IIMS Journal of Management Science
issue front

Sushmita Singh1,2 and S. K. Singh2

First Published 29 Sep 2022. https://doi.org/10.1177/0976030X221113980
Article Information Volume 14, Issue 1 January 2023
Corresponding Author:

Sushmita Singh, Sushmita Singh, Parul University, Vadodara, Gujarat 391760, India; Institute of Management, BHU, Varanasi, Uttar Pradesh 221005, India.
Email: sushmitasingh@fmsbhu.ac.in,sushmita.sa@gmail.com

1 Parul University, Vadodara, Gujarat, India

2 Institute of Management BHU, Varanasi, Uttar Pradesh, India

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed.


The study investigated work-related well-being among handloom weavers of Varanasi. The various dimensions of work-related well-being were work engagement, job satisfaction and occupational stress. The work also focused on inter-dimensional relationship of various components of work-related well-being. A cross-sectional survey design with random sampling method was used, and 325 handloom weavers were part of the survey. Exploratory factor analysis and confirmatory factor analysis was used to explore and validate the measurement instrument for work-related well-being. Pearson product-moment correlation coefficients were used to investigate the relationships among various dimensions. The model was tested using structural equation modelling on AMOS 22 platform. The outcomes were suggestive of a three-factor model of work-related well-being which included work engagement, occupational stress and job satisfaction as the components. The findings suggested that job satisfaction positively characterizes work-related well-being followed by work engagement. Occupational stress negatively explains work-related well-being.


Handloom weavers, job satisfaction, job demands, job resources, work engagement, work-related well-being

What Is Known About the Topic?

  • The work-related well-being has been validated with either three or four interrelated dimensions.
  • The model has been validated in organized sector.
  • The concept of work-related well-being has been an important concept in organizational psychology.

What Does the Article Add To It?

  • Work-related well-being model has not been validated in unorganized sector like handlooms.
  • This validation includes modification in the current context which can be applied to similar labour-extensive sectors. The validation of job demands and resources (JD-R) measurement model in the current context was an important contribution.
  • The handloom weaving is a strenuous activity; hence, studying workplace well-being in weavers becomes even more important. This holistic study can be useful for policymakers and labour economics.


Workplace stress has been an important facet in social psychological research (Cooper et al., 2001). Danna and Griffin (1999) are of the opinion that well-being should be perceived as workers satisfaction from various components of work such as job satisfaction and work-related aspects. Earlier studies of employee well-being generally suggested that happiness is synonymous to job satisfaction, and the presence of positive affects means the absence of negative effects (Cropanzano & Wright, 2001). Affective well-being is not only about social, cognitive and psychosomatic well-being, rather it is fulcrum of occupational well-being (van Rijswijk et al., 2004). Positive and negative feelings are strongly irretrievably associated with well-being (Watson & Tellegen, 1985). Positive affect is about intensity to which the individual experiences delight. Negative affect means unpleasant feeling. Handloom weavers face a lot of difficulty in terms of working conditions, wages and competition from power looms. Due to long seating hours and repetitive actions during weaving, it becomes physically strenuous leading to musculoskeletal disorders (Durlov et al., 2014). Taking into account the stressful conditions faced by the weavers, the researcher has tried to investigate the work-related well-being among handloom weavers.

Literature Review

Well-being at workplace has gained attention in recent years (Rothmann & Coetzer, 2002; van der Colff & Rothmann, 2009). It has become an important antecedent for productivity of employees and organization as a whole (Wright & Cropanzano, 2004; Wright et al., 2007), absenteeism from work, attrition and poor performance at workplace (Cropanzano & Wright, 2001). Work forms an integral part of our lives, because it is the source of earning which in turn affects various other activities of our lives. Not only it consumes a major chunk of individuals time but it also affects one’s life’s goals, personal relationships and social life. Subjective well-being is an important reflector of individuals well-being (Kahn & Juster, 2002). Well-being related to workplace also needs focus, as most of the times, it is considered as measure of job satisfaction. Daniels (2000) brought attention on the phenomena underlying the work. According to Cropanzano and Wright (2001), job satisfaction, burn out, occupational stress and work engagement form the dimensions of affective work-related well-being. Several studies have been conducted in professions such as health care professionals in this regard (Bennett, 2004; Ramirez et al., 1996). Studies have been conducted on ambulance professionals, and it has been found that lower the job satisfaction, greater is the amount of burn out (Young & Cooper, 1997). Lomas (2019) have also advocated for a multidimensionality of work-related well-being, that is, psychological drivers, physical drivers and sociocultural drivers. Though the multidimensionality arises from work engagement and job satisfaction. These two concepts are considered to be the base theories.

In India, the handloom weavers face a lot of occupational stress and lower job satisfaction. The hand weaving work requires long seating hours and concentration with repetitive actions leading to stress (Koiri, 2020). So the study aims to propose a three-dimensional model of work-related well-being which would help to measure the affective work well-being among the handloom weavers.

Dimensions of Well-Being

Affective well-being is measured pertaining to a particular domain which is equally applicable to work-related well-being (Warr, 1990). This article aims to investigate the dimensions of work- related well-being by the help of exploratory factor analysis (EFA) and further use of first order confirmatory factor analysis (CFA) to confirm the determinants of well-being. Several studies have been conducted in different professions such as ambulance professionals (Daniels, 2000) and South African police personnel (Rothmann & Coetzer, 2002). A four-factorial model with separate yet related factors (satisfaction, occupational stress, burnout and engagement) was validated for work-related well-being in South African police force. The components of work-related well-being have been validated and suggested relationship between work engagement, job satisfaction, burnout, job demands and resources and happiness in Zimbabwean bus drivers (Buitendach et al., 2016). The four factorial model is confirmed in medical laboratory settings in India (Narainsamy & van der Westhuizen, 2013). Perceived organizational support and emotional stability act as important antecedents for work-related well-being in ambulance personnel, and a three-factor model has been validated, namely job satisfaction, engagement and stress (Soh et al., 2016). Van der Vaart and de Beer (2021) have emphasized on the trade-off between burn out and engagement among the South African employees. Sometimes, dedication among the employees come at a price in the form of increased burnout. Multidimensional positive psychological interventions are the ways towards workplace well-being and good performance (Donaldson et al., 2022). In case of handloom weavers, the dimensionality had to be established first. Handloom sector is successful in drawing the attention of work-related well-being concept as the weavers face a lot of difficulties at their workplace in terms of wages, poor working conditions and ergonomical issues. Long working hours in static position and postural problems due to archaic looms are the reasons for stress (Rahman et al., 2017). So, first of all, the dimensions need to be verified which can together make up work-related well-being. Previous models cannot be used directly because the handloom sector in India is basically unorganized. Warr (1990) suggested dimensions of affective, work-related well-being which comprised of enthusiasm–depression (engagement is the indicator), anxiety–comfort (occupational stress is the indicator) and pleasure–displeasure (job satisfaction is the indicator). Job satisfaction is a multifaceted abstract; intrinsic and extrinsic job satisfaction are the two essences of this concept. Intrinsic occupation fulfilment is about people feeling about the work action and assignments, whereas extrinsic employment fulfilment is about how the individual feels about the functioning conditions which are at the outside the work (Hirschfeld, 2000). According to Warr (2002), job satisfaction is a component of pleasure–displeasure dimension of work-related well-being. When the external environment creates an imbalance between emotional and cognitive surrounding, outcome is in the form of occupational stress. Stress is conceptualized as a mindboggling process that comprises of three noteworthy segments, to be specific: (a) cause of stress that are experienced in the workplace; (b) recognition and evaluation of a specific reason for stress by a worker; and (c) the passionate responses that are evoked when a reason is assessed as undermining (Lazarus, 1991; Spielberger et al., 2003). Endurance of stress for a longer duration may result adverse changes in behaviour (Spielberger et al., 2003). Occupational stress is comprised of two constructs job demands and lack of resources (Rothmann, 2008). There are various characteristics which have effect on workers well-being. Many models were of the opinion that job characteristic have an effect on workers functioning (Hackman & Oldham, 1976; Karasek, 1979). Job Demand is a concept which includes any physical, mental, social activity which requires continuous physical or mental (intellectual and enthusiastic) exertion which is often associated with physiological and mental expenses (Bakker & Demerouti, 2007). Job resources are those aspects of job which are useful in achieving work goals, decreasing job demands and promoting learning and development (Bakker et al., 2007). JD-R model has been studied in different occupational context such as students’ misbehaviour with teachers (Bakker et al., 2007), occupational job demands and work-related social support in case of nurses in Sweden. Work engagement is termed as positive and satisfying state of mind at work which is identified by vigour, absorption and dedication. Work engagement is an enduring cognitive state of mind process and not a short lived one. Work engagement is all about employee and his relationship with his work that he performs, whereas employee engagement refers to the relationship with the organization where he is working (Schaufeli, 2013). The study is based on precisely the work engagement aspect. The concept is further substantiated by the multidimensional approach which discusses about difference between organizational engagement and work engagement (Saks, 2006). It considers employee engagement as a unique concept which combines emotional, behavioural and cognitive parameters associated with one’s work/task performance.

Research Methodology

Contextual Importance

Researchers over last decades have shown interest on positive psychological aspects of individuals well-being at work (Maddux, 2008). Employee well-being is not just sheer absence of any disorders, it includes presence of positive psychological resources (Sin & Lyubomirsky, 2009). The handloom industry is a trademark of India’s centuries-old tradition of art and weaving. It has helped India in making a mark on global platform because of unmatched intricacies in the designs. Almost all the state of India has something unique to contribute in handmade fabrics such is the tradition of hand weaving. The industry is expected to employ around 17.8 million people by the year 2022. The sector contributes 4% to the gross domestic product (GDP) of the country. In handloom sector, all weaving work is carried out by hands, and it requires minimum use of power, thus making it an eco-friendly production. But the flip side reveals challenges associated such as tough working conditions, lower wages, difficulty in getting credit facility and irregular raw material supply. Handloom weaving involves pre-weaving activity which requires manual sorting of raw materials and dyeing the fibres with acid and chrome. Thereafter, boiling the fibre in acetic acid and dye solution followed by washing and drying. The hand operated looms require the weavers to sit at the loom and operate foot pedals that hang below in the pit. To perform this, there is repetitive movement of the upper and lower limbs to operate pedals and shuttles, and the arms are raised away from the body. Post-weaving activities include cutting out the threads, edge bending and chemical washing to produce the final product. In addition to postural issues, workers are exposed to noise and dust pollution while carrying out the weaving (Nag et al., 2010). Musculoskeletal pain and other postural disorders have been reported among weavers due to such strenuous activities (Durlov et al., 2014). These factors can be important contributors for occupational stress which is a result of job demands exceeding job resources. Here, in this context, the weaving activity is quite demanding on the part of production, and, hence, negative aspects may affect the work-related well-being among the weavers. Hand weaving requires a lot of concentration from the weavers as the slightest of distractions may lead to faulty designs which might not be accepted by the consumers. Also, wastage of raw materials, time and other important resources such as punch cards and loss of opportunity cost because otherwise the loom could have been used for making different fabric. In the light of the above challenges being faced by the weavers, study of work-related well-being becomes important as the problems pertain to areas such as occupational stress, work engagement and job satisfaction.


The aim of the study is to explore and validate job satisfaction, occupational stress and work engagement as components of work-related well-being for handloom weavers.


Work-related well-being among handloom weavers is represented by a hierarchical model with three discrete but interconnected factors, namely work engagement, job satisfaction and occupational stress.

The study was conducted in two phases. Several unstructured interviews and focus group discussions were conducted to find out the relevance of work-related well-being. Thorough literature review was done in order to find out factors and components of work-related well-being. Thereafter, items were generated to form a scale which was further validated using EFA and CFA.


Participants and Procedure

The study was carried out in Varanasi during the period of July–September 2021. A cross-sectional survey design with random sampling method was adopted. About 342 individual handloom weavers were contacted out of which 325 agreed to be a part of the survey. About 90% of the respondents were males and the remaining 10% were females. The females working in weaving industry generally perform the pre- and post-loom activities. The main weaving activity is performed by males only. There were 325 weavers, from which 25% weavers, that is, 82 weavers were 10th pass; 43%, that is, 140 had studied below class 10; 25%, that is, 81 were 12th pass; and remaining 7% were graduate, that is, 23 weavers. The average age was 29 with 6.3 standard deviation. The average years of weaving experience was 11 years with standard deviation of 5.4 years.

Measuring Instrument

For measuring various components of work-related well-being, different modified scales were used. The questionnaire was divided into two parts: the first section dealt with demographics, and the second section was about work-related well-being. Job satisfaction was measured using modified Minnesota scale, that is, MSQ short form, which measures intrinsic and extrinsic job satisfaction. There were 11 items in this modified scale. Occupational stress was measured by JD-R model (Demerouti et al., 2001), that is, job demands and resources model, job demand was measured using pace and amount of work, mental load and physical efforts. Job resources included raw material support, market information, training support and equipment support as constructs (contextual modification was done). Job demands and resources depends upon the particular job characteristics that persists (Bakker et al., 2007). This increases the applicability of this model. Work engagement was measured using modified UWES-9 items scale (Schaufeli et al., 2006). All the responses were recorded on 5-point Likert scale.

Data Analysis

The data was analysed using SPSS 20 version and AMOS 22. Cronbach’s alpha coefficients (α) are measures to find out the internal consistency of the measuring instruments (Clark & Watson, 1995). The values were found to be above the threshold value, that is, 0.7. EFA was conducted for all the measuring scales used. First, a simple principal component analysis was conducted in order to find out the number of factors extracted. The eigenvalues and scree plot were studied. Principal component analysis with varimax rotation was performed to check whether the factors obtained are related or not (Tabachnick & Fidell, 2001). In order to confirm the factors taken, CFA was done using AMOS. Finally, the relationship was investigated among the confirmed components using Pearson product-moment correlation coefficients followed by SEM to study the model fit. SEM is useful multivariate technique used to test and evaluate the causal relationships. It is an amalgamation of CFA and path analysis. It represents the measurement model as well as structural model. Path analysis helps to quantify the relationships among multiple variables, and CFA is the method for measuring latent variables (Byrne, 2013). Since the author has tried to propose a model for work-related well-being in weavers, SEM was applied to study the model fit.


Exploratory Factor Analysis and Confirmatory Factor Analysis

In the present study, principal component analysis was performed on the 34 items measuring different components of work-related well-being as the factor analysis extraction technique. A correlation matrix was analysed to check whether the factor analysis model is appropriate or not. Bartlett’s test of sphericity is the measure of sampling adequacy that gives the idea whether the sample is enough for the evaluation of the factor structure. The Kaiser–Meyer–Olkin (KMO) test allows us to know that the data we have collected is suited to run factor analysis, that is, sufficiency of ratio of responses to scale items. It yielded a value of above 0.7 for all the scales suggesting factorability and substantiating that ratio of responses (325) to scale was acceptable. The items from the scale which were having loadings less than 0.5 were removed. Thereafter, CFA was conducted to confirm and validate the factors.

Job Satisfaction

Job satisfaction scale was extracted into two factors (Table 1) by the help of principal component analysis. Items 1 to 6 were extracted as extrinsic job satisfaction factors. These are the factors which are external to the job and includes dimensions such as working conditions, wages and job security. Items 7 to 11 were named intrinsic job satisfaction factors which had facets about the work itself such as recognition and accomplishment (Hirschfeld, 2000). The measuring scale had KMO value of 0.771 (Table 2), above the threshold value of 0.5. The internal consistency was good as depicted by Cronbach’s alpha value 0.785 which was well above 0.6. The validity of the scale was determined using CFA. The validity was measured for the scale (Table 3). Construct validity is made up of convergent validity and discriminant validity. In order to establish validity of the scale, the values of composite reliability (CR), average variance extracted (AVE), measure share variance (MSV) and average shared variance (ASV) are taken into consideration. For convergent validity, AVE > 0.5, CR > 0.7; and for discriminant validity, MSV < AVE and square root of AVE should be greater than inter-construct correlation or AVE > ASV (Gaskin, 2020).

Table 1. Result of Rotated Component Matrix Which Gave Two Factors for Job Satisfaction Scale

Table 2. KMO and Bartlett’s Test for Job Satisfaction Scale

Abbreviations: Df, degree of freedom; Sig, significance level.

Table 3. The Values Showing the Validity for Job Satisfaction Scale

Abbreviations: CR, composite reliability; AVE, average variance extracted; MSV, maximum shared variance; ASV, average shared variance.

Work Engagement

Principal component analysis extracted work engagement scale into three factors (Table 4) in accordance with the standard UWES-9 items scale (Schaufeli et al., 2006). Items 1 to 3 were extracted as absorption, items 4 to 6 were extracted as vigour and factors 7 to 9 as dedication. The measuring scale in the current context had KMO value of 0.715 (Table 5), well above the threshold value of 0.5. The internal consistency was good as depicted by Cronbach’s alpha value 0.767 which was well above 0.6. The validity of the scale was determined using CFA, and the results were tabulated (Table 6).

Table 4. Result of Rotated Component Matrix Which Gave Two Factors for Work Engagement Scale

Table 5. KMO and Bartlett’s Test for Work Engagement Scale

Table 6. The Values Showing the Validity for Work Engagement Scale

Abbreviations: ABS, absorption; VIG, vigour; DED, dedication.

Job Resources-Demands

EFA was conducted for job demands and resources scale, where few items were modified with regards to the current context. Job demands and resources play a crucial role occupational and depends upon the particular job characteristics that is associated with the job (Bakker et al., 2007). Job resources consisted of factors such as training support (Buitendach et al., 2016), raw material support, market information and equipment support. Job demands consisted of factors such as pace and amount of work, mental load and physical efforts (Lequeurre et al., 2013), which were modified as per the context of the study. In various studies, job demand and lack of resources are taken as two factor structure and verified as component of work-related well-being (Rothmann, 2008); therefore, for two constructs, EFA was conducted separately (Table 7 and Table 8). The measuring scale for job resources scale in the current context had KMO value of 0.648. Items 1 to 3 were classified as skill utilization, items 4 to 6 were classified as training support, items 7 to 9 were classified as raw material support and items 10 to 11 were classified as market information. The internal consistency was good as depicted by Cronbach’s alpha value 0.710. Similarly, the KMO value demands scale was reported to be 0.667. Items 1 to 3 were extracted as pace and amount of work, factors 4 to 6 were extracted as physical efforts and factors 7 to 9 were classified under the category of mental load. The internal consistency depicted by Cronbach’s alpha value 0.679. The validity of the scale was determined using CFA (Table 9 and Table 10).

Table 7. Result of Rotated Component Matrix Which Gave Three Factors for Job Resources Scale

Table 8. Result of Rotated Component Matrix Which Gave Three Factors for Job Demand Scale

Table 9. The Values Showing the Validity for Job Demand Scale

Source: Computed by researcher.

Table 10. The Values Showing the Validity for Job Resources Scale

The Pearson product–moment correlation (Table 11) measured the relationship between the different dimensions of well-being. Job satisfaction (intrinsic and extrinsic) and occupational stress (lack of job resources and job demands) were statistically significantly negatively related (p < .01). Terry et al. (1993) had reported that increased level of stress leads to decrease in job satisfaction. This negative correlation was further confirmed by Fairbrother and Warn (2003). The extrinsic and intrinsic job satisfaction are positively related to vigour, dedication and absorption (p < .01; Narainsamy & van der Westhuizen, 2013). The job demands and job resources are negatively correlated with work engagement which suggests that when there are lack of resources and more job demands, it leads to low work engagement (Buitendach et al., 2016).

Table 11. Relationship Between Work Engagement, Occupational Stress and Job Satisfaction

Note: ** Correlation is significant at 0.01 level (2-tailed).

Abbreviations: JS, job satisfaction; JR, job resources and JD, job demands.

A Structural Model of Work-Related Well-Being

After confirming and validating the constructs of all three scales of job satisfaction, work engagement and job resources-demands, structural equation modelling (SEM) method by AMOS was used to test the model of work-related well-being in the context of the study (Figure 1). The goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), normed fit index (NFI) and root mean square error of approximation (RMSEA) and CMIN/DF were used as indicators of fit index (Lomax & Schumacker, 2004). GFI is the share of variance for the given population covariance, which is similar to R2. AGFI is there for parsimony (Table 12). Ideally, the value should be GFI > 0.95 and AGFI 0.90. The model clearly concurs with the view that work-related well-being is a multidimensional construct (Daniels, 2000). In line with the argument of Daniels (2000), affective well-being is multidimensional. The model involved a one-factor model with all the components of well-being loading onto a single first-order factor (Soh et al., 2016). Occupational stress had negative loading on work-related well-being (–0.17). Work engagement loaded positively on work-related well-being (0.76) and job satisfaction also showed positive loading (0.89). The components of work engagement, that is, vigour (0.54), dedication (0.56) and absorption (0.56) loaded positively on work engagement. Intrinsic job satisfaction (0.69) and extrinsic job satisfaction (0.57) loaded positively on overall job satisfaction.

Figure 1. Structural Model of Relationship Work-Related Well-Being and Its Component

Table 12. Values as Obtained from Structural Equation Modelling

Note: All the values indicated a good fit of the model with p < .001.

Abbreviations: CMIN/Df, discrepancy divided by degree of freedom; CFI, comparative fit index; GFI, goodness-of-fit index; ADFI, adjusted goodness-of-fit; and RMSEA, root mean square error of approximation.


This study explored the job satisfaction, occupational stress and work engagement among handloom weavers and also attempted to analyse the relationship between the constructs. The results substantiated that all these factors together make a three-factorial model of work-related well-being. These constructs were composed of the following dimensions: job satisfaction, occupational stress and work engagement (Soh et al., 2016). Hypothesis was well supported by the results which hierarchical model combining dimensions of affective well-being loading onto work-related well-being among handloom weavers. This result is in congruence with (Warr, 1990) three-dimensional model of affective work-related well-being and (Rothmann & Coetzer, 2002) model of well-being for individuals working in stressful conditions. The occupational stress dimension loaded negatively onto work-related well-being, while job satisfaction and work engagement being the positive component. It is evident from the results that work-related well-being is a multidimensional concept (Daniels, 2000). Handloom weavers work in extremely difficult working conditions, and often the remuneration is too low. The skills that they possess is of unmatched level which is not justified by the wages that they get. They also have to face tough competition from power looms (Bhattacharya & Sen, 2018). This adds to the mental agony. This makes study of work-related well-being among weavers even more important, taking into account the situation that they face. The study undertaken is the first of its kind which attempts to study work-related well-being as a concept which has three dimensions associated with it.


The study adds to the model of work-related well-being by validating it in the context of the study. No previous studies have been conducted in handloom sector in light of affective work- related well-being. So, this study can pave a way for further studies among weavers and their work-related issues can be addressed effectively. This can also act as a measure to assess the welfare schemes that government implements for weavers since these are mostly job-centric schemes. More features in the schemes can be synthesized which can contribute to counter the negative predictors of work-related well-being. The welfare schemes enhance the well-being of the beneficiaries (Heins & Deeming, 2015). Work-related well-being which is a concept within psychological research domain can also be applicable to labour economics and might as well prove to be better indicator for performance (Green, 2010).


Work-related well-being was composed of three separate but related factors, namely engagement, job satisfaction and occupational stress. It could, therefore, be suggested that all three factors should be taken into consideration when addressing work-related well-being among the handloom weavers. The validation of this model might act as a suggestive tool as to how working environment and other work-related aspects can be addressed in order to have better well-being among the handloom weavers.


This model validation may help the policymakers and institutional bodies in better implementation of the work-centric policies. There are numerous schemes implemented by the government which have features to focus on the work-related issues such as wages, poor working conditions, market development and so on and so forth. These challenges negatively affect the well-being of the weavers leading to mobility, taking up other jobs for livelihood.

Work being a source of income, which impacts various life facets, plays an important role in studying the well-being of individuals. It also consumes significant part of time and energy and is most important determinant of life satisfaction (Rothmann, 2008). Work-related aspect also affects mental well-being of an individual so the study can contribute in analysing overall life satisfaction. Work-related well-being is associated with macroeconomics and labour market structures which determines opportunities for employment and chances of unemployment (Tausig, 1999). Therefore, this study can be of importance for labour economics, policymakers and might be a contributor in studying psychology at work settings.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.


The authors received no financial support for the research, authorship, and/or publication of this article.


Sushmita Singh  https://orcid.org/0000-0002-6595-4900


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