Hierarchical Factor Analysis Research Articles

Chemotherapy-induced oral mucositis: hierarchical analysis of recurrence factors.

This study aimed to analyze, through a hierarchical model, the risk factors associated with the recurrence of chemo-induced oral mucositis (OM) in children and adolescents. A retrospective cohort with 31 individuals of both sexes, aged 1-18years, who were undergoing chemotherapy, and presented OM lesions was conducted. Data collection included analysis of medical records, interviews, and intraoral examination. Information regarding patients' socioeconomic and demographic profile, underlying disease, antineoplastic regimen, hematological condition, and oral health status were collected. To assess the association of independent variables with the outcome, the Chi-square, Fisher's Exact, and Mann-Whitney tests were used, in addition to a binary logistic regression model, with a maximum error of 5% and a 95% confidence interval. Significant associations were observed between the history of OM and the diagnosis of the child/adolescent, neutrophil count, previous cancer treatments and the chemotherapy scheme in use (p < 0.05). Binary logistic regression revealed a 13.69 higher risk of developing OM recurrence in individuals who received high-dose methotrexate (MTX) therapy. Socioeconomic and demographic factors did not influence OM recurrence. However, clinical variables, such as neutropenia, diagnosis of leukemia, and high-dose MTX protocols increase the chance of OM new cases.

Optimization and Benefit Assessment of Production Supply Chain Networks Using Graph Neural Network Models

With the flourishing development of global economy, effective management of production supply chains is crucial for the competitiveness of enterprises. Optimizing supply chain networks can not only improve the efficiency of resource allocation but also enhance market responsiveness and systemic risk resistance. Traditional supply chain network optimization methods, focusing mostly on linear models and static analysis, fall short in addressing the growing complexity and dynamism. The emergence of Graph Neural Network (GNN) models in recent years has offered new opportunities to tackle non-linearity and structural dynamism in supply chain networks. However, existing research still faces methodological limitations in supply chain node relationship mining and benefit assessment. This study introduces an optimization and benefit assessment method for production supply chain networks based on GNNs. Firstly, by developing a node role type-aware graph neural network model, this paper achieves in-depth mining and optimization of node relationships within production supply chain networks. Secondly, a hierarchical factor analysis method is used to comprehensively assess the benefits of the production supply chain. This method can dynamically capture changes in node roles and relationships within the supply chain network, optimize the network structure, and provides a multidimensional, multilevel framework for benefit assessment. This study not only expands the application of GNN in the field of supply chain management but also provides a new analytical tool for the comprehensive assessment of supply chain benefits.

P-Factor(s) for Youth Psychopathology Across Informants and Models in 24 Societies

ABSTRACT Objective Although the significance of the general factor of psychopathology (p) is being increasingly recognized, it remains unclear how to best operationalize and measure p. To test variations in the operationalizations of p and make practical recommendations for its assessment, we compared p-factor scores derived from four models. Methods We compared p scores derived from principal axis (Model 1), hierarchical factor (Model 2), and bifactor (Model 3) analyses, plus a Total Problem score (sum of unit-weighted ratings of all problem items; Model 4) for parent- and self-rated youth psychopathology from 24 societies. Separately for each sample, we fitted the models to parent-ratings on the Child Behavior Checklist for Ages 6–18 (CBCL/6–18) and self-ratings on the Youth Self-Report (YSR) for 25,643 11–18-year-olds. Separately for each sample, we computed correlations between p-scores obtained for each pair of models, cross-informant correlations between p-scores for each model, and Q-correlations between mean item x p-score correlations for each pair of models. Results Results were similar for all models, as indicated by correlations of .973–.994 between p-scores for Models 1–4, plus similar cross-informant correlations between CBCL/6–18 and YSR Model 1–4 p-scores. Item x p correlations had similar rank orders between Models 1–4, as indicated by Q correlations of .957–.993. Conclusions The similar results obtained for Models 1–4 argue for using the simplest model – the unit-weighted Total Problem score – to measure p for clinical and research assessment of youth psychopathology. Practical methods for measuring p may advance the field toward transdiagnostic patterns of problems.

Hierarchical clustering analysis of musculoskeletal stress factors and their risk level in cardboard manufacturing: research from PLIBEL.

A hierarchical cluster analysis for the cardboard manufacturing industry was developed with the aim of identifying similarities between workstations in terms of musculoskeletal stress factors (MSFs) and their impact on workers' bodies. The hierarchical clustering analysis was conducted using data from 44 workstations, which included 6 body part divisions and 51 stress factors as variables with 36 answer options. Firstly, the content of the dataset was defined. Secondly, the data were agglomerated and classified into 3 clusters using Ward's method based on the presence or absence of stress factors. Finally, the multivariable matrix was reduced to 2 factors: the x-axis representing the risk level of the workstation, and the y-axis representing the impact on the workers' health. The study found that workers' knees were the most affected body parts, with 47 cases. The resulting work-related musculoskeletal disorders included tendinitis, arthralgia, chondromalacia, and gonarthrosis. The MSF with the most significant impact on the body's health was fatiguing work that involves repeated jumps, prolonged squatting, or kneeling, present in cluster 1 and cluster 3. Moreover, two of the most common MSFs associated with repeated work positions were identified: a mild forward flexion of the back (63 cases) in combination with one leg being used more often to support the body (56 cases). It was possible to identify the main work-related musculoskeletal disorders and the associated stress factors for the cardboard manufacturing industry by using hierarchical cluster classification and analysis, enabling the classification of risk levels and the impact on body health for each workstation.

A hierarchical analysis of associated factors to lifetime suicide attempts in alcohol use disorder.

Substance use is strongly associated with suicide attempts throughout life. We aimed to investigate the prevalence of suicide attempts (SA) and associated factors in life in patients with Alcohol Use Disorder (AUD). The sample consisted of 424 men with AUD who underwent treatment at the Addiction Psychiatry Unit of the Hospital de Clínicas de Porto Alegre. The clinical evaluation included the Addiction Severity Index, the Childhood Trauma Questionnaire, the Barratt Impulsiveness Scale, and the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders. Variables that showed p-value < 0.05 in the bivariate analyses were included in a hierarchical regression model with robust variance to investigate associations with SA in life via estimation of adjusted Prevalence Ratios (PR). The lifetime prevalence of SA among alcohol users was 36.6%. Patients with childhood maltreatment, borderline personality disorder, and higher impulsivity scores had a higher lifetime prevalence of SA. Our findings indicate that male inpatient alcoholics present an important prevalence of SA. The study also corroborates the relationship between maltreatment, impulsivity, and borderline personality disorder with SA among inpatients in treatment for AUD.

The impact of digital trade rule networks on the advancement of global value chains in the Internet era

Abstract In the context of the digital era, global value chains are facing unprecedented reconstruction and upgrading. The development of global trade is influenced by the importance of digital trade in upgrading the status of global value chains. Based on the research of digital trade and global value chain theory, we construct a mechanism model of digital trade to enhance the status of the global value chain and measure digital trade and global value chain by combining the multi-indicator panel hierarchical factor analysis method and the trade value-added accounting method, respectively. Benchmark regression analysis of digital trade and global value chain status indices of major economies is used to explore the impact of digital trade on the status of global value chains. There is a positive correlation between the level of digital trade and the GVC status index, with the GVC status index increasing by 1.6 percentage points for every 1 percentage point increase in the level of digital trade. The level of digital trade has a positive impact on the GVC position of both developed and developing economies. For every 1% increase in the level of digital trade, the GVC position index of developed and developing economies increases by 2.5% and 1.7%, respectively.

Hierarchical and networked analysis of resilience factors in mountain communities in Southwest China

Hierarchical and networked analysis of resilience factors in mountain communities in Southwest China

Attitudes towards Digital Educational Technologies Scale for University Students: Development and Validation

Numerous studies of the digitalization of higher education show that university students’ attitudes toward digital educational technologies (DETs) are one of the important psychological factors that can hinder or facilitate the optimal implementation of digital technologies in education. International researchers have developed many tools for diagnosing the attitudes of university students toward various aspects of the digitalization of education; however, until recently, similar scales in Russian have not been developed, which determined the purpose of this present research. The proposed version of the Attitudes towards DETs Scale for University Students (ATDETS-US) includes the cognitive, emotional, and behavioral subscales corresponding components of the attitude according to the ACB Model. The validation sample included 317 (160 females and 157 males) bachelor and master students from different Russian universities. Psychometric testing using Cronbach’s Alpha and McDonald’s Omega coefficients, hierarchical factor analysis, and CFA confirm the high internal consistency, reliability of the ATDETS-US and its subscales, and the good fit of the model. ATDETS-US will be used for obtaining reliable data on the attitudes towards DETs in university students, which should be taken into account when designing programs for their psychological support in the educational process and developing their digital competence.

The needle in the haystack: Is the dimensionality of the PGSI a prized object, or something to discard? A response to Tabri & Wohl’s commentary ‘There is (still) a global factor that underlies the PGSI.’

Tabri and Wohl question the utility of a two-factor PGSI model, as proposed in our study (Tseng et al., 2023). Although we acknowledge the validity of the full scale PGSI as an index of problem gambling, we suggest our findings indicate there is merit in using the PGSI as a two-factor model. We also outline our responses to the alternative hierarchical factor analysis of the PGSI. Despite the differing views, we remain confident that the two-factor PGSI model may serve as an appropriate tool to examine the differences between behavioral dependence and negative consequences of gambling, particularly when researchers do not have the option to explore these dimensions of problem gambling with customized measures. We also wish to clarify that we are not advocating for the abandonment of the PGSI as a total index of problem gambling. Instead, we suggest that our findings and that of Tabri and Wohl’s are not mutually exclusive.

A Reexamination of Drinking Motives in Young Adults: The Development and Initial Validation of the Young Adult Alcohol Motives Scale.

This study reexamined the factor structure of drinking motives using 205 unique items from 18 drinking motives scales with the inclusion of social tension reduction motives, which have been largely neglected in the literature. A new scale was created and compared with the Drinking Motives Questionnaire-Revised (DMQ-R) to predict alcohol use/problems. Young adults (N = 1,049) completed questionnaires assessing drinking motives and alcohol use/problems. A subset (N = 368) of participants completed a 6-month follow-up. Hierarchical factor analyses informed the creation of a four-factor (i.e., coping, social, enhancement, and social tension reduction) scale (i.e., the Young Adult Alcohol Motives Scale [YAAMS]). In general, the YAAMS performed similarly to the DMQ-R in predicting concurrent and prospective alcohol consumption (i.e., typical drinking quantity and frequency) and alcohol problems (i.e., Alcohol Use Disorder Identification Test [AUDIT] and Brief Young Adult Alcohol Consequences Questionnaire [B-YAACQ] scores), but there were some notable differences, including that the novel social tension reduction scale of the YAAMS was particularly relevant in predicting drinking frequency in those with social anxiety. Results suggest that drinking motives can be described by multiple factor structures and predict alcohol-related outcomes.

Hierarchical Analysis of Factors Determining the Impact of Forest Certification in Mexico

Forest certification is a private, voluntary and market-driven instrument designed to promote responsible forest management. This paper focused on the FSC and the NOM NMX-AA-143-SCFI-2008 schemes used in Mexico for the certification of sustainable forest management. In this paper we used the analytical hierarchical process (AHP) to study the factors that determine the main impacts of forest certification in México. A panel of 30 experts was selected as decision-makers to find which principles, criteria and indicators are considered as the most relevant while implementing forest certification. For decision-makers, the environmental principle occupied the first place with 40.26% of importance in the implementation of forest certification, followed by the social principle, and the economic principle with 32.15% and 27.59% of importance, respectively. Regarding the criteria, forest management and production, biodiversity, and forest protection were considered to be the most relevant. Regarding the indicators, the results indicated that forest certification in Mexico can have a positive impact on the existence of educational institutions, community services such as water, energy, medical services and drainage, the quality of the forest management plans, investment in forest management, machinery and equipment, environmental services, recreation, tourism, research, development and community education, planning for the conservation of biological diversity, and planning for biodiversity conservation.

The Goldsmiths Dance Sophistication Index (Gold-DSI): A psychometric tool to assess individual differences in dance experience.

Dance has become an important topic for research in empirical aesthetics, social and motor cognition, and as an intervention for neurodegenerative and neurodevelopmental disorders. Despite the growing scientific interest in dance, no standardised psychometric instrument exists to assess people’s dance experience. Here, we introduce the Goldsmiths Dance Sophistication Index (Gold-DSI), a 26-item questionnaire to measure individual differences in participatory and observational dance experience on a continuous scale. The Gold-DSI was developed in three stages: In the first stage a set of 76 items was generated by adapting questions from the Goldsmiths Musical Sophistication Index (Mullensiefen et al., 2014), and as part of a stakeholder workshop using a grounded theory approach. The second stage focused on item reduction. Using a large-scale online survey (N=424) , hierarchical factor analysis was used to fit a model comprising of one general and six secondary factors (28 items in total). In stage three, six new items were added to specifically capture individual differences in dance observation. We then collected data from two samples for final model estimation (N=127) and evaluation (N=190). The final version of the Gold-DSI comprises 26 items; 20 items relate to one general factor that captures experience in dance participation. This includes four secondary factors: Body Awareness, Social Dancing, Urge to Dance, and Dance Training. A further six items separately measure experience in dance observation. In sum, the Gold-DSI provides a brief, standardised and continuous assessment of doing, watching and knowing about dance.

The Factor Structure and External Validity of the COPE 60 Inventory in Slovak Translation.

The COPE Inventory (Carver et al., 1989) is the most frequently used measure of coping; yet previous studies examining its factor structure yielded mixed results. The purpose of the current study, therefore, was to validate the factor structure of the COPE Inventory in a representative sample of over 2,000 adults in Slovakia. Our second goal was to evaluate the external validity of the COPE inventory, which has not been done before. Firstly, we performed the exploratory factor analysis (EFA) with half of the sample. Subsequently, we performed the confirmatory factor analysis with the second half of the sample. Both factor analyses with 15 factor solutions showed excellent fit with the data. Additionally, we performed a hierarchical factor analysis with fifteen first-order factors (acceptance, active coping, behavioral disengagement, denial, seeking emotional support, humor, seeking instrumental support, mental disengagement, planning, positive reinterpretation, religion, restraint, substance use, suppression of competing activities, and venting) and three second-order factors (active coping, social emotional coping, and avoidance coping) which showed good fit with the data. Moreover, the COPE Inventory’s external validity was evaluated using consensual qualitative research (CQR) analysis on data collected by in-depth interviews. Categories of coping created using CQR corresponded with all COPE first-order factors. Moreover, we identified two additional first-order factors that were not present in the COPE Inventory: self-care and care for others. Our study shows that the Slovak translation of the COPE Inventory is a reliable, externally valid, and well-structured instrument for measuring coping in the Slovak population.

Measuring What Counts in Life: The Development and Initial Validation of the Fulfilled Life Scale (FLS).

In a recent work, we introduced a theoretical model for fulfillment in life that covers cognitive and affective components and distinguishes different time frames. The present study evaluates this model and describes the construction of the Fulfilled Life Scale (FLS) to assess fulfillment regarding the whole lived life retrospectively. We investigated the scale in two samples (Sample 1: N = 282 adults aged 50–93 years; Sample 2: N = 406 adults aged 40–85 years). The model of the cognitive component combines three sources of fulfillment (self, life, impact/legacy) with three criteria (wholeness, fit, value), yielding nine facets. Employing hierarchical factor analysis, we inspected all solutions between one and nine. We identified three optimal factors, which we labeled unfolded self and life, the worthwhile life, and positive impact and legacy. Next, we selected marker items and replicated the factor structure in Sample 2. The three scales were positively intercorrelated and showed good internal consistency in both samples. For the affective component, exploratory and confirmatory factor analyses established a one-factor structure in both samples, and high internal consistency was obtained. Across a range of related constructs, we demonstrated construct and criterion validity. Notably, cognitive and affective fulfillment incrementally predicted a global rating of a fulfilled life and mental well-being, even after controlling for subjective and eudaimonic well-being. Overall, the study proves that the FLS is necessary to capture people’s experience of a fulfilled life, which could not be assessed sufficiently with previous well-being measures. Both cognitive and affective fulfillment were able to predict additional variance in mental well-being. Moreover, the study reveals psychometric support for the FLS and presents the first evidence on its validity. Lastly, applications in research and practice are discussed, especially in the context of living and aging well in the second half of life.

Higher-order dimensions of psychopathology in a neurodevelopmental transdiagnostic sample.

Hierarchical dimensional models of psychopathology derived for adult and child community populations offer more informative and efficient methods for assessing and treating symptoms of mental ill health than traditional diagnostic approaches. It is not yet clear how many dimensions should be included in models for youth with neurodevelopmental conditions. The aim of this study was to delineate the hierarchical dimensional structure of psychopathology in a transdiagnostic sample of children and adolescents with learning-related problems, and to test the concurrent predictive value of the model for clinically, socially, and educationally relevant outcomes. A sample of N = 403 participants from the Centre for Attention Learning and Memory (CALM) cohort were included. Hierarchical factor analysis delineated dimensions of psychopathology from ratings on the Conner’s Parent Rating Short Form, the Revised Children’s Anxiety and Depression Scale, and the Strengths and Difficulties Questionnaire. A hierarchical structure with a general p factor at the apex, broad internalizing and broad externalizing spectra below, and three more specific factors (specific internalizing, social maladjustment, and neurodevelopmental) emerged. The p factor predicted all concurrently measured social, clinical, and educational outcomes, but the other dimensions provided incremental predictive value. The neurodevelopmental dimension, which captured symptoms of inattention, hyperactivity, and executive function and emerged from the higher-order externalizing factor, was the strongest predictor of learning. This suggests that in struggling learners, cognitive and affective behaviors may interact to influence learning outcomes.

Measuring professional action competence in education for sustainable development (PACesd)

Based on the concept of action competence, the current study introduces an integrated framework of Professional Action Competence in Education for Sustainable Development (PACesd) described by three defining features: willingness, knowledge of pedagogical approaches, and self-efficacy. To validate this framework, we developed a questionnaire measurement instrument: ‘PACesd-Q’. This questionnaire was administered to a sample of 557 primary and secondary school in-service teachers in Flanders, Belgium. The instrument’s psychometric quality was assessed in terms of its reliability, construct, and criterion-related validity. Results of reliability analysis and hierarchical (second-order) confirmatory factor analysis provided evidence of good measurement properties of the instrument in terms of reliability and construct and criterion-related validity. We suggest the instrument can be successfully used to provide educational practitioners with a tool to monitor and eventually identify professional development needs regarding education for sustainable development.

Evaluation of basic laparoscopic training under 5A teaching mode

Objective: To evaluate the rationality and effectiveness of basic laparoscopic training under 5A teaching mode. Methods: A prospective randomized controlled study was conducted. The teaching records of 70 trainees who received basic laparoscopic traning at the Laparoscopic Surgical Training Base in Chinese PLA General Hospital from July to December 2019 were analyzed. All the trainees participating in the laparoscopy training had obtained the national practicing physician certificates, including 12 junior physicians of our center, 9 intermediate physicians of our center, 19 advanced physicians, 13 postgraduate students, 8 doctoral students, and 9 surgical standardized training physicians. A random number table method was used to divide all the trainees into two groups: the traditional teaching group or the 5A teaching group (35 people in each group). In the traditional teaching group, the training of 4 modules of " precise beans, quincuncial piles, ring positioning and knot-tying suture" modules according to a fixed sequence and schedule was carried out. Each module had a learning time of 8 hours. In the 5A teaching group, the training started from five dimensions of analysis, aim, accomplishment, appraise and advance. Before conducting each stage of training, the actual operation ability of the trainees was tested, each class hour was designed individually, accurate teaching was conducted to the trainees, the ability of the trainees was evaluated dynamically, and the previous steps were cycled periodically based on class hours. The operating time and pass rate of trainees of two groups in the basic operation module of laparoscopy were statistically analyzed, and a hierarchical analysis of related influencing factors was conducted. Results: The time of above modules before training in the 5A teaching group and the traditional teaching group was similar (all P>0.05). After definitive training, the time required for trainees in 5A teaching group and traditional teaching group to complete the 4 modules was shortened to varying degrees. Compared to traditional teaching group, 5A teaching group spent less time in completing each project [precise beans: (63.2±10.1) seconds vs. (83.6±18.7) seconds, quincuncial piles: (56.2±7.3) seconds vs. (101.4±31.7) seconds, ring positioning: (84.2±13.7) seconds vs. (127.3±28.5) seconds, knot-tying suture: (263.2±41.8) seconds vs.(428.8±95.2) seconds, all P<0.05], and had higher pass rates [precise beans: 97.1% (34/35) vs. 80.0% (28/35), quincuncial piles: 91.4% (32/35) vs.71.4% (25/35), ring positioning: 100.0% (35/35) vs. 82.9% (29/35), knot-tying suture: 77.1% (27/35) vs. 60.0% (21/35), all P<0.05]. Among the junior trainees (junior physicians of our center, postgraduate students, doctoral students, and standardized surgical training physicians) and intermediate trainees (intermediate physicians of our center and advanced physicians), the 5A teaching group completed 3 modules (quincuncial piles, ring positioning and knot-tying suture) faster than the traditional teaching group [junior trainees: quincuncial piles (76.4±12.4) seconds vs. (139.8±41.6) seconds, ring positioning (92.2±20.5) seconds vs. (131.3±28.4) seconds, knot-tying suture (293.8±66.7) seconds vs. (444.3±103.3) seconds; intermediate trainees: quincuncial piles (51.4±5.9) seconds vs. (94.7±8.6) seconds, ring positioning (63.9±13.5) seconds vs. (87.5±18.6) seconds, knot-tying suture (210.1±35.6) seconds vs. (367.5±54.9) seconds, all P<0.05]. Conclusion: 5A teaching mode can acheive better training results compared with the traditional teaching mode in basic laparoscopic training, and is worthy of further popularization and application.

Bayesian Hierarchical Factor Analysis for Efficient Estimation Across Race/Ethnicity

Patient reported outcomes are gaining more attention in patient-centered health outcomes research and quality of life studies as important indicators of clinical outcomes, especially for patients with chronic diseases. Factor analysis is ideal for measuring patient reported outcomes. If there is heterogeneity in the patient population and when sample size is small, differential item functioning and convergence issues are challenges for applying factor models. Bayesian hierarchical factor analysis can assess health disparity by assessing for di˙erential item functioning, while avoiding convergence problems. We conducted a simulation study and used an empirical example with American Indian minorities to show thatffitting a Bayesian hierarchical factor model is an optimal solution regardless of heterogeneity of population and sample size.

Hierarchical Factor Analysis Methodology for Intelligent Manufacturing

To realize intelligent manufacturing, a controllable factory must be built, and manufacturing competitiveness must be achieved through the improvement of product quality and yield. The yield in the micromanufacturing process is gaining importance as a management factor used in deciding the production cost and product quality as product functions becomes more sophisticated. Because the micromanufacturing process involves manufacturing products through multiple steps, it is difficult to determine the process or equipment that has encountered failure, which can lead to difficulty in securing high yields. This study presents a structural model for building a factory integration system to analyze big data at manufacturing sites and a hierarchical factor analysis methodology to increase product yield and quality in an intelligent manufacturing environment. To improve the product yield, it is necessary to analyze the fault factors that cause low yields and locate and manage the critical processes and equipment factors that affect these fault factors. However, yield management is a difficult problem because there exists a correlation between equipment, and in the sequence of process equipment that the lot passed through, the downstream and the upstream cause complex faults. This study used data-mining techniques to identify suspected processes and equipment that affect the yield of products in the manufacturing process and to analyze the key factors of the equipment. Ultimately, we propose a methodology to find the key factors of the suspected process and equipment that directly affect the implementation of the intelligent manufacturing scheme and the yield of the product. To verify the effect of key parameters of critical processes and equipment on the yield, the proposed methodology was applied to actual manufacturing sites.

Hierarchical analysis of factors influencing acceptance of remanufactured medical devices

The growth of remanufacturing has seen its application in different industrial sectors including automotive, electronics and medical devices. In medical and healthcare sector, remanufacturing presents an opportunity to equip facilities with functional, safe, affordable and sustainable medical systems. However, there is a lack of understanding of the key factors that influence customers' acceptance of remanufactured medical devices. This study addresses this gap by analysing and ranking key factors that impact customers' decisions to purchase and use remanufactured medical systems using pairwise comparisons obtained from the analytical hierarchical process (AHP) model. The structural decision hierarchy was developed followed by a description of the adopted scale of importance. Thereafter, pairwise comparisons were performed by the expert panel constituted by six medical equipment experts with a total of 194 years’ experience between them. The responses were tested for rationality and consistency, the analysis of the comparisons was performed, and factor weights obtained for each factor. Results obtained ranked product quality as the most critical factor affecting acceptance of remanufactured devices followed by price, warranty, brand equity, available information, added value services and environmental friendliness. Findings from this study highlight the peculiarity of medical devices remanufacturing which gives more attention to product quality in terms of performance and safety. Taken together, these results provide a basis on which medical devices remanufacturers can improve customer acceptance. Before this study, discussions on customer acceptance of remanufactured medical devices were purely anecdotal and this is the first comprehensive investigation of customer factors in medical devices remanufacturing.