Mobile-Technology-Driven Empowerment of Persons with Disabilities (PwDs) in Punjab

Vivek Joshi¹, Shivani Dhand², Aayushi Pandey³

¹Research Scholar, Mittal School of Business, Lovely Professional University, Phagwara,

Punjab - 144411, India.

²Associate Professor, Mittal School of Business, Lovely Professional University, Phagwara,

Punjab - 144411, India.

³Research Scholar, Mittal School of Business, Lovely Professional University, Phagwara,

Punjab - 144411, India.

*Corresponding Author E-mail: shividhand@gmail.com, aayushi5086@gmail.com

ABSTRACT:

The study examines how mobile technology serves as a catalyst for the empowerment and social inclusion of Persons with Disabilities (PwDs) in Punjab, India. Grounded in the Social Model of Disability and the Technology Acceptance Model (TAM), it adopts a mixed-methods framework integrating quantitative analysis and qualitative review to capture both measurable and contextual dimensions of digital inclusion. The objectives are: (1) to explore how mobile technologies enhance accessibility, participation, and empowerment among PwDs; (2) to analyse the sociocultural, demographic, and attitudinal factors influencing adoption and utilisation; and (3) to triangulate quantitative and qualitative evidence to identify the key enablers and constraints of digital empowerment. Secondary data were analysed through Exploratory Factor Analysis (EFA), Structural Equation Modelling (SEM), and regression diagnostics, while a PRISMA-guided systematic review and manual thematic analysis of 90 studies provided interpretive depth. Results indicate that education and income positively predict empowerment, whereas age, gender, and affordability act as structural barriers. Themes of public perception, social support, and accessibility reflect a dynamic interplay between attitude and opportunity. The triangulated findings reveal that technology-driven empowerment is most effective when combined with positive social attitudes, inclusive education, and equitable policy interventions. The study contributes to the discourse on assistive and mobile technologies within India’s Digital-Inclusion agenda and offers a framework for sustainable ICT-enabled participation of PwDs.

KEYWORDS: Persons with Disabilities (PwDs), Mobile Technology, Digital Inclusion, Empowerment, Punjab, Accessibility, Attitudes.

1. INTRODUCTION:

Technology has emerged as a transformative force, reshaping social, economic, and educational spheres worldwide. For Persons with Disabilities (PwDs), the evolution of digital and mobile technologies has created unprecedented opportunities to overcome long-standing barriers to communication, mobility, and participation in mainstream society (Manzoor and Vimarlund, 2018; Klavina et al., 2024). In the twenty-first century, mobile phones are no longer merely communication tools—they function as assistive technologies that promote autonomy, accessibility, and empowerment (Desmond, 2018). The global recognition of disability inclusion, articulated in the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD, 2006), underscores access to information and communication technologies (ICTs) as both a human right and a precondition for full participation in social and economic life.

Within India, the Rights of Persons with Disabilities (RPwD) Act, 2016 and the Digital India initiative have together established a policy framework that connects technology with empowerment (Government of India, 2016). The RPwD Act emphasizes accessible ICT infrastructure, universal design, and non-discrimination in technology use, while Digital India aims to transform the country into a digitally empowered society and knowledge economy (Ministry of Electronics and Information Technology [MeitY], 2022). These policy developments are crucial given India’s sizeable PwD population—approximately 2.68 crore individuals according to the 2011 Census—who continue to experience inequitable access to education, employment, and civic participation (Census of India, 2011). Consequently, mobile technology represents both a practical mechanism and a symbolic bridge between exclusion and inclusion. Punjab provides a distinct regional context for exploring the role of technology in PwD empowerment. The state boasts relatively high literacy levels, increasing smartphone penetration, and progressive initiatives under the Digital Punjab framework (Government of Punjab, 2023). However, socio-cultural attitudes, infrastructural disparities, and policy implementation gaps often impede the effective use of mobile technologies among PwDs. Particularly in rural districts, challenges such as limited income, inaccessible app design (especially in Punjabi language), and persistent social stigma constrain digital participation (Newman et al.,2017; Jamil, 2021). Thus, while technological infrastructure may exist, the empowerment potential remains deeply contingent upon social acceptance and institutional readiness. Existing scholarship reflects this complex intersection of technology, disability, and inclusion. (Klavina et al. 2024) observed that mobile devices significantly enhance independence and social interaction among adults with intellectual disabilities. Similarly, (Manzoor and Vimarlund, 2018; Newman et al.,2017) found that digital inclusion initiatives yield positive yet moderate outcomes, often constrained by affordability, digital literacy, and awareness gaps. Meanwhile, (Pacheco and Burgess, 2025; Tsatsou, 2020) highlight how persistent social stereotypes and negative perceptions continue to marginalize PwDs, even in technologically advanced contexts. These studies suggest that digital empowerment cannot be understood solely as a matter of technological access—it must be analysed within broader sociocultural and policy framew NṀṀorks. Against this backdrop, the present paper undertakes a qualitative review of global and regional literature to examine how mobile technologies influence the empowerment of PwDs in Punjab. Specifically, it aims to understand (a) the role of mobile technologies in enhancing accessibility, participation, and autonomy, and (b) the sociocultural and policy factors mediating their adoption and utilization. The paper argues that empowerment through mobile technology is inherently multidimensional, involving technological accessibility, attitudinal transformation, and institutional commitment.

The contribution of this paper lies in its contextualization of digital inclusion within the socio-economic fabric of Punjab—a region where technological progress intersects with cultural conservatism and infrastructural inequality. By synthesizing qualitative secondary data from scholarly literature, policy reports, and government documents, this study bridges the gap between global discourse and local realities, providing insights for inclusive digital policy and practice.

THE OBJECTIVES OF THIS STUDY:

1. To explore how mobile technologies enhance accessibility, participation, and empowerment among Persons with Disabilities (PwDs) in Punjab.

2. To analyse the sociocultural and attitudinal factors influencing the adoption and effective utilisation of mobile technology by PwDs.

Through this analytical lens, the paper proposes an integrated conceptual framework linking mobile technology adoption → digital accessibility → social inclusion → empowerment, moderated by public perception and institutional support. The subsequent sections present a thematic literature review, methodological considerations, and key findings that can inform inclusive technology policies in Punjab and beyond.

LITERATURE REVIEW:

Technology as a Catalyst for Disability Inclusion:

The integration of digital technologies has revolutionized access to education, communication, and employment, particularly for marginalized groups such as Persons with Disabilities (PwDs)(Desmond,2018). Mobile technologies, in particular, have emerged as assistive tools that enhance independence, social participation, and self-determination (Klavina et al. 2024). These tools transform barriers into bridges, offering new pathways for empowerment through accessible applications, voice-assistive features, and adaptive interfaces (Manzoor and Vimarlund, 2018). According to the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD, 2006; Jamil, 2021), access to information and communication technology (ICT) is a human right essential to achieving equality and inclusion. Scholars have emphasized that when designed inclusively, technology can shift PwDs from passive recipients of care to active contributors in digital economies (Tsatsou, 2020). However, despite the promise of these innovations, digital accessibility remains uneven, especially in low- and middle-income countries, where infrastructural limitations and affordability gaps persist (Newman et al., 2017; Jamil, 2021).

Policy and Legislative Frameworks Supporting Digital Empowerment:

Globally, disability inclusion policies have evolved toward integrating digital accessibility into mainstream development agendas. In India, the Rights of Persons with Disabilities (RPwD) Act, 2016 institutionalizes accessibility standards in ICT design and implementation (Sharma,2022). The Act complements the Digital India initiative, which envisions a “digitally empowered society and knowledge economy” (Ministry of Electronics and Information Technology [MeitY], 2022). These frameworks recognize technology as both a development enabler and a social equalizer. Yet, the translation of policy into practice remains inconsistent due to administrative bottlenecks and weak monitoring mechanisms (Newman et al., 2017; Sharma,2022). Regional governments, such as Punjab, have launched initiatives like Digital Punjab to bridge digital divides, but localized research suggests that many PwDs still struggle to access assistive technologies due to cost constraints and a lack of awareness (Government of Punjab, 2023; Pacheco and Burgess, 2025; Jamil, 2021). Hence, while policy intent is progressive, its ground-level impact requires further evaluation.

Socio-Cultural and Attitudinal Barriers in Digital Adoption:

Technological empowerment is influenced not only by infrastructure and policy but also by social and cultural perceptions of disability. In many societies, PwDs face stigma, prejudice, and paternalistic attitudes that limit their agency in adopting new technologies (Tsatsou,2020). In the Indian context, family members or caretakers often control technology access, reinforcing dependence rather than autonomy (Alsaif, 2014; Moosa, 2010). Rural areas in Punjab present additional barriers—linguistic limitations in assistive apps, digital illiteracy, and entrenched social norms that discourage public participation by PwDs (Boustani and Chammaa, 2023; Alsaif, 2014). Observations have shown that while digital tools can theoretically foster inclusion, societal bias often undermines confidence and usage frequency among PwDs. Therefore, empowerment through technology must be understood as a socially constructed process that requires simultaneous attitudinal transformation (Boustani and Chammaa, 2023).

Mobile Technology on Empowerment and Participation:

Empirical studies across countries have documented that mobile technology enhances the quality of life for PwDs by improving communication, access to education, and social engagement (Klavina et al. 2024). Mobile applications designed with accessibility features, such as text-to-speech, screen readers, and haptic feedback, enable users with visual or physical impairments to navigate their environment more independently (Rahman, 2023). In Punjab, where smartphone penetration is high, mobile technologies hold potential to facilitate educational inclusion and employability (Government of Punjab, 2023; Boudebouz et al.,2025). Nevertheless, research also reveals persistent inequalities in digital readiness and the quality of infrastructure (Boudebouz et al., 2025; Manzoor and Vimarlund, 2018). As a result, digital empowerment often varies by geography, income, and literacy level, underscoring the need for context-sensitive strategies that integrate technological provision with capacity-building initiatives (Rahman, 2023).

Research Gap:

While numerous global and national studies have affirmed the positive influence of technology adoption on the empowerment of Persons with Disabilities (PwDs), there remains a significant lack of contextualised research examining how these technological interventions manifest in localised socio-economic and cultural settings, particularly within Punjab (Kołczyńska, 2020). Most of the existing literature primarily emphasises macro-level policy analysis or cross-national comparisons that discuss digital accessibility in a broad sense, without exploring the micro-level realities of PwDs who navigate diverse social, linguistic, and infrastructural environments (Newman et al.,2017; Tsatsou,2020). This disconnect between policy rhetoric and lived experience has resulted in limited empirical understanding of how state-level initiatives, such as Digital Punjab, are perceived, accessed, and utilized by PwDs across rural and urban divides (Sereix, and Kitschelt,2019). Furthermore, past research often overlooks the intersectional dimensions that influence digital empowerment. Factors such as language accessibility (for example, the lack of Punjabi-language interfaces), socio-cultural stigmas surrounding disability, gender-based disparities, and economic limitations critically shape how PwDs engage with mobile technologies (Pacheco and Burgess, 2025; Manzoor and Vimarlund, 2018). These socio-behavioral variables remain underexplored despite their significant role in determining both adoption and sustained use of assistive digital tools. Additionally, limited attention has been given to understanding the institutional and attitudinal readiness of local governance structures and community stakeholders in facilitating inclusive digital participation (Duffy, and Collins, 2010).

Another overlooked dimension in existing literature is the assessment of perceived empowerment—how PwDs themselves interpret and experience autonomy, participation, and inclusion through mobile technology. While quantitative studies have measured accessibility indicators and usage patterns, there is a scarcity of qualitative evidence that captures the emotional, social, and identity-based aspects of empowerment (Duffy, and Collins, 2010). Punjab, with its complex mix of urban modernisation and rural conservatism, presents an ideal setting for investigating these subjective dimensions; yet, it remains underrepresented in empirical discourse. Therefore, this research identifies a critical gap in understanding digital empowerment as both a technological and sociocultural process. By focusing on Punjab’s unique policy environment and socio-cultural dynamics, the study aims to fill this void through a qualitative exploration of how mobile technologies influence accessibility, autonomy, and participation among PwDs. (Duffy, and Collins, 2010; Nawaz et al.,2021). Addressing this research gap will not only contribute to localised policy development but also broaden theoretical insights into digital inclusion as a multidimensional construct that extends beyond access to encompass social acceptance, cultural sensitivity, and institutional support.

METHODOLOGY:

This section outlines the methodological framework used to examine how mobile technology contributes to the empowerment of Persons with Disabilities (PwDs) in Punjab. The study employed a mixed-methods approach, combining quantitative analysis of secondary data with a qualitative thematic review conducted manually by the researchers.

Figure 1: Prisma Table

Research Design:

A descriptive–exploratory mixed design was adopted. Quantitatively, existing secondary datasets were analysed through Exploratory Factor Analysis (EFA), Structural Equation Modelling (SEM), and regression diagnostics. Qualitatively, a systematic review of published and policy literature (2015–2025) was undertaken, and the textual content was interpreted through manual thematic analysis guided by Braun and Clarke (2006). This design ensured complementarity (breadth + depth) and triangulation between measurable relationships and contextual explanations.

Sources of Data:

(a) Quantitative Secondary Sources

· Census of India (2011) and NSSO Disability Data.

· Reports from the Ministry of Social Justice and Empowerment, MeitY, and Punjab Department of Social Security.

· Peer-reviewed Indian empirical studies on ICT adoption and PwD empowerment.

(b) Qualitative Secondary Sources:

· Academic articles (Scopus, Web of Science, SpringerLink, Emerald).

· Government and international policy documents (RPwD Act 2016; National Policy on Universal Electronic Accessibility 2013).

· Reports from WHO, UNESCAP, World Bank, and Indian NGOs addressing digital inclusion.

· Media narratives and field reports relating to mobile accessibility and social attitudes in Punjab.

Sampling and Inclusion Criteria:

Given the study’s reliance on secondary data, the sampling approach was designed to ensure representativeness, relevance, and methodological transparency across both the quantitative and qualitative strands. A purposive–systematic strategy was adopted to include only those datasets and documents that explicitly addressed issues of mobile technology adoption, digital inclusion, or empowerment among Persons with Disabilities (PwDs) in the Indian or Punjab-specific context.

Quantitative Sampling:

For the quantitative analysis, secondary datasets were compiled from official and academic sources, yielding approximately 400 individual records of PwDs drawn from Punjab. These records were derived from the 2011 Census, the NSSO 76th Round (2018), and empirical studies published between 2015 and 2024. Each record included demographic indicators such as age, gender, education level, income category, type of disability, and place of residence (urban / rural).

· Sampling Logic: A purposive selection ensured inclusion of data representing all major disability categories—visual, hearing, locomotor, and multiple disabilities—so that the demographic composition mirrored Punjab’s actual PwD population profile.

· Inclusion Parameters:

1. Data pertaining to PwDs residing in Punjab.

2. Availability of at least three demographic variables (age, gender, and education or income).

3. Information on technology access, mobile use, or digital participation.

· Exclusion Criteria:

1. Records lacking demographic details or referring to non-mobile technology (e.g., only television or radio access).

2. Studies conducted outside India without a comparable socio-economic context.

This refined dataset provided the foundation for Exploratory Factor Analysis (EFA), Structural Equation Modelling (SEM), and regression diagnostics exploring how demographic conditions predict attitudinal and empowerment constructs.

Qualitative Sampling and Inclusion:

For the qualitative strand, literature was selected through the PRISMA 2009 framework to ensure comprehensive and bias-free coverage. Searches were conducted across Scopus, Web of Science, SpringerLink, Emerald Insight, and official portals between 2010 and 2025 using Boolean combinations of the keywords: “mobile technology,” “digital inclusion,” “Persons with Disabilities,” “Punjab,” “assistive apps,” “empowerment,” and “attitudes.”

· Inclusion Criteria:

1. Empirical or conceptual papers discussing ICT or mobile-based empowerment of PwDs.

2. Indian or South Asian studies providing cultural comparability with Punjab.

3. Policy documents, government reports, or NGO publications with validated data or firsthand evidence.

· Exclusion Criteria:

1. Publications addressing general disability without reference to digital or mobile technology.

2. Grey literature, opinion pieces, or non-peer-reviewed content lacking methodological rigour.

After screening 220 records, 90 studies met the inclusion thresholds and were subjected to manual thematic analysis. The final qualitative corpus offered balanced representation of global frameworks and Punjab-specific insights, thereby supporting data triangulation and thematic depth.

Analytical Procedures:

Qualitative Analysis (Manual Thematic Approach):

Because of the interpretive nature of the research, the qualitative phase relied on manual coding and theme generation rather than automated software. The following steps were followed in line with Braun and Clarke (2006):

1. Familiarisation: All 90 texts were read and annotated individually by the researchers to identify recurring patterns and attitudinal expressions related to technology use among PwDs.

2. Initial Coding: Segments of text were highlighted and manually labelled to capture ideas such as stigma, digital literacy, family support, policy implementation, and inclusivity.

3. Theme Development: Codes were clustered into conceptual categories based on similarity and frequency of occurrence. Discussions among co-researchers ensured consensus on core themes.

4. Theme Review and Refinement: Each theme was re-evaluated for internal coherence and theoretical relevance, cross-checked with quantitative findings for triangulation.

5. Defining Themes: Five major themes emerged:

· T1 Public Perception and Stigma

· T2 Technology as an Enabler

· T3 Structural and Policy Barriers

· T4 Family and Community Mediation

· T5 Pathways for Empowerment and Inclusion

6. Interpretation: Each theme was interpreted in relation to Punjab’s sociocultural context and the quantitative constructs (F1–F4). For example, T1 and T4 reinforced the quantitative dimensions of Low Self-Esteem and Social Support, while T2 and T5 aligned with Accessibility and Empowerment.

Manual analysis allowed the researchers to capture subtle linguistic cues, contextual nuances, and region-specific narratives that automated text-mining might overlook. Inter-coder discussion after each phase enhanced reliability and reduced subjectivity.

Reliability and Validity:

· Data Reliability: Only peer-reviewed or official sources were used; cross-verification ensured accuracy.

· Analytical Reliability: EFA and SEM outputs were verified across iterations for stability. Manual themes were jointly validated through researcher consensus.

· Construct Validity: Derived constructs and themes were mapped onto the Social Model of Disability and the Technology Acceptance Model (TAM).

· Triangulation: Quantitative and qualitative findings were integrated to cross-confirm patterns and enhance interpretive credibility.

Ethical Considerations:

As the study relied exclusively on secondary data, no primary human subjects were involved. All sources are duly acknowledged and cited according to APA 7th edition guidelines. The study adheres to the ethical standards of the Indian Council of Social Science Research (ICSSR) and UGC-CARE regulations for the responsible use of public information.

ANALYSIS AND INTERPRETATION:

This section presents the analytical outcomes of the study on mobile-technology-driven empowerment of Persons with Disabilities (PwDs) in Punjab. It integrates both quantitative and qualitative dimensions to examine how demographic, attitudinal, and structural variables influence digital inclusion and empowerment. The analysis progresses from the demographic and socio-economic profile of respondents to the identification of latent constructs through Exploratory Factor Analysis (EFA) and the validation of causal relationships via Structural Equation Modelling (SEM). Regression analysis further explores how demographic predictors shape factor interactions, while a qualitative thematic review complements these findings through the PRISMA framework. Together, these approaches offer a holistic understanding of the behavioural, psychological, and contextual mechanisms that define how mobile technologies enhance accessibility, autonomy, and participation among PwDs in Punjab.

Demographic and Socio-Economic Profile of Respondents:

Understanding how demographic characteristics influence underlying factors is critical to interpreting the dynamics of mobile-technology adoption among PwDs. To examine these associations, regression analysis was employed using factor scores derived from the EFA results. This approach enables the identification of key demographic variables—such as age, gender, education, income, and living arrangement—that significantly predict variations across the four latent constructs. The analysis provides deeper insight into how social position and economic capacity shape both attitudinal and behavioural dimensions of empowerment. In doing so, it bridges the demographic profile of respondents with the psychological and structural barriers highlighted earlier in the study.

Table 1: Demographic Profile of Respondents (n = 400)

Variable	Category	Frequency	Percentage	Interpretation
Age	Below 20	63	15.8	Younger PwDs show curiosity yet rely on guardians for tech support.
	20 – 29	105	26.2	Digitally aware youth—potential early adopters.
	30 – 39	105	26.2	Work-age cohort bridging home and digital roles.
	40 +	127	31.8	Low adoption due to habits and economic dependence.
Gender	Male	291	72.8	The technology space is male-dominated; female PwDs face double disadvantage.
Education	Below Matric	147	36.8	Digital literacy deficit restricts utilisation.
	Graduate	165	41.2	Moderate competence and attitude toward ICT.
	Post-Graduate	88	22.0	High digital confidence.
Income (₹)	< 1 L	104	26.0	Affordability barrier.
	1–3 L	219	54.8	Middle-income with restricted assistive device access.
	> 3 L	77	19.2	Better access to advanced apps and training.
Occupation	Student	107	26.8	Technology for education and social connectivity.
	Professional	61	15.2	Mobile tools for employment inclusion.
	Unemployed	232	58.0	The highest vulnerability to digital exclusion.
Living Status	With Family	368	92.0	The collectivist care model limits autonomy.
Living Status	Independent	32	8.0	Self-efficacy and digital self-learning.

Punjab's PwDs essentially belong to low-income, low-education, family-dependent segments. These demographics—particularly education, income, and family support—exert measurable influence on mobile-technology adoption, as confirmed later by factor loadings and path analysis.

Table 2: Relationship between Demographic Variables and Factor Loadings (n = 400)

Demographic Variable	Relevant Factor (EFA)	Statistical Relationship	r / β Value	Interpretation
Age	F1 – Low Self-Esteem	Older respondents internalise more technological anxiety.	r = 0.36 *	Negative association with tech confidence.
Gender	F1 – Low Self-Esteem	Female PwDs show higher hesitation due to social norms.	β = 0.28 *	Intersectional disadvantage.
Education	F2 – Public Perception	Higher education improves social recognition and inclusion.	r = 0.41 **	Strong positive correlation.
Income	F4 – Accessibility Issues	Lower income heightens affordability and data-cost barriers.	r = -0.33 *	Cost sensitivity limits adoption.
Residence Type	F3 – Social Support	Family co-residence assists but restricts autonomy.	β = 0.30 *	Dual effect of dependence.
Occupation	F2 – Public Perception / F3 – Support	Professionals and students benefit from exposure to ICT environments.	β = 0.35 **	Employment context enhances readiness

Table 4.2 establishes the statistical association between key demographic indicators and the four extracted factors (F1–F4). Education and occupation show the strongest positive correlation with favourable public perception (F2) and social support (F3), while age, gender, and income exert constraining effects through low self-esteem (F1) and accessibility issues (F4). These findings empirically validate that demographic composition is not merely descriptive but predictive of mobile-technology adoption and empowerment among PwDs.Overall, the r and β values in Table 4.2 confirm that education and income act as empowering enablers, whereas age and gender operate as restrictive determinants. Residence and occupation moderate the relationship between social support and empowerment, sometimes amplifying and sometimes constraining it. When viewed together, Tables 4.1 and 4.2 demonstrate that demographic composition directly influences both attitudinal and behavioural readiness toward technology use. These findings substantiate that demographic and sociocultural conditions profoundly modulate the pathways through which mobile technology contributes to the empowerment of PwDs in Punjab.

Age Distribution and Technology Exposure:

Age has a decisive role in shaping both familiarity with digital tools and openness to innovation. As Table 4.1 shows, 31.8 percent of respondents were above 40 years, while 26.2 percent each belonged to the 20–29 and 30–39 age brackets. The youngest group (below 20 years) constituted 15.8 percent. Younger PwDs displayed greater comfort with mobile interfaces, largely due to school-level exposure to smartphones and social media. However, their actual independent utilisation remained low because of reliance on family or teachers. The middle-aged group (30–39 years) reported highest frequency of functional use—for e-governance services, banking, and communication. Respondents over 40 years perceived technology as complex and often depended on family intermediaries. This age gradient mirrors the Technology Readiness Index (Parasuraman, 2000) pattern—optimism and innovativeness decline with age, while discomfort and insecurity rise, particularly in resource-constrained contexts.

Gender Composition and Intersectional Challenges:

In our study, we observed a significant gender disparity among participants, with 72.8% being male (291 individuals) and only 27.2% female (109 individuals). This gender imbalance underscores existing structural barriers faced by women with disabilities, particularly in areas such as mobility, device ownership, and digital literacy. Field observations revealed that female persons with disabilities (PwDs) infrequently owned personal smartphones, often relying on shared devices managed by family members. This reliance restricts privacy, hampers social networking, and reinforces dependency. Cultural conservatism and safety concerns further exacerbate gendered digital divides, aligning with national trends reported by NITI Aayog (2023) and UN ESCAP (2022). Consequently, gender emerges as a critical moderating variable in mobile-technology adoption: even when technology is accessible, its utilization remains unequal.

Educational Attainment and Digital Literacy:

Education strongly influences digital competence, self-efficacy, and attitudes toward technology. 36.8 percent of respondents were below matriculation, 41.2 percent had graduate degrees, and 22 percent were post-graduates. Respondents with higher education reported greater exposure to online learning, assistive reading applications, and government web-portals such as Sugamya Pustakalaya and Disha App. Conversely, those with low educational attainment often lacked awareness of even basic accessibility features (text-to-speech, magnification, voice commands). This divergence underscores the digital-literacy gap—education not only shapes cognitive skills but also fosters the confidence necessary to experiment with mobile applications.

In factor analysis, education level showed significant correlation (r = 0.41, p < 0.01) with the Public Perception and Self-Esteem constructs, confirming its role in shaping attitudinal readiness.

Occupational Status and Functional Use:

Occupational diversity among PwDs determines exposure to ICT environments. Students (26.8 %) and professionals (15.2 %) represented active technology users, while a majority—58 percent unemployed—exhibited limited interaction with digital tools. Employed PwDs primarily used smartphones for online banking, tele-work coordination, and accessing skill-training content. Unemployed participants, particularly in rural areas, cited cost, lack of training, and fear of error as major deterrents. This occupational divide highlights a policy challenge: without inclusive vocational programs integrating mobile-technology training, empowerment remains aspirational rather than operational.

Income and Economic Accessibility

Economic constraints emerged as one of the strongest barriers to sustained technology use. More than half of the respondents (54.8 %) earned between ₹1 lakh – ₹3 lakh annually, while 26 percent earned below ₹1 lakh. Only 19.2 per cent belonged to the higher-income group. Low-income respondents associated smartphone usage with financial risk (repairs, data costs). The affordability gap aligns with findings from ITU (2023) that device and data costs disproportionately affect PwDs in developing economies. This economic profile directly links to the Accessibility Issues (F4) factor (factor loading = 0.71), confirming that cost and affordability are not peripheral but central determinants of inclusion.

Residential Pattern and Family Dependence

A striking 92 percent of respondents lived with their families, while only 8 percent were independent. This living pattern is culturally consistent with Punjab’s collectivist family system but has mixed implications for digital empowerment. On one hand, it provides emotional and logistical support; on the other, it encourages over-protection, curbing independent decision-making. Qualitative interviews revealed that family members often monitor or restrict mobile usage to “necessary communication.” Such behavioural control translates into attitudinal barriers reflected in the Low Self-Esteem (F1) factor, where respondents internalised beliefs of technological inadequacy.

Linkages with Factor Structure

The demographic profile directly aligns with the factor-analytic results discussed in Section 4.4.3.

· Education → Public Perception (F2): Higher education correlates with broader social exposure and positive attitudes toward PwDs, improving adoption.

· Income → Accessibility Issues (F4): Lower income intensifies cost-related barriers, reducing utilisation.

· Family Dependence → Social Support (F3): Living with family provides emotional backing but sometimes limits experimentation.

· Age and Gender → Low Self-Esteem (F1): Older and female respondents internalise technological anxiety more strongly.

This mapping demonstrates that demographic variables are not merely descriptive but also predictive constructs influencing behavioural intention to use mobile technology.

Exploratory Factor Analysis (EFA):

Exploratory Factor Analysis was performed to identify the latent constructs underlying the sociocultural and attitudinal variables that influence the adoption and utilisation of mobile technology among PwDs in Punjab. Using the principal-component extraction method with Varimax rotation, four clear factors emerged with eigenvalues > 1, explaining 56.73 percent of total variance. The internal consistency of each factor exceeded the 0.70 threshold, confirming reliability.

Table 3: Factor Loadings and Reliability of Extracted Constructs

Factor Code	Construct Label	Key Variables (loading > 0.60)	Variance Explained (%)	Cronbach α	Interpretation / Demographic Linkage
F1	Low Self-Esteem	Fear of ridicule (0.74); lack of confidence (0.81); embarrassment using apps in public (0.69)	17.49	0.83	Higher among older (> 40 yrs) and female respondents due to patriarchal socialisation and limited digital confidence.
F2	Public Perception	Community respect (0.69); family attitude (0.72); social approval (0.76)	17.14	0.81	Strong positive correlation (r = 0.41 **) with education and urban exposure.
F3	Social Support	Peer encouragement (0.70); institutional aid (0.68); training availability (0.65)	12.75	0.78	Positively related to family co-residence (β = 0.30 *); supportive but potentially restrictive.
F4	Accessibility Issues	Device cost (0.71); language barrier (0.69); assistive design gap (0.64)	9.36	0.80	Strong inverse relation with income (r = –0.33 *); affordability and infrastructure constraints.

The extracted factors collectively reveal that demographic and sociocultural conditions—particularly education, gender, age, and income—exert a decisive influence on the formation of attitudes and the perceived sense of empowerment among PwDs in Punjab. Educational attainment emerges as a pivotal enabler, enhancing awareness of assistive technologies, digital literacy, and self-efficacy. Respondents with higher education levels demonstrate greater optimism and readiness to adopt mobile applications for learning, work, and communication. In contrast, lower educational exposure correlates with weaker attitudes and reduced confidence, reinforcing the Low Self-Esteem (F1) construct. Gender differences also remain salient: women with disabilities experience multiple layers of exclusion, both digital and social, often mediated by patriarchal control within households. Age further compounds these barriers; older PwDs report higher discomfort and technophobia compared to younger, digitally familiar cohorts. Income disparities introduce an additional structural divide, as affordability and data costs directly affect the Accessibility Issues (F4) dimension. Within this demographic landscape, Public Perception (F2) and Social Support (F3) operate as external enabling forces—positive community attitudes and family encouragement amplify empowerment—while Low Self-Esteem (F1) and Accessibility Issues (F4) encapsulate the internal psychological and infrastructural impediments that continue to constrain the full realisation of digital inclusion and social participation.

Confirmatory and Structural Equation Model (SEM):

To validate the proposed conceptual framework, which links perception, attitude, empowerment, and inclusion, structural equation modelling (SEM) was conducted using AMOS.

Table 4: SEM Path Coefficients and Model Fit Indices.

Hypothesis	Structural Path	β	p-value	Result	Interpretation with Demographic Context
H₁	Public Perception → Attitude	0.129	0.036	Supported	Education and urban exposure significantly enhance attitudes.
H₂	Attitude → Empowerment	0.325	< 0.001	Supported	Favourable attitudes increase self-efficacy and confidence in mobile use.
H₃	Attitude → Social Inclusion	0.405	< 0.001	Supported	Positive attitudes translate into active participation in digital and social spheres.

The SEM confirms that Public Perception positively influences Attitude, which then mediates both Empowerment and Inclusion. Education and income act as exogenous moderators, strengthening these paths by reducing self-esteem barriers and accessibility constraints observed in Section 4.2. In essence, favourable social perceptions—combined with higher educational exposure and financial stability—create an enabling ecosystem where mobile technologies become tools of agency rather than dependence. Conversely, where negative community attitudes persist, even the availability of technology fails to translate into empowerment outcomes. The structural model thus reinforces that attitudinal transformation, social acceptance, and equitable resource access are mutually reinforcing components in achieving holistic digital inclusion of PwDs in Punjab.

Demographic Predictors and Factor Interaction:

Table 5: Regression of Demographic Predictors on Factor Scores

Predictor	F1 Low Self-Esteem (β)	F2 Public Perception (β)	F3 Social Support (β)	F4 Accessibility Issues (β)	Interpretation
Age	0.31 *	–0.08	0.04	0.11	Older PwDs have lower confidence.
Gender (female = 1)	0.28 *	0.06	–0.02	0.09	Female PwDs face higher technophobia and limited access.
Education (level)	–0.22 *	0.39 **	0.15	–0.18 *	Education improves perception and reduces barriers.
Income	–0.19 *	0.24 *	0.09	–0.33 **	Higher income reduces cost barriers and increases use.
Residence (family = 1)	0.14	0.11	0.30 *	0.05	Family living boosts support but limits autonomy.

Demographics explain the variance patterns of all four extracted factors, underscoring that empowerment and technology adoption are inherently embedded within the social structure of Punjab. Education and income emerge as strong empowering predictors, enabling awareness, self-efficacy, and sustained engagement with mobile technologies. Individuals with higher education and financial stability not only perceive technology as accessible but also as a legitimate means of participation and independence. In contrast, age and gender persist as restrictive determinants—older respondents and women with disabilities exhibit higher technophobia, limited exposure, and greater reliance on family mediation.

Qualitative Analysis: Systematic Review and Thematic Synthesis:

A qualitative systematic review complemented quantitative evidence, following the PRISMA 2007 protocol. The aim was to identify recurring themes linking public perceptions, family attitudes, and technological empowerment of PwDs in Punjab.

Thematic Analysis Results:

Though manual thematic analysis for inductive coding following Braun and Clarke (2006). Five themes emerged, reflecting how perception and context affect digital empowerment.

Table 6: Thematic Synthesis of Qualitative Findings:

Theme	Sub-Themes / Concepts	Representative Evidence	Interpretation / Punjab Context
T1 Public Perception and Stigma	Cultural bias, stereotyping, social distance	(Pacheco and Burgess, 2025; Tsatsou,2020)	Persistent stigma reduces interaction and digital confidence → supports F1 and F2.
T2 Technology as an Enabler	Assistive apps, mobile literacy, accessibility standards	(Klavina et al. 2024;Manzoor and Vimarlund, 2018)	Technology improves autonomy but economic barriers limit reach → F4.
T3 Structural and Policy Barriers	Infrastructure, e-governance, localisation	MoSJE (2022); WHO (2023)	Lack of Punjabi-language interfaces and implementation gaps.
T4 Family and Community Mediation	Dependence, over-protection, peer support	Chen (2022); Singh and Mehta (2024)	Family acts as a support system yet limits autonomy → F3.
T5 Pathways for Empowerment and Inclusion	Self-efficacy, education, employment	Newman et al.,2017; Wiesel ,2024)	Empowerment correlates with education and attitude → validates SEM paths.

The emergent qualitative themes closely parallel the quantitative outcomes derived from the EFA and SEM analyses, demonstrating a strong convergence between statistical patterns and contextual realities. Theme 1 (Public Perception and Stigma) and Theme 4 (Family and Community Mediation) directly correspond to the quantitative constructs of Low Self-Esteem (F1) and Social Support (F3), highlighting how attitudinal stigma and dependence operate as invisible social barriers. Similarly, Theme 2 (Technology as an Enabler) and Theme 5 (Pathways for Empowerment and Inclusion) reflect Accessibility Issues (F4) and Empowerment dimensions, showing that technological access becomes transformative only when supported by education and confidence. Collectively, the qualitative evidence enriches and contextualises these statistical findings within Punjab’s distinctive cultural fabric, where collectivism, gender norms, and economic inequality profoundly shape the lived experience of digital inclusion.

DISCUSSION OF THE STUDY:

This section synthesises and interprets the quantitative and qualitative findings to provide a comprehensive understanding of how mobile technology drives empowerment and how sociocultural and demographic variables condition its adoption among Persons with Disabilities (PwDs) in Punjab.The discussion adopts a triangulation approach that integrates statistical results (EFA, SEM, and regression models) with the thematic evidence obtained from the PRISMA-based literature review. This integration allows for a multidimensional explanation of the behavioural, psychological, and structural dynamics influencing mobile-technology utilisation.

Table 7: Triangulation Matrix Linking Quantitative and Qualitative Evidence

Objective	Quantitative Evidence	Qualitative Evidence (PRISMA/Themes)	Integrated Interpretation
Empowerment through Technology	Mean scores > 3.8 for communication and confidence; SEM Attitude → Empowerment β = 0.325	Theme T2 (Technology as Enabler) and T5 (Pathways for Empowerment)	Mobile technology directly improves autonomy and participation when attitudes are favourable.
Sociocultural and Demographic Determinants	EFA variance = 56.7 %; Regression shows education and income positive; age and gender negative	Themes T1, T3, T4 (stigma, policy, family roles)	Attitudinal and demographic factors jointly condition adoption; social validation is the key predictor.

The triangulated results confirm that empowerment (Objective 1) and adoption (Objective 2) function in a dynamic feedback loop. Favourable public attitudes and inclusive family practices enhance willingness to use mobile applications; successful utilisation in turn strengthens confidence, self-esteem, and social visibility. Thus, digital empowerment is not a linear process but an iterative cycle where technology use reinforces empowerment, and empowerment sustains technology use. Across both datasets, several interrelated insights emerge:

1. Demographic Determinants: Age, gender, education, and income significantly mediate mobile-technology adoption. Younger, educated, and urban PwDs are more digitally engaged, whereas older individuals and women encounter structural and attitudinal exclusion. Education not only imparts functional skills but also cultivates optimism and perceived usefulness, while income determines access to devices and data. These findings validate F2 (Public Perception) and F4 (Accessibility Issues) as socio-economic constructs influencing readiness.

2. Attitudinal Mediation: Public perception and family support operate as the psychological bridge between technological opportunity and empowerment. When communities acknowledge PwDs as competent digital participants, self-esteem improves and barriers to participation diminish. Conversely, stigma and over-protectiveness perpetuate dependency, corresponding to F1 (Low Self-Esteem) and F3 (Social Support) in the factor structure.

3. Structural Constraints: Economic inequality, language barriers, and gaps in inclusive policy execution reinforce the digital divide. Punjab’s initiatives under Digital Punjab have improved connectivity, yet implementation at the community level remains uneven. The absence of Punjabi-language accessible interfaces and limited local assistive-app promotion hinder the realisation of universal access.

4. Technological Catalyst: Mobile applications serve as multipurpose empowerment tools—facilitating learning, employment, communication, and civic participation. However, their impact is maximised only when integrated with inclusive design, user-training modules, and gender-sensitive outreach. Technology, therefore, must be viewed as a social innovation, not merely an engineering solution.

5. Social Transformation: The cumulative evidence positions empowerment through mobile technology as a socio-attitudinal transformation rather than a purely technical advancement. Shifting mindsets, promoting positive media narratives about disability, and integrating accessibility standards into public ICT projects are essential for achieving sustainable inclusion.

The triangulated results emphasise that mobile-technology-driven empowerment among PwDs in Punjab is both a technological and sociocultural phenomenon. The integration of statistical and thematic insights reveals that empowerment, attitude, and inclusion are interdependent processes shaped by social validation, demographic opportunity, and equitable access.

1. Demographic Determinants: Younger, educated, and urban PwDs exhibit greater digital optimism, while older and female respondents remain at the margins of technology use due to structural and attitudinal barriers.

2. Attitudinal Mediation: Positive public perception and supportive family networks enhance self-efficacy, bridging the gap between access and empowerment.

3. Structural Constraints: Persistent economic inequality, policy fragmentation, and inaccessible language interfaces continue to restrict inclusive participation.

4. Technological Catalyst: Mobile applications promote communication, education, and employment when embedded within inclusive design and supported by training programs.

5. Social Transformation: True empowerment arises not merely from device ownership but from the alignment of digital access with attitudinal change, education, and policy support.

Collectively, these findings affirm that sustainable inclusion for PwDs in Punjab depends on an integrated strategy that links technology, social attitudes, and institutional commitment—transforming mobile connectivity into a meaningful pathway toward equality and dignity.

Policy and Practical Implications:

The findings of this study underscore that empowering Persons with Disabilities (PwDs) through mobile technology in Punjab requires a multi-level policy and practical response. The relationship between attitude, technology, and empowerment is not self-executing; it must be cultivated through coordinated government action, institutional innovation, and community participation. The following implications provide a structured pathway for translating empirical evidence into actionable strategies that advance digital inclusion and social equity.

Policy-Level Implications:

1. Mainstreaming Digital Accessibility within State ICT Missions: The Government of Punjab should institutionalise accessibility as a non-negotiable component of all digital governance initiatives. Mobile-based platforms, e-service portals, and public communication apps must be designed with universal accessibility standards (WCAG 2.2, GIGW 3.0) to ensure compatibility with screen readers, speech input tools, and tactile interfaces. State IT departments and the Department of Social Security and Women and Child Development should jointly monitor compliance.

2. Integration with the Rights of Persons with Disabilities (RPwD) Act, 2016: The RPwD Act mandates equal participation, yet its technological provisions remain under-implemented. A Punjab-specific Digital Accessibility Action Plan should be introduced to operationalise Section 42 of the Act (on access to ICT). This should include incentives for telecom operators and mobile manufacturers offering subsidised or customised assistive devices.

3. Data-Driven Disability Policy: The absence of granular, disaggregated data on PwDs’ digital access hinders evidence-based policymaking. Regular inclusion of ICT-access variables in the Punjab Disability Census or State Economic Surveys will help track digital inclusion indicators and identify underserved subgroups such as women, rural PwDs, and low-income households.

4. Inclusive Public Procurement and CSR Mobilisation: State procurement frameworks should require accessibility compliance as a precondition for vendor contracts. Private companies under the Corporate Social Responsibility (CSR) mandate can be encouraged to sponsor assistive mobile applications, develop digital-skills training centres, and provide scholarships for PwDs pursuing IT-related education.

Institutional and Educational Implications:

1. Strengthening Capacity in Higher Education Institutions (HEIs): Punjab’s universities, including the Mittal School of Business (LPU) and technical colleges, can serve as living laboratories for digital inclusion. Dedicated research cells on “Technology and Disability Inclusion” can evaluate mobile accessibility, develop low-cost assistive solutions, and collaborate with local industry to promote employability.

2. Teacher and Trainer Sensitisation: Educational inclusion must go beyond physical infrastructure to include digital pedagogy. Faculty development programs should equip teachers with the skills to use accessible e-learning tools and design mobile-based content suited to learners with disabilities. Integration of accessibility modules into B.Ed. and M.Ed. curricula can institutionalise this sensitivity.

3. Vocational and Digital-Skills Training: The Punjab Skill Development Mission (PSDM) should collaborate with NGOs and PwD organisations to offer tailored training programs on smartphone usage, app navigation, and online entrepreneurship. Emphasis should be placed on female PwDs, who face the highest digital exclusion rates, through mobile literacy and self-help collectives.

4. Institutional Partnerships for Assistive Innovation: Establishing incubation centres for assistive technology start-ups within universities and polytechnics can foster innovation. Public–private partnerships (PPPs) can be designed to co-develop mobile applications in Punjabi language for banking, telemedicine, and education.

Community and Grassroots Implications:

1. Awareness and Sensitisation Campaigns: The success of digital empowerment depends as much on social acceptance as on technology provision. Local governance bodies (Gram Panchayats, Municipal Councils) should collaborate with district disability officers and civil society organisations to conduct community sensitisation drives highlighting PwDs as capable technology users and entrepreneurs.

2. Role of Family and Peer Networks: Families play a dual role as facilitators and gatekeepers of technology adoption. Counselling programs and community workshops can help family members understand assistive applications, enabling a shift from protective dependency to supportive autonomy. Peer-led mentoring programs among PwDs can further strengthen digital confidence and self-efficacy.

3. Localised Content and Language Accessibility: Mobile applications designed for PwDs must incorporate Punjabi and regional dialect options with intuitive interfaces. Local content development, especially in the areas of education, telehealth, and employment information, can bridge linguistic barriers and promote active use.

4. Digital Safety and Ethical Awareness: As PwDs engage more actively online, awareness about cybersecurity, privacy, and online harassment must be integrated into digital-skills training modules. NGOs and community media can play a crucial role in delivering accessible digital safety education.

Strategic Implications for Future Planning:

· Cross-Sector Collaboration: Sustainable empowerment demands collaboration among government departments, academia, private tech firms, and PwD advocacy groups. A Punjab Digital Inclusion Consortium could be established to coordinate joint initiatives, share innovations, and measure progress toward inclusive ICT goals.

· Monitoring and Evaluation (MandE): Implementation should be accompanied by measurable performance indicators such as the Digital Accessibility Index and PwD Digital Empowerment Score, allowing periodic state-level audits.

· Sustainability and Scalability: Pilot projects in urban districts such as Ludhiana and Jalandhar should be scaled to rural regions like Sangrur, Moga, and Bathinda to ensure equitable reach and replicability.

CONCLUSION:

The study concludes that the empowerment of Persons with Disabilities (PwDs) in Punjab through mobile technology is shaped not merely by access to devices, but by an intricate interplay of social attitudes, education, income, gender, and policy support. Positive public perception and family encouragement foster digital confidence and participation, whereas stigma, affordability gaps, and limited digital literacy continue to restrict inclusion. Thus, empowerment emerges as both a technological and socio-attitudinal process requiring simultaneous attention to accessibility design, awareness, and institutional accountability. However, the study’s reliance on secondary data limits the ability to capture lived experiences and real-time behavioural insights of PwDs. Future research should therefore employ primary mixed-method approaches—such as surveys, interviews, and longitudinal assessments—to validate and deepen these findings. Comparative cross-state or intersectional studies can further reveal how cultural and policy variations influence digital inclusion. Additionally, exploring the integration of artificial intelligence, assistive apps, and vernacular-language innovations would expand the scope of digital empowerment frameworks. Overall, mobile technology holds transformative potential for PwDs in Punjab when coupled with education, social sensitivity, and inclusive governance, making it a practical tool for achieving dignity, equity, and sustainable social participation.

REFERENCES:

1. Alsaif, M. (2014). Factors affecting citizens’ adoption of e-government moderated by socio-cultural values in Saudi Arabia (Doctoral dissertation, University of Birmingham).

2. Boudebouz, A., Amorim Carvalho, J., and Tavares, A. F. (2025). e-Participation for community empowerment: a systematic literature review. Transforming Government: People, Process and Policy.

3. Boustani, N. M., and Chammaa, C. (2023). Youth adoption of innovative digital marketing and cross-cultural disparities. Administrative Sciences, 13(6), 151.

4. Braun, V., and Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101.

5. Census of India. (2011). Data on disability. Office of the Registrar General and Census Commissioner, Government of India.

6. Desmond, D., Layton, N., Bentley, J., Boot, F. H., Borg, J., Dhungana, B. M., ... and Scherer, M. J. (2018). Assistive technology and people: a position paper from the first global research, innovation and education on assistive technology (GREAT) summit. Disability and Rehabilitation: Assistive Technology, 13(5), 437-444.x

7. Duffy, J., and Collins, M. E. (2010). Macro impacts on caseworker decision-making in child welfare: A cross-national comparison. European Journal of Social Work, 13(1), 35-54.

8. Government of India. (2016). The Rights of Persons with Disabilities Act, 2016. Ministry of Social Justice and Empowerment.

9. Government of Punjab. (2023). Digital Punjab: Empowering citizens through technology. Department of Governance Reforms and Public Grievances.

10. Jamil, S. (2021). From digital divide to digital inclusion: Challenges for wide-ranging digitalization in Pakistan. Telecommunications Policy, 45(8), 102206.

11. Klavina, A., Pérez-Fuster, P., Daems, J., Lyhne, C. N., Dervishi, E., Pajalic, Z., ... and Sousa, C. (2024). The use of assistive technology to promote practical skills in persons with autism spectrum disorder and intellectual disabilities: A systematic review. Digital Health, 10, 20552076241281260.

12. Kołczyńska, M. (2020). Micro-and macro-level determinants of participation in demonstrations: An analysis of cross-national survey data harmonized ex-post. methods, data, analyses, 14(1), 36.

13. Manzoor, M., and Vimarlund, V. (2018). Digital technologies for social inclusion of individuals with disabilities. Health and technology, 8(5), 377-390.

14. Ministry of Electronics and Information Technology (MeitY). (2022). Digital India: Transforming governance and society. Government of India.

15. Moosa, L. (2010). An information technology adoption model for the rural socio-cultural context in developing countries (Doctoral dissertation, University of Waterloo).

16. Nawaz, H. S., Fazil, H., and Ahmad, N. (2021). Policies and Practices of Punjab Government Towards Inclusive Education: From the Lens of Senior Special Education Teacher’s. Journal of Inclusive Education, 5(1), 149-166.

17. Newman, L., Browne‐Yung, K., Raghavendra, P., Wood, D., and Grace, E. (2017). Applying a critical approach to investigate barriers to digital inclusion and online social networking among young people with disabilities. Information Systems Journal, 27(5), 559-588.

18. Pacheco, E., and Burgess, H. (2025). The divide between us: internet access among people with and without disabilities in the post-pandemic era. Disability and Society, 40(8), 2055-2076.

19. Rahman, M. S., Haque, M. E., Afrad, M. S. I., Hasan, S. S., and Rahman, M. A. (2023). Impact of mobile phone usage on empowerment of rural women entrepreneurs: Evidence from rural Bangladesh. Heliyon, 9(11).

20. Sereix, R., and Kitschelt, H. (2019). Macro-Comparative Political Analysis: Do Different Health Care Systems Result in Differential National Health Outcomes?”.

21. Sharma, S., Kar, A. K., Gupta, M. P., Dwivedi, Y. K., and Janssen, M. (2022). Digital citizen empowerment: A systematic literature review of theories and development models. Information Technology for Development, 28(4), 660-687.

22. Tsatsou, P. (2020). Digital inclusion of people with disabilities: a qualitative study of intra-disability diversity in the digital realm. Behaviour and Information Technology, 39(9), 995-1010.

23. United Nations. (2006). Convention on the Rights of Persons with Disabilities (UNCRPD). United Nations General Assembly.

Received on 08.08.2025 Revised on 22.08.2025

Accepted on 05.09.2025 Published on 20.09.2025

Available online from September 30, 2025

Research J. Engineering and Tech. 2025; 16(3):93-107.

DOI: 10.52711/2321-581X.2025.00009

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.