Development of a care model for dependents among the elderly in Khon Kaen Province, Thailand: Action research

Abstract

BACKGROUND:

Thailand has become a complete aged society, leading to an increased number of dependent elderly who require effective long-term care. However, community-based care models that integrate participatory processes remain limited. The purposes of this research were to study the factors predicting and development of a care model for dependent among the elderly.

MATERIALS AND METHODS:

This mixed-methods study was conducted in two phases. Phase 1 utilized a cross-sectional explanatory design to identify predictors of QoL among 892 elderly residents in Khon Kaen, Thailand, using multistage sampling. Instruments included the WHOQOL-OLD and BAI (α = 0.90, 0.87). Phase 2 employed Action Research (AR) based on the PAOR cycle and the Topical Health Assembly process with 70 stakeholders. Data were analyzed using stepwise multiple regression and paired t-test. Data were analyzed using Chi-square (Z²), Pearson product-moment correlation coefficient, and stepwise multiple regression.

RESULT:

The factors revealed that QoL for dependent in elderly was significantly related to age (P < 0.001), education (P = 0.001), family relationships (P < 0.001), and community participation (P = 0.002). The model explained that the overall prediction success rate was 52.6%. The predictive model was statistically significant (F = 14.28, P < 0.001), with age, education, and community participation as key predictors. After the intervention, the mean QoL score significantly increased from 2.89 to 4.56 (t = −7.43, P < 0.001). Cronbach’s alpha coefficient equal to 0.86, 0.85, and 0.90, respectively. The care model consists of six components: preliminary screening, health promotion and disease prevention, health care, health recovery, family relationships, and community participation. Satisfaction with the care model and its implementation was reported at the highest level.

CONCLUSION:

The strengthening community-based resources and social support networks to ensure sustainable care. These community factors are crucial for advancing early prevention, timely intervention, and meeting the health care needs of an increasingly aging society. The model’s success lies in the integration of health assemblies and participatory action, providing a scalable framework for rural elderly care policy.

Introduction

The global population is aging at an unprecedented rate, leading to significant challenges in health-care systems and the quality of life of the elderly. The demographic transition in Thailand is marked by a rapid increase in the elderly population, which grew from 19.6% in 2021 to 20.0% in 2025.[1,2] This shift necessitates more robust community-based long-term care systems. The demand for elderly care tends to increase with age. Specifically, the proportion of older adults in the advanced age group who require assistance with daily activities is nearly nine times higher than that of the younger elderly group. This highlights that the longer people live, the more likely they are to depend on others for care and support.[3] Elderly people experience shifts in their physical and mental well-being, which can impact their everyday tasks. If they struggle to adjust to these changes, they might become a burden to their families and the community.[4]

Thailand has become a completely ageing society.[5,6] There is a lack of preparedness in terms of policy, particularly for elderly individuals who are in a dependent. This group is steadily increasing due to age-related factors and chronic illnesses. Care for dependent elderly remains primarily the responsibility of families, as public and social support systems are still underdeveloped and lack clear structure.[7] The position of older individuals in society has transitioned from being family leaders to becoming reliant on others. This change can result in issues related to self-esteem among the elderly. According to Erikson’s theory of psychological development,[8] elderly represent the final stage of life. If individuals have successfully navigated previous stages of social development, they will find contentment in their lives and past experiences, embracing the tranquility that comes with acceptance of natural changes (Integrity). Conversely, if development has been inadequate, they may struggle to adapt, leading to feelings of regret (Despair) and dissatisfaction with their past. Depression may set in, causing them to withdraw from society and lose interest in life. This state diminishes their potential and depletes this valuable resource.[9]

The Ministry of Public Health of Thailand (MOPH) has particularly extended health services to the community as follow: health centers, the Home Health Care Health Provider, and home visits. However, at most community, the health service is unable to offer comprehensive care to all target groups, particularly the elderly who suffer from chronic illnesses and need rehabilitation to maintain a suitable condition. Many of these personnel lack expertise approaches and geriatric care. These services offer home visits, advice, and assistance to the elderly. Multi-purpose centers and social care centers (Day Care) provide services within the facility, but they typically only accept elderly individuals who can care for themselves. These centers offer exercise programs and group activities. However, the number of such service centers remains limited and does not adequately cover all areas. Although the central government, local authorities, and some communities have begun to provide long-term elderly care through families and communities, several challenges remain. As a result, many elderly individuals, particularly in rural areas, are left behind and must care for themselves far more than they should.[10]

The conceptual framework of this study integrates Erikson’s theory of psychological development with the Long-Term Care (LTC)[11] concept and the participatory action research framework (PAOR).[12] This synthesis aims to address the Quality of Life (QoL)[13] of dependent elderly through community participation, as illustrated in the conceptual model. Based on this conceptual framework, the study proceeded with a Phase 1 quantitative approach to identify the key predictors of QoL. This was followed by a Phase 2 qualitative action research, which focused on the implementation of the care model through the PAOR cycle, ultimately resulting in the final model as illustrated in Figure 1.

Figure 1.

Models of self-care for dependent elderly (Source: Original Research Data)

Current research indicates a scarcity of studies on dependent in elderly. Consequently, the main goal of this study was to study about QoL of dependent elderly individuals. The secondary objective was to investigate the factors that predict dependent. The third objective was to develop a care model for dependent elderly. And the fourth objective was to evaluated care model among dependent elderly in the Dang Yai sub-district, Muang district, Khon Kaen province, Thailand.

Material and Methods

Study design and setting

This research employed a sequential explanatory mixed-methods design. Collected data from elderly aged ≥ 60 years with Thai nationality and registered in Daeng Yai Subdistrict, Mueang District, Khon Kaen Province, Thailand. The data collection procedure was carried out for a period of nine months: December 2024–August 2025. It was divided into two phases: Phase 1 was a cross-sectional descriptive study to identify predictors of QoL, and Phase 2 was an Action Research (AR) project using the PAOR (Planning, Action, Observation, and Reflection) cycle to develop a care model.

Study participants and sampling

The study participants were divided into two groups according to the research phases:

Phase 1: The target population was 892 elderly residents. Using multistage sampling, 57 elderly individuals who met the criteria for “dependency” (based on the BAI) were recruited as the primary sample.

Phase 2: A purposive sampling method was used to select 70 stakeholders, including community leaders, local government administrators, health professionals from the Subdistrict Health Promoting Hospital, village health volunteers (VHV), and caregivers, to participate in the care model development.

Data collection tool and technique

Phase 1 quantitative phase

The literature search was conducted using five databases, such as PubMed, Google scholar, SciELO, Web of Science, and Thaijo, using the keywords “elderly” “dependent” “older adult” and “quality of life.” Using the definition “dependent” of World Health Organization (WHO) along with Long Term Care (LTC) as the concept of research tool. The content validity of the research instruments was evaluated by three experts in the fields of gerontology and public health, yielding an Index of Item-Objective Congruence (IOC) ranging from 0.67 to 1.00. Regarding reliability, the tools were pre-tested (Try-out) with 30 elderly individuals sharing similar characteristics to the sample. The Cronbach’s alpha coefficients for the QoL assessment form and the dependent assessment form were 0.90 and 0.87, respectively, indicating high internal consistency.

The self-administered questionnaires were composed of three parts as follows:

Part 1: Sociodemographic factors including gender, age, marital status, income, and education related to the current disease.

Part 2: The quality-of-life assessment questionnaire (WHOQOL-OLD) from the WHO for elderly people.[14,15] It consists of 24 items categorized into six domains as follow: (1) sensory abilities, (2) autonomy, (3) past, present and future, (4) social participation, (5) death and dying, and (6) intimacy. Each item has five response options on a five-point likert scale. A score of 24–56 points indicates a low level, 57–89 points indicates a moderate level, and 90–120 points indicate a high level, with Cronbach’s alpha of 0.90.

Part 3: The dependent assessment questionnaire by MOPH of Thailand, which is BAI. The dependent score ranges from 0 to 20 points; that is, a score of 0–4 points indicate total dependence or bedridden, 5–11 points indicates a moderate severe dependence or homebound, and 12–20 points indicates an independent, with Cronbach’s alpha of 0.87.

Respondents were included in this study only when they have a score of 0–11 points to the aforementioned question, the respondents had to answer the form about QoL and demographic questionnaires.

We explored the predictive factors associated with the QoL of dependent elderly individuals. The participants of this study were elderly (aged 60 years or older) people residing in all 11 villages. This quantitative research was conducted from December 2024–February 2025. The sample consisted of 892 elderly,[16] who were invited to participate in the study and selected the sample group from the whole population.

Inclusion criteria

More than or equal 60-year-old with Thai nationality who had lived in Daeng Yai Subdistrict more than six months, with Barthel ADL Index (BAI) scores ranging from 0 to 11, were able to speak Thai, and voluntarily participated in this study.

Exclusion criteria

The person who had recognition difficulties and other disabilities, such as dementia, psychosis, intellectual disability, blindness, or deafness, be able to attend less than 80% of research activities.

Phase 2 qualitative phase

In the first step, data were collected using a focus group session by in-depth interview. Creating and developing a care model in the community that follows the steps of the cyclical AR model of Kemmis and McTaggart,[12] it consists of four steps according to the PAOR cycle.

Before developing, existing literature on elderly with dependent was reviewed. The literature search was conducted using five databases, such as PubMed, Google scholar, SciELO, Web of Science, and Thaijo, using the keywords “elderly” “dependent” “care model” “older adult” and “quality of life.” Using the definition “dependent” of WHO[13] along with Long Term Care (LTC)[11] as the concept of research tool. The interview and questionnaire forms were divided into 4 parts as follows:

Part 1: Questions for group discussion

Part 2: Evaluation of care model

Part 3: Evaluation of care model satisfaction

Part 4: Evaluation of those involved in the process of developing a care model satisfaction

The first domain comprised open-ended questions for group discussion to identify problems and needs in caring for elderly with dependent. The second domain was conducting evaluation of care model, a total of 7 questions, which focused on caregiving behavior regarding elderly with dependent adapted LTC.[11] The third domain was 9 questions for the evaluation of the care model satisfaction. The fourth domain consisted of 11 questions for the evaluation of those involved in the process of developing a care model satisfaction.

For content consistency, this study used five experts’ interviews to recheck the consistency of contents. Using questionnaires with 30 elderly with dependent who had the same conditions as the samplings in Khon Kean Province. The Cronbach’s alpha coefficient on evaluation was 0.86, on satisfaction was 0.85 and those involved in the process of developing care model satisfaction was 0.90.

We utilized action research to create and develop a care model for dependent elderly individuals to increase their QoL through community participation by applying the concept of Kemmis and McTaggart (1988). The concept consists of four stages: planning (P), action (A), observation (O), and reflection (R).[12] This qualitative research was conducted from February–July 2025 with the participation of 70 people. This group consisted of 20 elderly with dependent, the focus group was set up prior to commencing the project. Four elderly with dependent, three registered nurses working at Dang Yai Sub-district Health Promoting Hospital, four elderly caregivers with dependent, two public health officials, four Dang Yai village health volunteers, one Dang Yai village headman, and two representatives of Dang Yai Subdistrict Municipality.

Statistical analysis method

Data were processed using statistical software. The analysis was categorized as follows:

Descriptive statistics: Frequency, percentage, mean, and standard deviation (SD) were used to describe sociodemographic characteristics.

Inferential statistics (Phase 1): Chi-square and Pearson’s correlation were used to test relationships. A stepwise multiple linear regression model was used to exclude multicollinearity, with “QoL for elderly individuals” as the dependent variable. Next, binary logistic regression analysis was performed to test the relationships among gender, age, marital status, income, education, congenital disease, self-esteem, health condition, health status perception, family relationship, community participation, and QoL for elderly individuals. The level of statistical significance was set at a P value < 0.05.

Phase 2 Evaluation: The effectiveness of the developed model was assessed by comparing pre-test and post-test QoL scores using a paired t-test, with a significance level set at P < 0.05.

Use of Artificial Intelligence in the research process in this study, Artificial Intelligence (AI) tools were utilized to assist in the manuscript preparation process. Specifically, ChatGPT and Gemini were used for improving grammatical structure, and refining the English language flow. No AI tools were used for data collection or the primary analysis of the research results. The authors have reviewed and edited the content generated by the AI to ensure its accuracy and take full responsibility for the integrity of the final manuscript.

Ethical considerations

This study was conducted in accordance with the Declaration of Helsinki. The protocol was approved by the National Ethics Committee Accreditation System of Thailand (NECAST) of Northeastern University Ethics Committee on November 3, 2024–November 3, 2025, Project No. 078/2024 and Approval No. 071/2024. All participants provided written informed consent before participating. They were informed of their right to withdraw from the study at any time without any impact on the care they receive.

Results

The population-related data of the samplings in the community in Table 1 shows the data of 57 elderly who had dependent which found majority were female (63.1%) the average age at 76.73 years (standard deviation (SD) = 10.03, Min. = 61, Max. = 101): 36.8% of elderly aged between 80 and 89 years and 8.8% of elderly aged more than or equal 90 years. These elderly mostly had the highest education at 96.5% of primary school and more than half of the elderly (56.1%) single or separated. Approximately one-third (36.8%) had a monthly income of 600–1000 Thai Baht. Most of elderly (71.9%) with chronic disease and 73.6% had a moderate level of QoL.

Table 1.

Demographic profile of the respondents (n=57). (Source: Original Research Data)

Demographic profile of the respondents
Gender
Male		21 (36.9%)
Female		36 (63.1%)
Age (Mean=76.73, S.D. = 10.03, Min. = 61, Max. = 101)
60–69 Years		16 (28.1%)
70–79 Years		15 (26.3%)
80–89 Years		21 (36.8%)
≥90 Years		5 (8.8%)
Education level
Primary school		55 (96.5%)
High school		2 (3.5%)
Marital status
Single/Separated		32 (56.1%)
Married		25 (43.9%)
Income per month (Baht)
600–1000		21 (36.8%)
1001–2000		20 (35.1%)
≥2001		16 (28.1%)
Health condition
Without chronic disease		16 (28.1%)
With chronic disease		41 (71.9%)
Quality of life
Low level (24–56)		10 (17.6%)
Moderate level (57–89)		42 (73.6%)
High level (90–120)		5 (8.8%)

Factors related to dependent in elderly

Table 2 shows the factors related to dependent in elderly by Pearson correlation analysis indicated total for 6 factors as follow: age, marital status, education, family relationships, community participation, and health status perception were significantly associated with QoL in elderly individuals (P < 0.05). Pearson correlation analysis indicated that factors including age, marital status, education, family relationships, community participation, and health status perception were significantly associated with QoL (all with exact P values ranging from < 0.001 to 0.002 as shown in Table 2).

Table 2.

Factors related to dependent in elderly (n=57) (Source: Original Research Data)

Factors		Y		1		2		3		4		5		6
Quality of life (Y)		1
Age		0.029**		1
Marital status		0.032**		0.026**		1
Education		0.036**		0.042**		0.037**		1
Family relationships		0.042**		0.038**		0.033**		0.040**		1
Community participation		0.053**		0.047**		0.031**		0.051**		0.027**		1
Health status perception		0.035**		0.044**		0.043**		0.055**		0.036**		0.043**		1

*P-value < 0.05

The results of the stepwise multiple linear regression analysis revealed that QoL for dependent in elderly was significantly related to age (P < 0.001), education (P = 0.001), family relationships (P < 0.001), and community participation (P = 0.002). The model explained that the overall prediction success rate was 52.6%. The stepwise multiple linear regression revealed that age (t = 9.646, P < 0.001), education (t = 8.872, P = 0.001), family relationships (t = 6.503, P < 0.001), and community participation (t = 3.869, P = 0.002) were significant predictors of QoL as shown in Table 3.

Table 3.

Relationships between predictors and QoL among Elderly, Bivariate analysis by linear regression (n=57) (Source: Original Research Data)

Predictors		b		SE		β		t		P-value
Age		0.123		0.051		0.562		9.646		<0.001*
Education		0.433		0.089		0.345		8.872		0.001*
Family relationships		0.236		0.067		0.348		6.503		<0.001*
Community participation		0.139		0.049		0.178		3.869		0.002*

Constant=1.675, R=0.556, R² Adj=0.526, *P-value<0.05

In phase 2 of our study, the elderly care model was implemented by organizing the community health assembly process. We utilized a topical health assembly in long-term elderly health care that implemented the health assembly process together with the PAOR. The steps of the PAOR process were as follows: (1) Planning: studying the context of the community, meeting stakeholders, creating an action plan, established the health assembly process mechanism, grouping the health assembly network, and designing the health assembly process. (2) Action: operating on the basis of a model of an elderly self-care plan. (3) Observation: monitoring and evaluation, observation, and good participation by the network in the health assembly, and the elderly participants were satisfied and had a better QoL. (4) Reflection: This approach created a lesson summary for continuous development, exchange of knowledge and lessons learned through storytelling. We communicated with society throughout the process, prepared the documents to periodically publicize our work to people in the community, and publicized via the broadcast tower in the community every month. We participated in monthly subdistrict board committee meetings, and implemented systematic management together with the secretariat. The researchers thoroughly collected the operation data during each step and consistently met with other team members. After the implementation, the mean QoL score increased from 2.89 to 4.56, showing a statistically significant difference (t = −7.43, P < 0.001) as show in Table 4).

Table 4.

Comparison of QoL score before and after the implementation of the six component care model (n=57) (Source: Original Research Data)

Quality Of Life		n		mean		SD		mean Def.		95%CI		df		t		P-value
Before intervention		57		2.89		0.87
After intervention		57		4.56		1.89		0.55		0.36–0.69		12		−7.43		<0.05

The study found that age has a significant relationship with the QoL in elderly individuals with dependency. Several factors influence elderly ability to perform daily activities and maintain physical function,[17,18,19] including demographic background, financial situation, strained family relationships, limited social connections, chronic health conditions, and pain.[20] Perceived social support is another important health-related factor. Research has shown a clear link between low perceived social support[19,21] and increased physical inactivity, chronic illness, and dependence[19,22,23] in both basic (ADLs) and instrumental (IADLs) daily activities, affecting the QoL.

Corresponding to the results supported the hypothesis that social and demographic factors significantly predict the QoL of dependent elderly. Specifically, family relationships emerged as a critical predictor (P < 0.001), which aligns with Erikson’s theory that social integration and emotional support are vital for maintaining psychological integrity in late adulthood. This finding confirms that for the Thai rural context, the informal care system (family) remains a more influential determinant of well-being than formal healthcare alone.

The finding that family relationships significantly predict QoL is consistent with studies in Malaysia[22] and in Thailand,[24,25] which emphasized that for elderly people with dependency, emotional support from family members acts as a primary buffer against psychological distress. Moreover, the role of community participation reinforces the concept of “Social Capital” as suggested stating that community-based networks are vital for the sustainability of LTC in rural areas.[26]

Moreover, the overall quality of life among dependent elderly individuals was at a moderate level, which is related to moderate level of dependent elderly people in Patunnakure Subdistrict Municipality, Tambon Patun, Maetha, Lampang, Thailand.[24] The findings indicated that advanced age and highest education also serves as a predictor of quality of life among elderly.[25,26] Most elderly feel anxious, fearing that their children or grandchildren might abandon them. Chronic health issues often emerge, affecting their physical, mental, and social well-being. Many elderly withdraw from social interaction altogether, which leads to a further drop in their quality of life. Therefore, it’s important to create supportive environments to accommodate the daily needs of elderly individuals who are dependent on others.[27] Additionally, ensuring that healthcare services and medical equipment are readily available and sufficient to meet the needs of the elderly population is crucial. These efforts support both the prevention and management of illnesses, helping elderly maintain good physical health and continue performing daily activities independently. This also encourages their active participation in social activities and helps them stay engaged in their communities.[28]

Regarding the development of the six component care model through the PAOR cycle demonstrated a significant improvement in overall QoL. This success confirms the study’s hypothesis that community participation is not merely a supportive factor but a functional engine for sustainable care. By involving multidisciplinary stakeholders, the model addressed the “care gap” identified in the quantitative phase. This result reinforces the effectiveness of the Action Research approach in creating localized solutions that are more responsive to the needs of dependent elderly than top-down policy implementations.

The successful development of the six-component care model reflects the effectiveness of participatory action research, similar to developed integrated care models for NCD patients.[27] However, our model differs by specifically integrating the “Topical Health Assembly” process, which provides a more robust policy link compared to standard community care models found in the literature.[25]

In a broader context, the improvement of QoL through community-based intervention observed in this study aligns with the WHO Global Strategy on Ageing and Health. This suggests that localized models in Khon Kaen share common success factors with international benchmarks, such as the “Age-Friendly Cities” framework, emphasizing that social inclusion is a universal predictor of well-being for the frail elderly.

Strengths and limitations

The primary strength of this study is the mixed-methods approach, which combined a robust quantitative analysis of QoL predictors with an action research (PAOR) framework. By utilizing the “Topical Health Assembly” process, this research did not only identify problems but also created a community-led solution that is highly practical and culturally sensitive. Furthermore, the inclusion of multidisciplinary stakeholders ensures that the care model is integrated and sustainable at the local government level.

Despite its contributions, this study has some limitations. First, the sample size in Phase 1 for the dependent group (n = 57) was relatively small, which might limit the generalizability of the stepwise regression results to a larger national context. Second, the study was conducted within a specific rural sub-district (Daeng Yai); therefore, the findings and the developed care model may reflect unique local social capitals that differ from urban or other regional settings. Lastly, the evaluation of the care model’s impact on QoL was conducted shortly after implementation; a long-term follow-up is needed to assess the durability and longitudinal outcomes of the six component model.

Study novelty

This research introduces a novel integration of the “Topical Health Assembly” process within a participatory action research (PAOR) framework. This approach uniquely bridges the gap between community-identified needs and localized policy implementation, offering a grassroots-driven sustainability model specifically tailored for rural Thai subdistricts.

Therefore, future research should consider expanding the model to diverse geographic areas and employing a longitudinal design to track long-term health outcomes.

Conclusion

As a result the care model was clearly structured. The care model consists of six key components: preliminary screening, health promotion and disease prevention, health care, health recovery, family relationships, and community participation. Furthermore, all dimensions of care, including health promotion, protection, treatment, and rehabilitation.

Evaluation of the model showed that the QoL of elderly participants improved significantly when comparing pre- and post-intervention phases. Satisfaction with the care model and its implementation was reported at the highest level. These findings highlight important challenges for rehabilitation strategies in dependent elderly individuals, particularly those requiring LTC. The study emphasizes the need to provide insights for policymakers to design programs that promote early prevention of health complications among elderly.

Additionally, within the community context, dependent elderly individuals often rely heavily on families, caregivers, and local health systems. This underscores the importance of strengthening community-based resources and social support networks to ensure sustainable care.

In conclusion, the developed six component care model successfully enhances the QoL for dependent elderly individuals by fostering community and family synergy. Crucially, this model aligns with the Thailand National Strategic Plan for the Elderly (2023–2037), particularly the benchmark of strengthening community-based LTC systems. By integrating the ‘Topical Health Assembly’ and PAOR cycles, the model provides a practical framework that fulfills the WHO Healthy Ageing benchmarks, emphasizing functional ability and social participation. This research demonstrates that shifting from a purely medical-centric approach to a social-health integrated policy is vital for the sustainable management of aging societies in rural contexts. Therefore, this model is recommended as a benchmark for local government organizations to implement standardized, integrated care for dependents at the sub-district level.

The novelty of this care model lies in its holistic six component structure that empowers the community to transition from passive recipients of care to active health managers. This study provides a validated blueprint for other aging societies in developing nations to enhance the quality of life for dependent elderly through social capital and community-based resources.

Declaration of patient consent

The authors certify that all appropriate patient consent forms were obtained before enrolment in the study. The participants were appraised that their names and initials would not be published and that due efforts would be made to conceal their identity.

Declaration of generative AI and AI-assisted technologies

During the preparation of this manuscript, the authors used ChatGPT and Gemini in order to improving grammatical structure, and refining the English language flow. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication. The authors acknowledge that they are liable for any breach of publication ethics related to the AI-generated portions of this work.

Abbreviations

QoL: Quality of Life; ADL: Activity of Daily Living; BAI: Barthel ADL Index; IADL: Instrumental Activity Daily Living; WHO: World Health Organization; LTC: Long Term Care; AR: Action Research; WHOQOL-OLD: World Health Organization Quality of Life-OLD person; PAOR: Plan-Action-Observation-Reflection; SD: Standard Deviation; SPSS: Statistical Package for the Social Sciences; NECAST: National Ethics Committee Accreditation System of Thailand; RCT: Randomized Controlled Trial.

Ethical approval

This study was conducted in accordance with the Declaration of Helsinki. The protocol was approved by the National Ethics Committee Accreditation System of Thailand (NECAST) of Northeastern University Ethics Committee on November 3, 2024 (Project No. 078/2024 and Approval No. 071/2024). All participants provided written informed consent prior to their participation.

Author’s contributions

Concept, design, definition of intellectual content, literature search, data acquisition of the study, literature review, tool development, data cleaning, statistical analysis, and manuscript preparation was done by PC, WW, JL and TL. The final manuscript review and editing was done by WA and PC.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

There are financial support and sponsorship from Northeastern University.