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The interplay of ergonomic risk factor and lifestyle factors on Potter’s well-being and work fatigue in Magelang’s tourism village

BMC Public Health volume 25, Article number: 1550 (2025) Cite this article

Abstract

Background

Informal sector workers face high risk exposure combined with low social protection coverage, placing a significant portion of these workers in a highly vulnerable situation. Pottery crafting activities, in general, involve monotonous and repetitive work. Therefore, this research was conducted to examine the influence of ergonomic and lifestyle factors on work fatigue and well-being.

Methods

This study employed a quantitative methods for the identification and assessment of ergonomic factors, lifestyle, and their effects on work fatigue and well-being. The study sample consisted of pottery craftsmen in Karanganyar Village, Magelang, selected through simple random sampling calculations. Data analysis was performed using SmartPLS-SEM (Partial Least Square-Structural Equation Modeling).

Results

Based on hypothesis testing results, it was found that there was an influence of ergonomic risk factor on work fatigue (p-values: 0.165) and an influence of ergonomic risk factor on well-being (p-values: 0.604). There was also an influence of lifestyle on work fatigue (p-values: 0.000) and an influence of lifestyle on well-being (p-values: 0.005).

Conclusion

This study concluded that ergonomic risk factor and lifestyle had an impact on well-being, while neither of them significantly affected work fatigue.

Peer Review reports

Introduction

In 2023, there were 370,747 cases of workplace accidents in Indonesia, marking an increase of 35% compared to the previous year’s 239,000 cases [1]. The trend of workplace accidents has been consistently rising over the past five years. Therefore, research on occupational health and safety becomes crucial as a preventive measure against workplace accidents [2]. Informal sector workers are exposed to high risks, compounded by low social protection coverage, rendering most of them highly vulnerable [3]. Pottery crafting activities typically start early in the morning and end in the afternoon, indicating a lack of physical activity or exercise among pottery craftsmen. These craftsmen can work at any time, which can impact their physical condition and fatigue, subsequently affecting productivity.

Workers often do not pay adequate attention to their dietary habits and overall health. Based on previous, which reported that workers in the false eyelash industry in Purbalingga experienced fatigue in 75.57% of cases due to inadequate energy consumption relative to their nutritional needs [4]. When the workload exceeds the body’s capacity, it leads to fatigue as a signal to stop the activity [5]. A study conducted on 12 weavers in Gelgel Village, Klungkung Regency, Bali, found that 58.33% of the weavers had inadequate dietary patterns [6].

Pottery crafting activities generally begin in the early morning and end in the afternoon. Most of these activities are carried out at home, indicating a lack of physical activity or exercise among pottery craftsmen. Craftsmen can work at any time, potentially affecting their sleep patterns. Data on the age distribution of the population in Karanganyar Village indicates that 46% of the working-age population is at risk of hypertension, which can impact health and hinder work activities. Hypertension is related to sleep quality and lifestyle factors, including exercise habits, smoking, and alcohol consumption. If hypertension is not managed properly, it can lead to advanced diseases such as heart disease, stroke, kidney failure, and more [7].

Home industry workers typically use their homes as workplaces, leading to non-standardized working environments and associated ergonomic risks [8]. The pottery-making process involves manual handling and is time-consuming and repetitive. During this process, workers sit on a small stool, with their left hand rotating a potter’s wheel used to shape the pottery, while their right hand molds the workpiece according to their desires. This activity is repetitive, requires long work hours, involves non-ergonomic working postures, such as prolonged sitting and bending, and demands considerable physical effort [9]. Additionally, the pottery pieces vary in weight, from hundreds of grams to tens of kilograms, leading to variations in the load carried by each worker. Repetitive tasks, static working postures, and manual lifting are ergonomic factors that can lead to musculoskeletal disorders and fatigue [10].

Based on another research, it was found that the assessment of complaints and operator activity scores in the pottery craft printing process using the NBM table was as follows: operator 1 scored a total of 60, which falls under a moderate risk level [7]. The operator experienced complaints in the upper neck, left shoulder, right shoulder, lower back, buttocks, left wrist, right wrist, left knee, right knee, left calf, right calf, left ankle, and right ankle. The study revealed that the work equipment used so far affects the operator’s working posture, necessitating a redesign of work equipment. Additionally, another research stated that pottery craftsmen in the Sandi area consistently worked in non-ergonomic positions, sitting with bent knees, hunched backs, and bowed necks for hours, leading to lower back pain [11]. Prolonged incorrect sitting positions and poor working postures can cause musculoskeletal (skeletal) pain, including back pain. Back pain is one of the problems faced by craftsmen due to their seated working positions.

Subjective well-being is the result of a balance between psychological, physical and social resources and challenges in an individual’s life [12]. Therefore, examining subjective well-being from a physical or medical perspective, in this case a healthy lifestyle is quite important to be examined in this study. Especially in the population of informal pottery workers whose work requires physical labour that is prone to occupational fatigue. Often the fatigue felt by pottery artisans is not felt or noticed due to the pursuit of daily product targets and the absence of clear working hour arrangements in the informal sector [7]. In addition, the absence of priorities or special attention for the informal sector requires them to be able to strive for their welfare, one of which is by having a healthy lifestyle [11].

Based on the aforementioned background, this research aims to analyze ergonomic risk factor, lifestyle, and their impact on work fatigue and well-being among pottery craftsmen in Karanganyar Tourism Village, Magelang. This research stands out due to its holistic approach to understanding the multifaceted influences on potter’s well-being and work fatigue, integrating ergonomic principles with lifestyle factors to offer comprehensive insights and practical recommendations for optimizing occupational health and productivity in pottery studios. Ultimately, this research endeavors to foster a healthier and more sustainable work environment for pottery artisans, enriching both their professional practice and personal well-being.

Methods

This research employs a quantitative methods for the identification and assessment of work-related risks, ergonomic factors, lifestyle, and their impact on work fatigue and well-being. From a data collection perspective, it falls under the category of observational research, which means that the study is conducted without any specific intervention or treatment on the research subjects. This research was carried out in Karanganyar Tourism Village, Magelang, Indonesia, during July to August 2023. The population for this study consists of pottery craftsmen in Karanganyar Village, Borobudur Subdistrict, Magelang Regency, totaling 120 craftsmen. The sample for this study comprises 95 pottery craftsmen in Karanganyar, Magelang, selected through simple random sampling.

This research involves two variables: the dependent variable and the independent variable. The dependent variables in this study are work fatigue and well-being, while the independent variables are ergonomic risk factor and lifestyle. Data for this study is collected through general health measurements and questionnaires to respondents. General health measurements are taken to obtain primary data such as blood pressure, body weight, and fatigue levels. The study utilized various tools to assess different aspects of worker health and well-being. To objectively measure work fatigue, a reaction timer was employed. Work-related fatigue is measured by two methods, namely objective and subjective. Objective measurements are carried out using the Reaction Timer tool. Measurements are taken before and after work on all workers. Measurements in 1 test are 20 times then all results are averaged. The results of objective work fatigue measurements are grouped as follows:

  1. a.

    Normal = 150.0–240.0 milliseconds.

  2. b.

    Mild = > 240.0 - <410.0 milliseconds.

  3. c.

    Moderate = > 410.0 - < 580.0 milliseconds.

  4. d.

    High = > 580.0 milliseconds.

In addition, subjective measurement of job fatigue using the Industrial Fatigue Research Committee (IFRC) questionnaire. This original questionnaire is valid and reliable [13]. This questionnaire will produce a score with a range of 30–120, and is categorised as follows:

  1. a.

    Low = Score 30–52.

  2. b.

    Moderate = Score 53–75.

  3. c.

    High = Score 76–98.

  4. d.

    Very High = Score 99–120.

Dietary allowances are determined by using the Nutritional Adequacy Score set by the Ministry of Health of the Republic of Indonesia. This original score set is valid and reliable [14]. The Nutrient Adequacy Score is a value that indicates the average requirement of certain nutrients that must be met daily for almost all people with certain characteristics to live a healthy life. The Nutrition Adequacy Score categories of respondents in this study were categorised as follows:

  1. a.

    Severe deficit = < 70%.

  2. b.

    Moderate deficit = 70–79%.

  3. c.

    Mild deficit = 80–89%.

  4. d.

    Good = 90–119%.

  5. e.

    Excess = ≥ 120%.

Nutritional status is measured using the Body Mass Index measurement method, which is calculated as the respondent’s weight (in kilograms) divided by the square of the respondent’s height (in metres). The results of these measurements were categorised as follows:

  1. a.

    Very thin = measurement result < 17.

  2. b.

    Underweight = measurement result 17 - <18.5.

  3. c.

    Normal = measurement result 18.5–25.0.

  4. d.

    Overweight = measurement result > 25–27.

  5. e.

    Obese = measurement result > 27.

Sleep quality was measured using the PSQI- Pittsburgh sleep quality index questionnaire by Spira et al. [15] and the PSQI interview has 7 assessment components in all components have scoring range 0–3 points. This original questionnaire is valid and reliable [15, 16]. Sleep quality measurement results:

  1. a.

    Good, if the number of scores ≤ 5.

  2. b.

    Bad, if the total number of scores > 5.

Well-being in this study is measured using the Ryff Psychological Well-Being Scale which is a measuring tool resulting from the operationalization of six dimensions of psychological well-being. The six dimensions are autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptanced. The score categories for each dimension were determined using the calculation of research data descriptions containing descriptive statistics on each of the variables analyzed, such as the number of subjects (n), mean (M), standard deviation (s), variance (s [2]), minimum score (Xmin), and maximum score (Xmax). From the descriptive information obtained earlier, we can find out the condition of the subject in the aspect or variable under study. Moreover, this original questionnaire is valid and reliable [17].

Ergonomic risk factor was assessed using the Ergonomic Risk Factors Checklist Assessment. This original questionnaire is valid and reliable [17, 18]. Ergonomic Risk Factors (ERF) score of 1–15 categorized into:

  1. a.

    Score 1 = Safe.

  2. b.

    Score 2–3 = Low Risk.

  3. c.

    Score 3–7 = Medium Risk.

  4. d.

    Score 8–10 = High Risk.

  5. e.

    Score 11–15 = Very High Risk.

Additionally, the questionnaire included questions about smoking habits, alcohol consumption, and exercise, which were answered with yes or no.

Regarding the translated questionnaire, we translated those into Bahasa Indonesia. Then, the translated questionnaire is given to experts in the field and the language to check if the translation has retained its original meaning. After that, we translated back to English for confirmation. Finally, we conducted the pilot study to check the questionnaires’ validity and reliability to the similar subjects (potters) that were not included in our study. As a result, all items in the three questionnaires above are significant as the Cronbach`s Alpha results for all questionnaire items show the results of the Cronbach alpha r count > r table (for PSQI, IFRC, and Well-Being the cronbach’s alpha value are 0.622; 0.778; 0.710 respectively). So that it can be said that all questions on the questionnaire are reliable.

Data analysis is performed using SmartPLS-SEM (Partial Least Square-Structural Equation Modeling). The statistical analysis in SmartPLS-SEM includes:

  1. 1.

    Outer model analysis: Conducted to ensure that the measurements used are suitable (valid and reliable). Some calculations in this analysis include convergent validity, discriminant validity, composite reliability, Average Variance Extracted (AVE), and Cronbach alpha. This measurement assesses the reliability and validity of the indicators used to measure latent constructs. Its purpose is to evaluate the relationships between observed variables (indicators) and their corresponding latent constructs. This evaluation involves assessing the reliability and validity of the indicators.

  2. 2.

    Inner model analysis: Performed to test the relationships between latent constructs. Some calculations in this analysis include R Square, Effect Size (F Square), and Prediction relevance (Q Square). The inner model also assesses the significance of these path coefficients to determine whether the hypothesized relationships are supported by the data.

The informed consent was obtained from all the participants and from the parents of the participants who were below 18 years of age. All methods were performed in accordance with the relevant guidelines and regulations. This research has obtained ethical clearance from the Ethics Committee of the Faculty of Public Health, Universitas Airlangga, with certificate number: 55/EA/KEPK/2023.

Results

The research that was conducted produced several data on variables’ distribution including ergonomic risk factor, lifestyle, work fatigue, and well-being. The ergonomic risk factor consist of work posture indicator (listed in Table 1). While lifestyle consists of several indicators as nutritional status, recommended dietary allowance, dietary habit, exercise habit, smoking habit, alcohol consumptions, and sleep quality. Finally, the well-being variable includes 6 indicators such as autonomy dimension, personal growth, positive relation with other, purpose in life, and self-acceptance.

In Table 1, the pottery craftsmen’s ergonomic risk factor in the Karanganyar Tourist Village, Magelang, showed that the majority of them had the work posture assessment results in the low and medium categories (28.4% each), the majority were in the age category of 46–55 years (28.4%), and most of them have work experience in the category of > 10 years (77.9%). These three variables were factors that influence the ergonomic risk of the respondents.

Table 1 Ergonomic risk factor distribution
Full size table

The variables examined as markers of lifestyle (Table 2) were nutritional status (as defined by BMI), nutritional adequacy, eating habits, exercise habits, smoking habits, alcohol consumption habits, and sleep quality. The measuring findings, which reflected the respondents’ lifestyles as pottery craftsmen in the Karanganyar Tourist Village, revealed that the majority of them had normal nutritional status, good nutritional adequacy, and good eating habits. Furthermore, the majority of responders did not exercise, did not smoke, did not use alcohol, and had decent sleep quality.

Table 2 Lifestyle distribution
Full size table

Work fatigue was objectively tested with a response timer and subjectively quantified with the IRFC questionnaire. According to the measurement results showed in Table 3, the majority of respondents (57.9%) had mild objective and moderate subjective work fatigue (46.2%).

Table 3 Work fatigue distribution
Full size table

Well-being variable was constructed from six dimensions, such as autonomy (high scores indicate the individual’s ability to act independently, unaffected by societal influences), environmental mastery (effective utilization of opportunities and a feeling of control over one’s surroundings, including managing daily affairs and creating advantageous situations), personal growth (ongoing development, openness to new experiences, and acknowledgement of personal improvement over time), positive relations with others (active participation in meaningful relationships characterized by mutual empathy, closeness, and affection), purpose in life (a strong sense of direction and belief in the meaningfulness of life), and self-acceptance (a positive self-perception). All six dimensions must be achieved well to achieve overall good well-being. The research results showed that the majority of respondents achieved well-being in the moderate category (64.2%) (listed in Table 4).

Table 4 Well-Being distribution
Full size table

Analysis of the influence of ergonomic risk factor and lifestyle on work fatigue and Well-Being among pottery craftsmen in Karanganyar tourist village, Magelang

In this study, the data analysis will be conducted step by step. First, it begins with the evaluation of the measurement model (outer model) showed in Fig. 1 and Fig. 2 while the evaluation of the structural model (inner model) performed in Fig. 3 and Fig. 4. The outer model describes the relationship between each indicator and its latent variable, while the inner model illustrates the relationships among latent variables.

Fig. 1
figure 1

First outer model analysis

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Fig. 2
figure 2

Second outer model analysis

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Fig. 3
figure 3

First inner model testing

Full size image
Fig. 4
figure 4

Final inner model

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Outer model analysis

The measuring model assessment sought to investigate the link between each indicator and its latent variable, known as the outer model. Loading factor values and Average Variance Extracted (AVE) values were evaluated in the outer model analysis. The loading factor reflected the relationship between a given question item’s score and the score of the indicator construct gauging that construct. If the loading factor value produced is greater than 0.6 and the AVE value is greater than 0.5, the construct is legitimate [19]. The outer model analysis findings are shown in the Table 5 below:

Table 5 Loading factor and average variance extracted
Full size table

According to the Table 5, numerous items have loading factor of < 0.6 (showing that they do not contribute to the formation of the sociodemographic latent variable), hence the observed variables had to be eliminated and retested to get new loading factor values. After deleting the incorrect observed variables, the study model is showed in Fig. 2.

Table 6 shows the value of AVE, composite reliability, and Cronbach Alpha on each variable with the following results:

Table 6 Result of convergent validity after deducting invalid indicators
Full size table

Inner model analysis and hypothesis testing

The Inner Model (Evaluation of the Structural Model) was a model that offered an overview of the links between latent variables and other latent variables (showed in Fig. 3 and Fig. 4). This model might be bootstrapped to determine the amount of variability of variables in explaining other latent variables with the R-Square value.

Hypothesis testing in this research will use the T-Statistic values showed in first inner model testing as it performed in Fig. 3. At a significance level of 5%, a variable can be considered to have a significant effect on another latent variable if the T-Statistic value is > 1.96 or the P-Value is < 0.05. If the T-Statistic value is < 1.96 or the P-Value is > 0.05, then the research variable does not have a significant effect on the other latent variable. Path coefficients aim to measure the extent of the relationship between latent variables. If the coefficient value approaches + 1, the relationship between variables is positive, indicating a stronger predictive value for the dependent variable. The model that has been bootstrapped in this study showed in Fig. 3.

According to Fig. 3, the P-value between ergonomic risk factor (ERF) and fatigue, as well as the P-value between ERF and well-being (WB), were both greater than 0.05, indicating that the results of the inner model testing were non-significant. Table 7 has more extensive information as follows.

Table 7 Hypothesis testing
Full size table

The non-significant hypothesis in the model was removed in the second phase of the inner model testing. Because ERF exhibited no link to both fatigue and well-being variables, it was eliminated from the model, and the final model is presented in Fig. 4 as follows.

Table 8 Fit test
Full size table

The SRMR value in Table 8 shows both estimated and saturated model in 0.070 and 0.072 respectively, this indicates that the model is already fit.

Discussion

The relationship between ergonomic risk factor on work fatigue

This study showed there is no relationship betweeen ergonomic risk factor and work fatigue. The results are consistent with recent research that showed the respondents have appropriate work postures and have been trained in good working positions [20]. Similarly, the respondents in this study have a majority of work experience of more than 10 years, so they are experienced in determining comfortable and ergonomic work postures.

Work experience has both positive and negative impacts on performance [21]. The positive impact is that as work experience increases, so does the level of experience. The negative impact is that the longer the work experience, the greater the exposure to hazards, whether from the work environment or other factor [22]. To reduce workers performing tasks in awkward postures, managers can design ergonomic workstations and incorporate stretching routines to relax stiff muscles. Stretching can help relieve muscle tension [23].

The influence of age on work fatigue occurs because the body’s functional capacity can change due to aging, affecting a person’s physical endurance and capacity for work. Younger individuals can handle heavier workloads, while older individuals may experience a decrease in their ability to perform heavy work due to quicker fatigue and reduced agility when carrying out their tasks, which can affect their performance [24]. Other research concludes that individuals under the age of 45 are considered young and capable of handling heavier workloads compared to older individuals [25]. Increasing age can be one of several factor that can lead to fatigue in performing work [26]. It is not just a matter of certain organs experiencing a decline; workers can also become more sensitive and have reduced productivity in their work [27].

The relationship between lifestyle and work fatigue

This study shows that there is an influence of lifestyle on work fatigue. The results of this study align with research which states that there is a significant relationship between energy intake and work fatigue [10]. Workers with lower energy intake experienced more fatigue, even those with a sufficient intake because the timing and quantity of energy intake were not appropriate. This result is also consistent with another research, where cross-tabulation between energy intake sufficiency and work fatigue showed that high levels of work fatigue were only experienced by workers with insufficient energy intake [28, 29]. Correlation testing using Spearman’s rank yielded a p-value of 0.001 (p < 0.05), indicating a moderately strong negative correlation (r = -0.548) between energy intake sufficiency and work fatigue.

Adequate dietary patterns are a determinant of work productivity [30]. Workers can perform their tasks better when they have the energy obtained from food [31]. Dietary patterns with energy/calorie intake meeting the requirements represent normal nutritional status, while energy/calorie intake that does not meet the requirements may lead to malnutrition, causing the body to use its nutrient reserves to meet its needs [32]. Continuous deficiencies can deplete nutrient stores, lead to tissue depletion, increase lactic acid and pyruvate levels, and lower hemoglobin levels. This can disrupt bodily functions, resulting in symptoms such as dizziness, fatigue, and shortness of breath.

Ceramic craftsmen’s work is one of the monotonous and continuous jobs, making them highly susceptible to work fatigue, so it is essential to pay attention to rest breaks. Previous research aligns with the findings of this study, indicating a relationship between sleep quality and work fatigue among informal workers, such as fishing craftsmen [33]. This study is also consistent with prior research which found a relationship between sleep quality and work fatigue [34]. For humans, quality sleep is crucial as it allows the body to recover after a day of work. Sleep quality problems can be addressed by avoiding alcohol and caffeine consumption and turning off electronic devices like phones before bedtime.

Workers’ perceived sleep disturbances can affect their sleep quality. Quality sleep plays a vital role in an individual’s physical and mental health because it allows the body to recover and rest after daily activities, reduces stress and anxiety, and enhances concentration for daily tasks [35]. Quality sleep is a critical source of vitality for improving bodily productivity in the long run. Like nutritious food and exercise, quality sleep is equally essential. Typically, adults require 7–8 h of sleep per day to maintain health and optimal performance [36].

Body recovery occurs during the sleep process. Body recovery is considered successful when an individual feels more refreshed and energetic when working [26]. Fatigue is a serious issue that needs attention [37]. Based on a comprehensive analysis, sleep quality is associated with work fatigue experienced by workers in various job sectors [38]. Other research also suggests that an individual’s level of fatigue increases as sleep quality decreases. Fatigue manifests differently in each individual [39]. However, when someone exceeds their physical or mental work capacity, they will experience fatigue, which can hinder the achievement of the desired sleep quality [40].

The relationship between ergonomic risk factor and Well-Being

In this study, ergonomic risk factor do not have an impact on well-being. Although there are not many studies examining the influence of ergonomic risk factor on well-being, some studies have assessed the impact of ergonomic risk factor on physical complaints or diseases. The physical condition unaffected by ergonomic risk factor is an indication that they do not affect well-being because good health is also part of well-being. A previous study by Nissa (2015) found a p-value of 0.593 (α > 0.05) through statistical testing, indicating that the null hypothesis (Ho) is accepted, meaning there is no relationship between repetitive movements and right-hand CTS complaints in architecture students from the 2013 class of Diponegoro University [41]. Ceramic craftsmen in Kranganyar Village, Magelang, have good self-control over what they feel; most respondents stated that they would immediately take a break if they felt pain or discomfort in their bodies.

The relationship between life style and Well-Being

This study concludes that there is an influence of lifestyle on well-being. The results of this study align with previous research indicating that a healthy lifestyle, such as healthy eating habits, significantly influences well-being [35, 42]. Previous research has found that individuals who adopt or perceive themselves to have healthy eating habits have better well-being, while those with less healthy eating habits or dissatisfaction with their eating habits tend to experience negative symptoms such as stress, anxiety, and depression [43, 44]. Healthy eating habits can enhance individuals’ positive emotions [45]. The perception that one adopts healthy eating habits is positively related to their well-being [43].

Another aspect of lifestyle is sleep quality. Sleep quality is essential for an individual’s health and well-being [46]. Previous research has found that sleep quality is the strongest predictor of subjective well-being [47, 48]. Sleep quality has also been significantly associated with stress, depression, and anxiety, indicating a decrease in well-being [49]. Subjective well-being is the result of a balance between psychological, physical, and social resources and challenges in an individual’s life [50]. Therefore, examining subjective well-being from a physical or medical perspective, in this case, a healthy lifestyle, is essential in promoting an individual’s mental health [51]. This is especially true for informal sector workers like ceramic craftsmen, whose work involves physical labor. Additionally, the lack of specific priorities or attention to the informal sector forces them to take steps to improve their well-being, one of which is adopting a healthy lifestyle.

Conclusions

This study’s findings clearly indicated that lifestyle choices had a major impact on job tiredness and well-being, particularly sleep quality and eating habits indicators. Surprisingly, the study finds that ergonomic risk factor have no significant effect on job fatigue or well-being, indicating that interventions and resources should be focused largely on lifestyle changes for improved employee outcomes. To enhance employees’ well-being and decrease their work fatigue, encouraging and supporting employees in making positive changes in their dietary habits and sleep quality can lead to substantial improvements in their overall work experience. This can include initiatives like providing healthier food options, promoting exercise, and educating employees about the importance of a balanced diet and good sleep hygiene. Furthermore, it is essential to continue monitoring and assessing the impact of lifestyle changes on job fatigue and well-being through regular surveys and feedback mechanisms. This will help organizations tailor their efforts more effectively and measure the progress of their initiatives.

The study’s focus on specific ergonomic risk factor and lifestyle factors may limit other potentially influential variables that could contribute to work fatigue and well-being among pottery craftsmen. Future research could explore a broader range of factors, such as socio-economic status, social support networks, or organizational culture within pottery studios, to provide a more comprehensive understanding of the dynamics at play. Finally, the study’s reliance on a single method of data collection, namely questionnaires, may limit the depth of insights obtained.

Data availability

The datasets generated are available from the corresponding author on reasonable request. We do not make participants’ data publicly available due to data protection restrictions and participant confidentiality as it has been stated in our informed consent and research protocol.

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Acknowledgements

The Airlangga Research Funds Batch 1 was used to support this study, and the authors are grateful to the Faculty of Public Health and Airlangga University for their assistance. The firm where this research was done and all the employees who agreed to participate as responders were also much appreciated by the writers.

Funding

Universitas Airlangga under The Airlangga Research Funds Batch 1 254/UN3/2023.

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Authors and Affiliations

  1. Department of Occupational Health and Safety, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia

    Indriati Paskarini, Endang Dwiyanti & Dayinta Annisa Syaiful

  2. Department of Epidemiology, Biostatistics, Population Studies and Health Promotion, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia

    Mahmudah Mahmudah

  3. Center for Training and Empowerment of Village Communities, Disadvantaged Areas and Transmigration, Yogyakarta, Indonesia

    Widarjanto Widarjanto

  4. School of Medicine and Dentistry, Public Health, Griffith University, Gold Coast, Australia

    Shani Agung Nugroho

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  1. Indriati Paskarini
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Contributions

I.P. prepared research proposal, funding proposal, data collection, wrote the main manuscript.E.D. prepared research proposal and research reporting.M. prepared research proposal, data analysis, and wrote the main manuscript.W. prepared research proposal and data collection.S.N prepared research proposal and data collection.D.S prepared research proposal, correspondence, administration, and wrote the main manuscript.All authors reviewed the manuscript.

Corresponding author

Correspondence to Indriati Paskarini.

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Ethics approval and consent to participate

The informed consent was obtained from all the participants and from the parents of the participants who were below 18 years of age. All methods were performed in accordance with the relevant guidelines and regulations. This research has obtained ethical clearance from the Ethics Committee of the Faculty of Public Health, Universitas Airlangga, with certificate number: 55/EA/KEPK/2023.

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The authors declare no competing interests.

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Paskarini, I., Dwiyanti, E., Mahmudah, M. et al. The interplay of ergonomic risk factor and lifestyle factors on Potter’s well-being and work fatigue in Magelang’s tourism village. BMC Public Health 25, 1550 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12889-025-22780-7

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