Psychometric properties of the Chinese version of the M.D. Anderson symptom Inventory-Multiple Myeloma Module: a translation and validation study.

Background

Multiple myeloma is a malignant clonal bone marrow disease originating from plasma cells, characterized by excessive secretion of monoclonal immunoglobulins. Clinical manifestations include anemia, bone pain, hypercalcemia, renal impairment, and amyloidosis [ 1 ]. This disease predominantly affects individuals aged 55–74 years [ 2 ]. According to 2022 global epidemiological data, there were 187,000 new multiple myeloma cases diagnosed worldwide, with 121,000 associated deaths, making it the third most common hematologic malignancy [ 3 ]. Given the acceleration of global population aging, its incidence and prevalence demonstrate a significant upward trend, presenting an increasing disease burden and challenging outlook [ 4 ]. Chemotherapy remains the primary treatment modality for multiple myeloma, and patients experience multidimensional symptom clusters due to prol pain, peripheral neuropathy, insomnia, nausea, vomiting, skin rashes, and depression [ 5 – 7 ], which significantly impact patients’ prognosis and health-related quality of life. Additionally, multiple myeloma has markedly increased healthcare resource utilization and imposed substantial economic burdens on patients, families, and society, thus representing a critical public health challenge requiring immediate attention.

Effective symptom management relies on precise symptom screening and assessment, and utilizing standardized, objective evaluation tools is essential for effectively assessing symptoms in multiple myeloma patients. Currently, Chinese researchers have neither introduced nor developed specific assessment scales for multiple myeloma symptoms. Most commonly used universal scales in China include the Edmonton Symptom Assessment Scale (ESAS) [ 8 ] and Memorial Symptom Assessment Scale (MSAS) [ 9 ]. In 2013, the University of Texas MD Anderson Cancer Center developed the MDASI-MM [ 10 ], which comprehensively addresses specific symptoms of multiple myeloma patients, offers ease of use, and demonstrates strong reliability and validity [ 6 ]. This study aimed to establish a reliable and scientific instrument for evaluating symptoms in Chinese patients with multiple myeloma by translating the MDASI-MM into Chinese and assessing its validity and reliability across diverse Chinese myeloma patient populations.

Methods

Samples and setting

This prospective cross-sectional study was conducted across multiple sites. Using a convenience sampling method, multiple myeloma patients were selected from hematology departments of three tertiary general hospitals in Zhejiang Province, China, between August 2023 and December 2023. Inclusion criteria required patients to: (1) meet the diagnostic and treatment criteria of the Multiple Myeloma , Version 2.2024 , NCCN Clinical Practice Guidelines in Oncology [ 11 ], with confirmation through laboratory and pathological examinations; (2) be conscious and capable of verbal communication; (3) be informed of their condition; (4) provide signed informed consent and voluntary participation. Exclusion criteria comprised: (1)I ndividuals with multiple malignant tumors; (2) patients with critical conditions or severe physical illnesses, including cardiac, cerebral, or pulmonary diseases; (3) vulnerable populations, including those with psychiatric disorders, cognitive impairments, critically ill patients, minors, pregnant women, and illiterates.

Instruments

General demographic characteristics questionnaire

The questionnaire was developed based on literature review. It encompassed sociological data: age, sex, BMI, nationality, marital status, education level, work, residence, religious belief, etc.; and disease-related data: duration of illness, disease staging, tumor metastasis, number of comorbidities, Eastern Cooperative Oncology Group (ECOG) physical status, and related factors. Participants self-reported sociologic information, while researchers obtained clinical disease information through medical record review.

M.D. Anderson symptom Inventory-Multiple myeloma Module(MDASI-MM)

A customized version of the M.D. Anderson Symptom Inventory (MDASI) [ 12 ], the MDASI-MM scale [ 10 ] was developed in 2013 by Jones et al. from the M.D. Anderson Cancer Center, USA, to evaluate the severity of symptoms and degree of daily life distress experienced by multiple myeloma patients during the previous 24 h. The scale comprises two components, the first of which consists of 20 symptom assessment items, including 13 core symptoms (pain, fatigue, nausea, disturbed sleep, emotional distress, shortness of breath, difficulty remembering, lack of appetite, drowsiness, dry mouth, sadness, vomiting and numbness or tingling) and 7 multiple myeloma-specific symptoms (constipation, muscle weakness, diarrhea, sore mouth or throat, rash, paying attention, bone aches), and the second of which comprises 6 interference items (general activity, mood, work, relations with other people, walking and enjoyment of life). Each item is rated on a scale from 0 to 10, where 0 indicates “no symptoms” or “no distress” and 10 represents “worst imaginable” or “total distress.” Higher scores indicate greater symptom severity.

Chinese version of the Edmonton symptom assessment scale (ESAS)

The ESAS was developed by Canadian researcher Bruera [ 8 ] in 1991 to assess common psychological and physical symptoms in cancer patients. The scale evaluates nine specific symptoms including discomfort, exhaustion, nausea, and appetite loss, plus one optional symptom. Symptoms are rated from 0 to 10, with higher scores indicating greater severity. In 2015, Chinese researchers Dong et al. [ 13 ] modified the scale by incorporating “itchy skin” as an additional symptom. The Chinese version demonstrated a Cronbach’s alpha coefficient of 0.71. The Limited Symptom Remeasurement was utilized as a validity measure, showing reliability coefficients between 0.72 and 0.92.

Procedure

Translation and back-translation of the scale

Following email approval from Dr. Xin Shelley Wang, the original author, the scale underwent Chinese translation following the Brislin bidirectional translation method [ 14 ]. Initially, two bilingual individuals proficient in both Chinese and English conducted independent forward translations (one English master with eighth-grade English proficiency and one doctor of nursing with international study experience). The translation process adhered strictly to principles of conceptual, semantic, content, technical, and standardized equivalence with the original scale [ 15 ], resulting in Chinese versions A1 and A2. Subsequently, researchers and translators performed orthographic synthesis, comparing and integrating the original scale with A1 and A2 to create Chinese version A3. In the third step, two graduates with master’s degrees who were native English speakers fluent in Chinese had never seen the original scale and had no medical experience, back-translated. They independently translated the Chinese version A3 back to English, resulting in two back-translated versions, B1 and B2. The fourth step involved back-translation synthesis, where researchers and translators compared versions B1 and B2, conducting revisions and discussions to create version B3. Finally, the Chinese version A3 and back-translated version B3 were submitted to the original authors for review. Following their feedback and recommendations, researchers developed the initial Chinese version of MDASI-MM.

Cross-cultural debugging of the scale

Nine experts from hematology diagnostics, hematology nursing, nursing administration, and nursing education are invited, all with a master’s degree or higher in medicine or nursing and at least 10 years of experience working with multiple myeloma patients in healthcare. Based on their professional knowledge and clinical work experience, the experts independently reviewed the content of each entry on the scale using a Likert 4-point scale in four aspects [ 16 ], namely, ease of understanding of the entries (about the reading level of the sixth grade in elementary school [ 15 ]), linguistic conventions, cultural context compliance, and content relevance, with a score of 1–4 representing, in order of priority, “irrelevant,” “somewhat relevant,” “relevant,” and “very relevant.”

Prior to the official survey, thirty patients with multiple myeloma who satisfied the inclusion and exclusion criteria took part in a pilot study. After completing the scale, the completion time was recorded, and the patients were asked how they felt about finishing the scale to assess their understanding of the scale guidelines and the various entries. They were invited to give their opinions and suggestions on the entries’ unclear or semantically ambiguous points. Following the pre-survey findings, the study team refined the wording of the scale questions until a consensus was achieved, culminating in the final Chinese version of the MDASI-MM.

Data collection procedure

In this study, data collectors underwent a comprehensive standardized training protocol comprising three sequential phases: theoretical instruction, practical simulation, and competency evaluation. The theoretical curriculum encompassed research contextualization and cross-cultural adaptation rationale, instrument structure and psychometric properties, standardized operating procedures for data acquisition, patient-centered communication strategies, quality control metrics, and ethical compliance protocols. Practical training utilized scenario-based simulations replicating clinical environments, enabling trainees to operationalize data collection protocols and manage unanticipated contingencies through deliberate practice. The assessment incorporated scale sinicization, reliability and validity standards, ethical norms, role-playing, and standardized patient evaluation, with survey administration permitted only after successful completion. Monthly group meetings facilitated discussion of challenges and process optimization, establishing a feedback mechanism. Prior to study initiation, strict ethical guidelines were implemented. Following approval from the head nurse, department director, and hospital ethics committee, data collectors administered questionnaires through paper-based completion and questionnaire-star QR code WeChat responses during patient hospitalization. Data collectors explained the survey objectives, significance, and completion guidelines to patients and families. Questionnaire distribution proceeded after obtaining signed informed consent. Data collectors reviewed medical records for clinical information following patients’ completion of general information. Patients independently completed the symptom scale, with assistance provided to those who were elderly, severely weakened, or less educated through clear, unbiased verbal administration. The data collection environment remained quiet, with collectors present to address questions. Collectors verified questionnaire completeness and accuracy, addressing any discrepancies immediately. The study collected 512 questionnaires, with 500 deemed valid.

Ethical statement

This study was conducted in strict accordance with the principles of the Declaration of Helsinki, and all participants read and signed an informed consent form. The hospital’s Ethics Committee approved the study (Approval Number: Ethics Review No. 0123 of 2024, Sir Run Run Shaw Hospital).

Data analysis

Software called Epidata 3.1 was used to enter the data twice, and SPSS 26.0 and AMOS 23.0 were used for statistical analysis. Frequency and percentage were used to characterize the count data. A normal distribution was used to determine the two-sided test level α for the measurement data, and P < 0.05 denoted statistical significance.

Item analysis

The correlation coefficient and decisive value procedures are commonly employed for item analysis. Independent samples t-test evaluated differences between high and low groups for each item. Items with P < 0.05 were retained, indicating acceptable differentiation levels. The decisive value method arranges scale scores from high to low, with the top 27% representing the high group and the bottom 27% representing the low group [ 17 ]. The correlation coefficient approach assessed item homogeneity and independence. Items with correlation values exceeding 0.2 or P < 0.05 were retained, utilizing the Pearson correlation coefficient method to determine relationships between individual item scores and total scale scores [ 17 ].

Validity analysis

A scale’s validity reflects its accuracy in measuring intended concepts and demonstrates its authenticity [ 18 ]. This study assessed validity through multiple approaches: convergent, discriminant, construct, content, and calibration validity.

Content validity was evaluated by nine subject-matter experts. The item-level content validity index (I-CVI) was determined by calculating the ratio of experts who assigned scores of three or four to the total number of experts. The scale-level content validity index/universal agreement (S-CVI/UA) was calculated by dividing items rated three or four by total expert submissions. The scale-level content validity index/average (S-CVI/Aue) represents the mean of all I-CVI entries. Strong content validity is indicated by S-CVI/UA ≥ 0.80, S-CVI/Aue ≥ 0.90, and I-CVI ≥ 0.78 [ 19 ]. The structural validity assessment employed validation factor analysis on 500 questionnaires using AMOS 23.0 software with the maximum likelihood method. Model fit is considered adequate when the chi-square/degree of freedom ratio (χ 2 /df) is between 1 and 3, goodness-of-fit index (GFI) > 0.80, root mean square error of approximation (RMSEA) < 0.08, comparative fit index (CFI) > 0.80, normed fit index (NFI) > 0.80, tucker-lewis index (TLI) > 0.80, incremental fit index (IFI) > 0.80, and adjusted goodness of fit index (AGFI) > 0.80 [ 20 , 21 ]. Convergent validity refers to the correlation between scales measuring identical concepts [ 22 ]. Adequate convergent validity is established when combination reliability (CR) exceeds 0.60 and average variance extracted (AVE) exceeds 0.50 [ 23 ]. Discriminant validity is confirmed when the square root of AVE exceeds the correlation coefficient of latent variables [ 24 ]. The Pearson correlation coefficient method was utilized to determine correlation coefficients between the Chinese versions of the MDASI-MM and ESAS scales. Correlation coefficients ≥ 0.7 indicate strong correlation, with higher coefficients suggesting superior calibration validity [ 25 ].

Reliability analysis

Reliability reflects a scale’s consistency, stability, and dependability. This study assessed reliability through split-half reliability and internal consistency reliability. A Cronbach’α coefficient exceeding 0.8 indicates excellent internal consistency [ 26 ]. Split-half reliability was evaluated using the Spearman-Brown coefficient, calculated by dividing entries into two segments based on parity. A coefficient exceeding 0.8 indicated high reliability [ 16 ].

Responsiveness

The study population was categorized based on physical condition suitability for chemotherapy into two ECOG score subgroups: <3 (ideal for chemotherapy) and ≥ 3 (unsuitable for chemotherapy). The Chinese version of the MDASI-MM scale’s overall scores, symptomatic items, and interference items were used to compare the ECOG subgroups. The statistical significance cutoff point was set at P < 0.05.

Results

Patients

The 500 individuals with multiple myeloma in the study had an average age of 67.63 ± 9.39 years. There were 219 women (43.8%) and 281 men (56.2%). Table 1 displays all other baseline clinical and sociodemographic information.

Table 1 The participant socio‑demographic characteristics ( N = 500) Factors Group n % Age < 61 117 23.4 61–70 180 36.0 71–80 165 33.0 > 80 38 7.6 Gender Male 281 56.2 Female 219 43.8 Body mass index < 18.5 33 6.6 18.5–23.9 277 55.4 24.0-27.9 159 31.8 > 28.0 31 6.2 Nationality Han ethnic group 500 100 Residence Towns 289 57.8 Countryside 211 42.2 Marital status Unmarried/Divorced/Widowed 26 5.2 Married 474 94.8 Work Employed 38 7.6 Leave/Retirement 331 66.2 Peasants 131 26.2 Education attainment Primary school and below 265 53.0 Junior high school 142 28.4 Senior school 62 12.4 College or above 31 6.2 Monthly per capita household income (yuan) <3000 189 37.8 3000–5000 160 32.0 > 5000 151 30.2 Type of medical insurance Provincial medical insurance 101 20.2 Municipal health insurance 239 47.8 Rural social pension insurance 160 32.0 Residency status Solitary/sanatoriums 25 5.0 Living with family 475 95.0 Religious belief Without 411 82.2 With 89 17.8 Duration of illness <3 months 100 20.0 3–6 months 41 8.2 6–12 months 66 13.2 More than 1 year 293 58.6 Disease Staging(R-ISS Staging) I Staging 95 19.0 II Staging 196 39.2 III Staging 209 41.8 Tumor Metastasis Without 54 10.8 With 446 89.2 Number of comorbidities 0 230 46.0 1 203 40.6 ≥ 2 67 13.4 Combination Chemotherapy No 56 11.2 Yes 444 88.8 R-ISS staging is Revised International Staging System (Revised International Prognostic Staging Criteria 2015), which complements and improves the original ISS (International Staging System) staging; combination chemotherapy refers to the use of two or more chemotherapy drugs in combination, including traditional chemotherapeutic drugs, proteasome inhibitors, immunomodulators, targeted drugs, and inhibitors of nuclear output proteins

Cross-cultural adaptation

The forward and reverse translations of this study proceeded efficiently, requiring no additional modifications to the scale. The expert correspondence achieved 100% positivity across two rounds, with coefficients of 0.844 for authority, 0.811 for familiarity, and 0.877 for judgment foundation. During the pre-survey phase, all 30 participants indicated that the scale items were clearly written, semantically clear, and readily comprehensible. The scale requires 5 to 7 min for completion.

Item analysis

The decision value analysis revealed statistically significant score differences between high and low categories ( P < 0.05), with the exception of question 16, “Your diarrhea (loose stools) at its WORST?”. The correlation coefficients between individual item scores and the overall scale score ranged from 0.260 to 0.915 ( P < 0.05), all exceeding 0.200, thus confirming item representativeness. The poor differentiation of item 16 may be attributed to the fact that some patients primarily exhibited diarrhea symptoms while other symptoms remained minimal [ 27 ]. Given the clinical significance of diarrhea in symptom assessment for multiple myeloma patients, the research team opted to retain item 16 for subsequent analysis. Details are presented in Table 2 .

Table 2 Item analysis of the MDASI-MM scale ( N = 500) Item Mean ± Std. Deviation Critical ratio Correlation coefficient between item and total score P High Group Low Group 1 4.32 ± 2.88 1.09 ± 0.33 -9.192 0.556 < 0.001 2 6.24 ± 2.20 2.10 ± 1.31 -13.320 0.705 < 0.001 3 1.46 ± 1.25 1.03 ± 0.17 -2.785 0.327 0.006 4 4.54 ± 2.67 1.72 ± 1.28 -7.869 0.624 < 0.001 5 3.16 ± 1.81 1.22 ± 0.71 -8.239 0.602 < 0.001 6 2.63 ± 2.09 1.16 ± 0.59 -5.575 0.516 < 0.001 7 3.41 ± 2.31 1.35 ± 0.86 -6.897 0.544 < 0.001 8 3.96 ± 2.37 1.22 ± 0.64 -9.202 0.657 < 0.001 9 2.76 ± 2.24 1.06 ± 0.34 -6.208 0.556 < 0.001 10 3.31 ± 2.29 1.43 ± 0.90 -6.312 0.596 < 0.001 11 3.25 ± 1.92 1.10 ± 0.46 -8.970 0.723 < 0.001 12 1.31 ± 0.95 1.00 ± 0.00 -2.680 0.260 0.008 13 3.01 ± 2.63 1.49 ± 1.13 -4.402 0.416 < 0.001 14 2.65 ± 2.17 1.35 ± 1.00 -4.463 0.531 < 0.001 15 4.46 ± 2.83 1.28 ± 0.67 -9.008 0.771 < 0.001 16 1.34 ± 1.38 1.03 ± 0.24 -1.820 0.289 0.071 17 1.65 ± 1.37 1.01 ± 0.12 -3.795 0.507 < 0.001 18 1.56 ± 1.5 1.12 ± 0.86 -2.107 0.384 0.037 19 2.71 ± 1.56 1.12 ± 0.44 -8.100 0.618 < 0.001 20 4.06 ± 3.07 1.10 ± 0.35 -7.886 0.583 < 0.001 21 7.00 ± 1.97 1.43 ± 0.83 -21.484 0.915 < 0.001 22 4.38 ± 1.85 1.47 ± 1.10 -11.181 0.696 < 0.001 23 8.29 ± 1.86 2.47 ± 1.52 -19.980 0.870 < 0.001 24 4.44 ± 2.15 1.31 ± 0.89 -11.123 0.680 < 0.001 25 6.71 ± 2.29 1.41 ± 1.15 -17.063 0.860 < 0.001 26 7.28 ± 2.25 2.93 ± 2.08 -11.721 0.777 < 0.001

Validity analysis

Content validity

The Chinese version of the MDASI-MM scale exhibits strong content validity, with an I-CVI ranging between 0.889 and 1.000, an S-CVI/UA of 0.846, and an S-CVI/Ave of 0.983.

Construct validity

Following the extraction of three male components based on the original scale’s structural framework, the analysis yielded a KMO value of 0.861 and Bartlett’s test of sphericity showed an approximate chi-square value of 3335.526 (df = 325, P < 0.001), confirming the appropriateness of factor analysis. Parameter estimation utilized the maximum likelihood method. The path diagram incorporated three latent variables (“Core symptoms”, “Multiple Myeloma symptoms”, and “Interference items”) and 26 observed variables to construct the validated factor analysis model. The model demonstrated statistical significance at P < 0.001. Initial fitting indices were suboptimal, necessitating model adjustment. After modifications (including correlating residuals e1 and e20, e3 and e8, e3 and e12, e4 and e5, e5 and e11, e5 and e22, e7 and e19, e8 and e12, e9 and e26, e11 and e19, e11 and e22, e16 and e17, e16 and e25, paths between e19 and e24, e23 and e26, e24 and e26), the final model achieved satisfactory fit indices: χ 2 /df = 1.687, GFI = 0.879, RMSEA = 0.053, CFI = 0.913, NFI = 0.813, TLI = 0.899, IFI = 0.915, and AGFI = 0.848. Figure 1 presents the validation factor analysis results.

Fig. 1 Standardized three-factor structural model of the MDASI-MM. F1 (Core symptoms, 13 items), F2 (Multiple Myeloma symptoms, 7 items), F3 (Interference items, 6 items)

Convergent validity and discriminant validity

The scale demonstrated robust convergent validity with standardized factor loadings ranging from 0.403 to 0.918, AVE values of 0.529 and 0.643 for the 20 symptom entries and 6 interference items respectively, and CR values of 0.747 and 0.865. The scale exhibited strong discriminant validity with AVE square roots of 0.923 and 0.943 for the symptom entries and interference items respectively, and a correlation coefficient of 0.749 that remained below the corresponding AVE square root.

Calibration validity

This study validated the Chinese version of the MDASI-MM scale using the Chinese version of the ESAS scale as a standardized reference instrument. The results demonstrate that the Chinese version of the MDASI-MM scale exhibits strong calibration validity. The correlation coefficients between the total scores of the 20 symptomatic items and 6 interference items were 0.869 and 0.838 ( P < 0.001), respectively. Furthermore, a correlation of 0.914 ( P < 0.001) was observed between the Chinese versions of the ESAS scale and the MDASI-MM scale.

Reliability analysis

The Cronbach’s alpha coefficients for the 20 symptomatic entries and six interference items were 0.856 and 0.889, respectively, while the Chinese version of the MDASI-MM scale demonstrated a Cronbach’s alpha coefficient of 0.908. The split-half reliability for the complete scale was 0.890. The 20 symptomatic entries and six interference items showed split-half reliabilities of 0.873 and 0.916, respectively.

Responsiveness

The overall scores for symptomatic entries, interference items, and the Chinese version of the MDASI-MM scale were significantly higher ( P < 0.001) in the ≥ 3 group compared to the < 3 group, as illustrated in Table 3 .

Table 3 Responsiveness of the Chinese version of the MDASI-MM scale ( N = 500) Item ECOG score < 3 group ECOG score ≥ 3 group Z score Symptom Assessment Scale Total Score 23.00(14.00,36.80) 51.00(35.80,71.30) -8.208 Total score for core symptom entries 8.00(5.00,15.00) 18.00(12.00,26.30) -6.892 Total score for Multiple Myeloma symptoms 2.00(0.00,5.00) 5.00(2.00,10.00) -4.529 Total score for Interference items 11.50(6.00,17.00) 27.50(20.00,35.00) -9.168

Discussion

The implementation of objective, standardized, and uniform assessment tools for accurately quantifying symptoms in multiple myeloma patients is essential for effective symptom management and precise intervention planning. Currently, Chinese researchers predominantly utilize universal symptom assessment tools, which may not adequately address the specific symptoms experienced by multiple myeloma patients. Thus, adapting established specialized assessment tools from other countries holds practical significance. This study represents the first Chinese translation of the MDASI-MM scale, conducted meticulously following Brislin’s two-way translation methodology, and demonstrates excellent psychometric properties in terms of reliability, validity, and responsiveness.

Item analysis serves to evaluate scale entries’ representativeness, consistency, and differentiation as criteria for entry retention or removal [ 28 ]. The item analysis revealed statistically significant differences between high and low subgroups for all items except item 16. Moreover, a significant correlation ( P < 0.001) existed between individual item scores and the overall scale. The lack of statistical significance in item 16 between high and low subgroups may be attributed to cultural differences in symptom perception. Chinese culture emphasizes patience and self-regulation regarding diarrhea symptoms, often attributing mild cases to dietary issues and seeking medical attention only when symptoms severely impact daily life. Conversely, Western cultures demonstrate greater sensitivity to diarrhea symptoms and emphasize the reporting of abnormal bodily signals. Chinese culture, particularly among older male patients, tends to underreport diarrhea symptoms, typically relying on physician inquiries rather than proactive reporting. This cultural distinction resulted in a more concentrated distribution of diarrhea severity scores among Chinese patients, making high and low group differentiation challenging. Western patients, however, demonstrated clearer distinctions in diarrhea severity, yielding statistically significant scale scores. Additionally, some multiple myeloma patients presented diarrhea as their initial or primary symptom. Following group discussion and consultation with experts and original authors, the decision was made to retain this entry. Overall, the scale entries effectively reflect multiple myeloma patients’ symptoms and distress levels with good differentiation.

Reliability indicates the scale’s consistency, stability, and dependability [ 29 ]. This study assessed reliability through split-half reliability and internal consistency measures. The Cronbach’s alpha coefficients for the 6 interference items and 20 symptom items are 0.889 and 0.856, respectively, with the Chinese version of the MDASI-MM scale achieving 0.908. Conventionally, Cronbach’s alpha coefficients exceeding 0.70 indicate good reliability, 0.60–0.70 suggest fair reliability, and values below 0.600 indicate poor reliability requiring scale modification. The present study’s Cronbach’s alpha coefficients align with those of the original scale (0.85–0.91), indicating high reliability. The Chinese version of the MDASI-MM scale demonstrated a split-half reliability of 0.916, with values of 0.890 and 0.873 for the 20 symptom entries and six interference items, respectively.

The degree to which a measurement tool reliably and consistently captures the topics it assesses is known as its validity [ 30 ]. This study evaluated the scale’s validity using discriminant, convergent, construct, content, and calibration validity criteria. Content validity determines whether scale items meet the assessment’s criteria and objectives [ 31 ]. The Chinese version of the MDASI-MM scale demonstrated enhanced content validity through its I-CVI between 0.889 and 1.000, S-CVI/UA of 0.846, and S-CVI/Ave of 0.983, achieving conceptual, semantic, and content equivalency with the original scale. Construct validity indicates the measure’s alignment with the scale’s theoretical structure [ 32 ]. Confirmatory factor analysis typically evaluates the scale’s construct soundness [ 33 ]. In the validation factor analysis, a 3-factor structural equation model was developed following the original scale’s framework. The initial model underwent correction to ensure standard factor loading values ≥ 0.4, except for entries 3 (nausea), 12 (vomiting), 13 (numbness or tingling), 14 (constipation), 16 (diarrhea), 18 (skin rash), and 20 (bone aches). The structural equation modeling indicators met ideal standards, confirming agreement between theoretical model and empirical data, thus demonstrating good structural validity. Factor Loading represents the core parameter of validated factor analysis (CFA), measuring the linear relationship strength between observed and latent variables [ 34 ]. This study retained entries with low factor loading based on expert opinion and their essential clinical value. Although including bone pain, painful numbness (hallmark symptoms of multiple myeloma), and treatment toxicity indicators (nausea, vomiting, diarrhea, constipation, and rash) reduced statistical indices, it enabled more comprehensive symptom heterogeneity capture. Future longitudinal data may further validate the model’s stability. The convergent and discriminant validity indicators met criteria, demonstrating item independence and relatedness. Calibration validity reflects the correlation between measurement and criterion scales, with higher correlation indicating better scale-calibration validity [ 35 ]. The significant positive correlations between Chinese versions of the MDASI-MM and ESAS scales demonstrated strong scale calibration validity.

The scale comprehensively addresses somatic symptoms, psychological symptoms, and symptomatic disturbances in multiple myeloma patients’ daily lives. Its moderate entry count, comprehensible format, and brief completion time of 5–7 min facilitate widespread clinical and research applications. The MDASI-MM Scale effectively identifies patient symptom levels, enabling early clinical assessment, screening, treatment, and intervention. Additionally, the scale assists healthcare professionals in monitoring symptomatic changes dynamically, allowing timely intervention strategy adjustments and precise care delivery to enhance patient quality of life. Furthermore, the validated scale serves as a standardized assessment tool, providing reliable data for symptom epidemiology studies, objective evaluation indices for symptom management intervention studies, and symptom cluster analysis to identify characteristic symptom patterns in multiple myeloma.

Limitations

Several limitations warrant consideration in this study. First, the study population was selected through convenience sampling from three tertiary-level hospitals in Zhejiang Province. Given that symptoms may vary among patients from different regions, cultural backgrounds, and medical settings, future research should employ stratified sampling to expand the sample selection across multiple provinces and medical institutions at various levels to evaluate the scale’s broader clinical applicability. Second, the sample predominantly comprised individuals over 60 years of age, lacking comprehensive coverage across age groups, particularly those under 40 years. Future studies should include a wider age range to enhance sample diversity and enable more comprehensive assessment of the scale’s scientific validity and reliability. Additionally, potential overfitting in the structural equation modeling necessitates further research to validate the construct validity of the MDASI-MM. Lastly, this study did not conduct retest reliability testing, which should be addressed in subsequent investigations.

Conclusion

This study introduced the MDASI-MM scale to China through a rigorous process of cross-cultural debugging, orthographic translation, and back-translation. The Chinese version of the MDASI-MM scale demonstrated robust responsiveness, content validity, construct validity, and reliability as an assessment tool for symptom severity in Chinese patients with multiple myeloma. The measure provides healthcare professionals with a validated instrument to evaluate symptoms and symptom distress in multiple myeloma patients, establishing a foundation for developing precise and effective interventions while advancing understanding of the disease’s characteristics.

Publisher’s note

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Ting Wang and Weiwei Chen contributed equally to this work and should be considered co-first authors.

Acknowledgements

We express our great gratitude to the participants in the study. Moreover, we sincerely thank the reviewers for their valuable comments and the hard work of the editors.

Author contributions

Ting Wang and Weiwei Chen contributed equally to this work.The authors confirm their contributions to the paper as follows: Ting Wang and Weiwei Chen were responsible for the conceptualization and design of the study, data collection, data analysis, writing the manuscript, and approving the version of the manuscript to be published; Yao Ge and Yanke Mao were responsible for the distribution and return of the questionnaires, Weiwei Chen and Yingying Lin was responsible for the expert interviews, Huan Liu analyzed the data. LeiWen Tang and Junxiang Sun take control of the research program, critically revise crucial intellectual content, and approve the version of the manuscript to be published.

Funding

This work was supported by the Zhejiang Provincial Medical and Health Science and Technology Program, project No.2023KY789.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available to preserve anonymity of the respondents but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Sir Run Run Shawe Hospital, Zhejiang University School of Medicine (Approval Number: Ethics Review No. 0123 of 2024, Sir Run Run Shaw Hospital). We certify that this study was conducted in accordance with the 1964 Declaration of Helsinki and subsequent amendments, and all methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was obtained from all participants prior to enrollment in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Abbreviations

Combination Reliability

Average Variance Extracted

Item-level Content Validity Index

Scale-level Content Validity Index/Universal Agreement

Scale-level Content Validity Index/Average

Chi-square/Degree of freedom ratio

Goodness-of-fit Index

Root Mean Square Error of Approximation

Comparative Fit Index

Normed Fit Index

Tucker-Lewis Index

Incremental Fit Index

Adjusted Goodness of Fit Index

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