantial shifts in activity self-reporting, though the magnitude and sustainability remain uncertain given the self-report methodology and short follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Psychological Well-Being Outcomes\u003c/h2\u003e \u003cp\u003ePre-post PGWBI domain changes are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Across all six domains, statistically significant improvements were observed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all domains). For anxiety (non-normally distributed), median scores increased from 10 (IQR 7\u0026ndash;14) to 14 (IQR 9\u0026ndash;17), corresponding to Wilcoxon signed-rank test p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Depression median scores increased from 7 (IQR 4\u0026ndash;10) to 9 (IQR 5\u0026ndash;11), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of pre and post-test of Psychological General Well-Being Index (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePGWBI Domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAfter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (7\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (9\u0026ndash;17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (5\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive Wellbeing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.17\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.20\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003csup\u003e*\u003c/sup\u003eWilcoxon Signed-Rank Test was used for non-normally distributed domains (Anxiety and Depression); \u003csup\u003e**\u003c/sup\u003e Paired t-test was applied for the normally distributed domain (Positive Wellbeing, Self-control, General Health, Vitality).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor normally distributed domains, paired t-tests revealed: positive well-being increased from mean 9.20 (SD\u0026thinsp;=\u0026thinsp;4.24) to 11.67 (SD\u0026thinsp;=\u0026thinsp;4.08), representing an absolute increase of 2.47 points and Cohen's d\u0026thinsp;=\u0026thinsp;0.59 with small-to-moderate effect size. Self-control increased from 7.90 (SD\u0026thinsp;=\u0026thinsp;3.36) to 9.17 (SD\u0026thinsp;=\u0026thinsp;3.25), d\u0026thinsp;=\u0026thinsp;0.38 with small effect. General health increased from 9.72 (SD\u0026thinsp;=\u0026thinsp;2.85) to 11.26 (SD\u0026thinsp;=\u0026thinsp;2.85), d\u0026thinsp;=\u0026thinsp;0.54 with small-to-moderate effect. Vitality increased from 10.00 (SD\u0026thinsp;=\u0026thinsp;2.59) to 12.20 (SD\u0026thinsp;=\u0026thinsp;2.73), d\u0026thinsp;=\u0026thinsp;0.85 moderate effect. All differences achieved statistical significance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe proportion of participants categorized as having \"good psychological well-being\" (PGWBI total\u0026thinsp;\u0026ge;\u0026thinsp;73) increased from 16.7% at baseline to 42.4% post-intervention as in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, an absolute increase of 25.7 percentage points and relative risk increase of 2.54-fold. Conversely, those experiencing \u0026ldquo;moderate to severe distress\" (PGWBI\u0026thinsp;\u0026lt;\u0026thinsp;73) declined from 83.3% to 57.6%.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis quasi-experimental feasibility study illustrates statistically significant associations between a single-session, home-delivered educational intervention and self-reported increases in physical activity and in psychological well-being among physically inactive T2DM patients in an urban LMIC primary health center setting. The intervention was feasible to implement with minimal resource requirements and demonstrated acceptable retention (94.3%). However, substantial methodological limitations preclude definitive causal conclusions and warrant transparent discussion.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Physical Activity Outcomes in Context\u003c/h2\u003e \u003cp\u003eThe significant decline in reported inactivity (72% to 27.3%) and increases in activity frequency/duration align qualitatively with findings from similar community-based interventions in diabetic populations. Xu et al [13] observed increased urban green space utilization and physical activity engagement following behavioral counselling in a Chinese diabetes program. Hong et al [14] reported that approximately half of participants receiving structured counselling achieved 60\u0026ndash;120 minutes of weekly activity. Zlender and Thompson [15] documented that approximately 22% of program participants progressed to daily physical activity following community-based promotion initiatives. These parallel findings suggest that culturally-adapted, community-focused behavioral strategies can mobilize physical activity among previously sedentary populations.\u003c/p\u003e \u003cp\u003eHowever, it is important to acknowledge significant limitations regarding how physical activity was measured. Self-reported physical activity demonstrates known limitations such as the correlation with objective measures is weak-to-moderate (r\u0026thinsp;\u0026asymp;\u0026thinsp;0.14\u0026ndash;0.17 for moderate-vigorous activity), and interventions targeting activity behaviour systematically increase over-reporting by 8\u0026ndash;19% due to social desirability bias and demand characteristics [16]. The WHO GPAQ framework, on which our instrument was based, is documented to systematically overestimate activity compared to accelerometer measurement [17]. Thus, reported activity improvements may substantially overestimate true behavioral change. The 4-week follow-up period is insufficient to assess sustainability as behavioral change literature indicates that activity gains often decline without ongoing reinforcement, particularly in single-contact intervention models [18]. We cannot determine whether observed changes represent genuine behaviour adoption or temporary social desirability response to study participation. Notably, the study did not measure glycaemic outcomes or other clinical markers, thus, metabolic significance of reported activity improvements remains unvalidated. Future studies must employ objective activity assessment alongside glycaemic markers to establish clinical relevance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Psychological Well-Being and Proposed Mechanisms\u003c/h2\u003e \u003cp\u003eThe statistically significant improvements across PGWBI domains, with moderate effect sizes for vitality (d\u0026thinsp;=\u0026thinsp;0.85) and small-to-moderate effects for positive well-being and general health, constitute the study's most robust findings. The 25.7% point absolute increase in \"good psychological well-being\" classification represents a meaningful shift from a population baseline of 83.3% experiencing distress. These findings align with meta-analytic evidence that physical activity interventions produce consistent, though modest, reductions in depression and anxiety symptoms in T2DM populations [19, 20].\u003c/p\u003e \u003cp\u003eThe mechanisms linking physical activity behaviour to psychological improvement are likely multifactorial. At the neurobiological level, physical activity is documented to increase circulating neurotrophic factors and enhance neural plasticity, changes associated with mood improvement and cognitive resilience [9]. At the behavioral level, successful activity adoption strengthens self-efficacy perceptions and generates mastery experiences, psychological constructs known to predict improved well-being. Psychosocially, increased activity exposure, particularly in urban green spaces emphasized in our counselling is associated with stress reduction, social connection, and perceived environmental improvement [21]. Additionally, provider contact and individualized attention during counselling may have generated therapeutic effects beyond activity promotion, including enhanced social support and validation of health concerns.\u003c/p\u003e \u003cp\u003eImportantly, our findings contrast with some prior studies documenting gender-differential intervention effects. Toselli et al [21] reported that psychological benefits of park-based activity programs were statistically significant for female participants but not males, attributing this to potential differences in baseline activity levels, social support availability, or health perception pathways. Our findings demonstrated improvements across both genders, though we did not stratify outcomes by sex and thus cannot evaluate potential sex-specific patterns. Future studies should examine whether gender, social support availability, or baseline psychological profiles moderate intervention effectiveness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e4.3 Study Limitations\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThe study\u0026rsquo;s interpretation is primarily constrained by its quasi-experimental, single-arm design, which precludes definitive causal inference. The absence of a control group leaves the results susceptible to regression to the mean, particularly given the extreme baseline inactivity and distress levels of the sample, observed improvements may partially reflect statistical normalization rather than intervention efficacy. Furthermore, potential selection bias arising from purposive sampling and high non-enrolment suggests that participants may represent a motivated subset of the population, thereby affecting external validity.\u003c/p\u003e \u003cp\u003eMethodologically, the reliance on subjective, self-reported physical activity without objective corroboration or clinical endpoints limits the confirmation of physiological benefits. Moreover, the brief four-week follow-up and the single-session minimal contact intervention dose contrast with standard high-intensity protocols, leaving the durability of behavioral change unverified. Consequently, while these findings establish preliminary feasibility, future research requires longitudinal randomized controlled trials with objective metabolic biomarkers to confirm the long-term clinical utility of this low-resource intervention model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Strengths of the Study\u003c/h2\u003e \u003cp\u003eThe community-based, primary care-linked design reflects real-world implementation in a resource-constrained setting, enhancing practical relevance for LMIC health systems. The intervention required minimal resources such as one trained health worker, basic IEC materials, less than an hour staff time per participant, making it scalable within existing primary health center capacity. Use of a validated psychological outcome measure with demonstrated reliability and construct validity in diabetes populations reduces measurement error in primary outcome. Intentional focus on physically inactive T2DM patients targets a high-need group with substantial disease burden. The diverse sociodemographic composition with 62.1% unemployed, 39.4% illiterate, representing economically disadvantaged urban population, reflects populations most affected by diabetes in LMIC contexts, enhancing applicability to similar settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Implications for Implementation and Future Research\u003c/h2\u003e \u003cp\u003eFor primary care practitioners in resource-limited urban settings, these findings suggest that brief, culturally-tailored counselling delivered through accessible home-visit mechanisms can be feasibly integrated into routine diabetes care and may be associated with improvements in self-reported physical activity and psychological well-being. The low resource requirement and brief intervention duration make implementation pragmatically feasible within existing health center capacity. However, practitioners must recognize that observed improvements may not fully reflect true behavioral change given measurement limitations.\u003c/p\u003e \u003cp\u003eFuture research should employ rigorous quasi-experimental designs with matched control groups to isolate intervention effects from regression to the mean and other temporal threats. Objective outcome measurement using accelerometery for physical activity and for metabolic impact would strengthen clinical validity. Longer follow-up periods are essential to evaluate behaviour sustainability and identify need for booster sessions or ongoing support. Gender-stratified analyses should examine differential intervention effects by sex. Mechanistic investigations examining whether psychological improvements result directly from activity increases or from provider attention and social support would clarify intervention pathways and inform optimization. Cost-effectiveness analyses comparing this minimal-contact approach to standard multi-session interventions would support resource allocation decisions in LMIC health systems.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eThis study establishes the feasibility and impact of a minimal-contact, home-delivered educational intervention, demonstrating statistically significant improvements in physical activity engagement and a twofold increase in favourable psychological well-being outcomes among urban patients. These findings highlight the critical value of integrating brief, behavioral health counselling into routine primary care to effectively bridge the gap between clinical advice and lifestyle modification.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding statement:\u0026nbsp;\u003c/strong\u003eThis research received no specific grant from any funding agency in the public, private, or non-governmental organisation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u003c/strong\u003e The study protocol was reviewed and approved by the Institutional Ethics Committee (IEC) of JSS Medical College, Mysore under the reference number JSS/MC/PG/91/2022-23 before commencing the study. Written informed consent was obtained from all participants prior to data collection, and patient confidentiality was strictly maintained in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u003c/strong\u003e Informed consent was obtained from all individual participants included in the study. The purpose of the research, the voluntary nature of participation, and the confidentiality of the data were explained in the local language (Kannada) or English, depending on the participant's preference. Written informed consent was secured prior to the administration of the questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u003c/strong\u003e The participants provided informed consent regarding the publication of anonymized aggregated data derived from this study. No personally identifiable information (PII) or individual clinical images are included in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e None declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCMS\u003c/strong\u003e-Data Curation, Formal Analysis, Investigation, Methodology, Writing-Original Draft Preparation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSBM\u003c/strong\u003e-Methodology, Visualization, Writing-Reviews and Editing, Validation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMSM\u003c/strong\u003e: Formal Analysis, Methodology\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCM\u003c/strong\u003e: Methodology, Formal Analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSBC\u003c/strong\u003e: Writing-Reviews and Editing, Validation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYA\u003c/strong\u003e: Writing-Reviews and Editing, Validation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMB\u003c/strong\u003e- Conceptualization, Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e The authors acknowledge the DBT BUILDER Project (Govt. of India) at JSS Academy of Higher Education \u0026amp; Research (JSS AHER), Mysore, for providing the licensed ArcGIS software (v10.8.2), procured under file number BT/INF/22/SP43045/2021 (dated November 22, 2021)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e1. 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Int J Environ Res Public Health. 2022 May 16;19(10):6028. doi: 10.3390/ijerph19106028. PubMed PMID: 35627565; PubMed Central PMCID: PMC9140357.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes, Physical activity, Psychological well-being, Urban health center","lastPublishedDoi":"10.21203/rs.3.rs-8624080/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8624080/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eType 2 diabetes (T2DM) is associated with physical inactivity and psychological distress. Community-based interventions addressing both physical activity and mental health remain understudied in low-resource urban settings in India.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo assess the feasibility and preliminary effects of a one-on-one educational intervention promoting physical activity on psychological well-being and self-reported physical activity levels among physically inactive T2DM patients in an urban primary health center in South India.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA quasi-experimental pre-post study recruited 132 physically inactive (\u0026le;\u0026thinsp;150 minutes/week moderate-intensity activity) T2DM patients from Saraswathipuram Urban Primary Health Center, Mysuru. Participants received a single one-on-one counselling session delivered via house-to-house visits using Information, Education, and Communication materials. Psychological well-being was assessed using the Psychological General Well-Being Index (PGWBI) at baseline and 4 weeks post-intervention. Physical activity was assessed via structured questionnaire based on WHO Global Physical Activity Questionnaire. Effect sizes (Cohen's d) and proportional changes in outcomes were calculated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFollowing the intervention, participant-reported physical activity engagement increased markedly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001): the proportion reporting no activity declined from 72% to 27.3%. Across all six PGWBI domains, statistically significant improvements were observed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mean PGWBI positive well-being increased from 9.20 to 11.67 (Cohen's d\u0026thinsp;=\u0026thinsp;0.59), self-control from 7.90 to 9.17 (d\u0026thinsp;=\u0026thinsp;0.38), general health from 9.72 to 11.26 (d\u0026thinsp;=\u0026thinsp;0.54), and vitality from 10.00 to 12.20 (d\u0026thinsp;=\u0026thinsp;0.85). The proportion of participants with good psychological well-being increased from 16.7% to 42.4%.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this study, a low-cost, single-session house-based educational intervention was associated with participant-reported increases in physical activity and improvements in psychological well-being among urban T2DM patients. Results suggest feasibility for implementation in resource-limited primary health centers. Longer-term follow-up with control groups and objective outcome measures such as HbA1c, accelerometry, are required to establish durability and clinical significance.\u003c/p\u003e","manuscriptTitle":"Improving Physical Activity and Psychological Well-Being in Type 2 Diabetes: An Educational Intervention in Urban Primary Care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 05:39:54","doi":"10.21203/rs.3.rs-8624080/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"028f79fd-e6a2-40be-bfbf-1a9924f3bf50","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T08:27:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 05:39:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8624080","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8624080","identity":"rs-8624080","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}