Потребность в помощи и соответствующий вопросник для семей, обеспечивающих уход за пациентами с множественной миеломой: исследование по вопросам развития и перекрестной проверки.

Background

Multiple myeloma (MM) is a hematologic malignancy characterized by abnormal clonal plasma cells that most commonly occur in elderly [ 1 ]. With the advancements in targeted medication, cellular immunotherapy, and hematopoietic stem cell transplantation, the overall survival of patients with multiple myeloma has been significantly lengthened [ 2 ]. However, the long treatment periods, serious burden of symptoms, and high cost of treatment not only bring pain to patients but also make caregivers bear heavy physiological, psychological, and economic burdens [ 3 , 4 ].

In patient care, family caregivers play a pivotal role but their supportive care needs have long been overlooked [ 5 ]. Amid broad-scale shortages in medical resources, family caregivers are the core caregivers of patients in the process of treatment and rehabilitation. Caregivers of patients with multiple myeloma tend to provide emotional and practical support almost exclusively to patients. Their needs were often ignored by themselves, leading to experiences of an improved burden and difficulties with coping. For example, some caregivers have chronic illnesses that need attention but are ignored, which may indicate that caregivers neglect their needs to meet the needs of patient [ 3 , 5 ]. Owing to the uncertainty of the patient’s survival and future, caregivers are prone to worries, insecurity, and fears [ 6 ]. Moreover, the treatment mode of patients with multiple myeloma has gradually changed from inpatient to day or outpatient treatment [ 7 , 8 ], which presents more complex challenges to family caregivers.

Supportive care needs (SCN) refer to the requirements for services and assistance that address the physical, informational, emotional, psychological, social, and practical issues arising from cancer and its treatment, from diagnosis onwards [ 9 ]. When these needs are perceived by the individual as being sufficiently addressed by existing services or support, they are considered met needs [ 10 ]. Conversely, unmet needs represent the gap between the services perceived as necessary and those actually received. Caregivers of cancer patients have a heavy burden of care and unmet supportive care needs [ 10 , 11 ]. Care procedures for patients with hematologic neoplasms are more complicated than those for solid tumors; caregivers are under great pressure and have high demands for information and emotion [ 12 ]. Caregivers of patients with multiple myeloma are plagued by multiple problems related to disease uncertainty, unmet information, psychological and emotional issues, economic and social support, and medical services [ 4 , 5 ]. Caregivers’ physical and mental issues are caused by a variety of unmet needs that manifest as headaches, insomnia, and gastrointestinal reactions, as well as distress, anxiety, and depression [ 10 , 13 ]. Therefore, support services for family caregivers of patients with multiple myeloma must be improved to meet their needs. In this regard, a pressing issue is the rapid and accurate identification of the supportive care needs and extent of unmet needs of caregivers of patients with multiple myeloma. Such identification would be helpful for medical staff to provide targeted services according to their needs.

According to the Supportive Care Needs Framework, the supportive care needs of cancer patients and their family members are composed of seven dimensions, namely, practical, spiritual, social, psychological, information, emotional, and physiological needs [ 14 ]. Several tools have been developed to assess cancer caregiver needs, such as the Home Caregiver Need Survey [ 15 ], Family Inventory of Needs Assessment [ 16 ], Supportive Care Needs Survey-Partners and Caregivers [ 17 , 18 ], and Comprehensive Needs Assessment Tool in Cancer for Caregivers [ 19 ]. However, these scales are universal and do not specifically target a certain group of caregivers and can only evaluate the degree of demand and satisfaction. As they do not fully elucidate the degree of caregiver supply and unmet demand, they cannot inform targeted measures. The Needs Assessment of Family Caregivers-Cancer [ 20 ], which is based on the need fulfillment theory, can evaluate the unmet needs of family caregivers of cancer patients and is more commonly used in solid tumors. However, radiotherapy and chemotherapy are the main means of treatment for hematologic malignancies, in contrast to solid tumors that can be treated by surgery. Family caregivers of patients with multiple myeloma have indicated a practical need to care for patients [ 5 ]. Therefore, the supportive care needs of family caregivers of patients with multiple myeloma are distinct. However, no specific assessment tool has been developed for matching the needs and unmet needs of family caregivers of patients with multiple myeloma.

Our study sought to develop an instrument that could both survey the degree of need of caregivers of patients with multiple myeloma and investigate their level of supply. We also evaluated the validity and reliability of the proposed instrument. By elucidating the differences between the two, we could identify the degree of unmet needs, which can help medical staff recognize service shortcomings and offer references for targeted service measures to meet demand.

Methods

Design

Our research focused on instrument development and cross-sectional validation to progress the supportive care needs and supply matching questionnaire for family caregivers of patients with multiple myeloma. The study involved the two main steps of instrument development and psychometric tests.

Instrument development

Item generation

The supportive care needs of cancer patients and their family members are composed of seven dimensions, namely, practical, spiritual, social, psychological, information, emotional, and physiological needs [ 14 ]. In addition, caregivers of cancer patients have four supportive needs (health service, psychological and emotional support, work and social support, and information needs) [ 18 ]. Particularly for caregivers of hematologic malignancy patients in China, researchers have identified psychological, information, economic, and social support needs [ 21 ].

Therefore, we divided the possible supportive needs of family caregivers of patients with multiple myeloma into four dimensions: disease information, care skills, psychological and emotional, and social support needs. Two sources guided the selection of the initial items of the instrument: an exhaustive literature review of supportive care needs for family caregivers of patients with multiple myeloma, and the findings of semi-structured interviews conducted with 12 family caregivers.

For the exhaustive literature review, we sought articles that published in international databases, namely, PubMed, Science Direct, and Web of Science, and three Chinese databases, namely, CNKI, WANGFANG DATA, and VIP, by combining the following keywords and Boolean operators: “(cancer OR tumor OR malignant blood disease OR hematological malignancy OR multiple myeloma) AND (caregiver) AND (need OR assessment tool OR scale OR questionnaire).” This was a non-systematic review aimed at identifying relevant domains and items to inform the initial item pool. The inclusion criteria were as follows: articles related to the caregiver need scale for cancer patients published in Chinese and English. We did not limit the type of study. Articles were excluded if the assessment tool was developed specifically for a non-family caregiver population, or if the study sample and results did not pertain to family caregivers at all.

For the semi-structured interviews, we enrolled 12 family caregivers of patients with multiple myeloma (average age = 47.67 ± 8.82 years) from the hematology department of a large tertiary hospital in Fuzhou, China using purposive sampling. The inclusion criteria were as follows: relatives of patients (e.g., spouses, parents, children, siblings) undertaking the main care tasks; if a patient had more than one caregiver, the patient designated a participant; 18 years of age or older; understood the disease diagnosis, condition, and treatment of patients; had no communication difficulties; willing to describe their true experience. The exclusion criteria were current or past psychological problems and a history of consciousness disorder, dementia, or mental illness. The major interview questions were as follows: What did you and your family feel after the diagnosis? What needs do you and your family have in the process of taking care of the patient? Have you sought help with these needs? What are the channels for help? What life changes have you and your family made since the patient’s illness diagnosis? In what ways can the hospital help you and your family? We then used qualitative content analysis to analyze the collected interview data.

Content validity test

Six medical specialists and nine nursing experts evaluated the content relevance, clarity, and language appropriateness of the initial questionnaire items. The content validity index (CVI) was used to test the content validity of the initial items, which was computed based on the importance score of the items in expert consultation. The scoring standard was a five-point Likert scale that ranged from 5 = very important to 1 = very unimportant . We individually computed the item-level CVIs (I-CVI) and scale-level CVI (S-CVI) using I-CVI > 0.78 and S-CVI ≥ 0.90 as the evaluation criteria [ 22 ].

Testing of psychometric properties

Study participants

Family caregivers of patients with multiple myeloma were recruited from the hematology department of a tertiary hospital in Fuzhou by convenience sampling. The inclusion and exclusion criteria were the same as those for the interviews. We adhered to the guideline of the sample size being at least 5 to 10 times the number of items [ 23 ]. We also considered a 10% loss to the follow-up rate. As the draft questionnaire consisted of 29 items, we intended to recruit 160–319 participants (29 × 5 × 1.1–29 × 10 × 1.1). A total of 187 participants were recruited for the exploratory factor analysis (EFA), of whom 156 completed the questionnaire and comprised the eventual final sample used for the analyses (Sample 1). Sample size was required for confirmatory factor analysis (CFA); we needed to reach more than 200 cases. Of the 221 participants included in the CFA, 204 provided valid questionnaires (Sample 2). Parts of the sample were lost because of incomplete questionnaire data and subsequently excluded from the data analysis.

Data collection

This study was approved by the Ethics Committee on Biomedical Research of Fujian Medical University (IRB Ref No: 2017/49). After obtaining additional administrative permission from the head of the hematology department] we recruited participants. The researcher who acted as the data collector was the head nurse of the hematology department, was engaged in clinical work in the hematology department for many years, and had mastered relevant knowledge and communication skills. Information about this study was explained to the recruited participants, including its purpose and significance, the right of participants to refuse or opt out at any time, the confidentiality of personal information, and the risks and benefits. All participants were required to complete an informed consent form on prior to being accepted into the study, which was available in paper and electronic versions and was sent out on-site or by mobile phone. The questionnaires were recovered on the spot and checked for omissions and errors.

Measures

We designed a sociodemographic questionnaire to collect data on the general characteristics of the family caregivers of patients with multiple myeloma. The preliminary draft of the supportive care needs and supply matching questionnaire was developed after three rounds of expert consultation. Each item was scored in two aspects, namely, “what you need” (needs) and “what you get” (supply), using a five-point Likert-type response format, ranging from 1 ( not needed or not provided ) to 5 ( very needed or often provided ), with higher scores indicating higher needs or supply of supportive care for family caregivers of patients with multiple myeloma. All items were scored in positive.

The questionnaire yields paired scores for each item, subscale, and the total scale: a ‘Needs Score’ (perceived importance of the support) and a ‘Supply Score’ (perceived extent of receipt). A ‘Need-Supply Gap’ can be calculated by subtracting the Supply Score from the Needs Score for each item or aggregate level. A positive gap indicates an unmet need, with larger values signifying greater disparity. Clinically, a profile showing high need but low supply would be prioritized for intervention.

Data analysis

The data were analyzed using Excel 2007, IBM SPSS Statistics for Windows, version 24.0, and AMOS version 24.0. Descriptive statistics were used to represent the general characteristics of the participants by number and frequency (%). Specific validity and reliability tests were performed as follows.

For item analysis, we used critical ratio, Pearson correlation, and homogeneity test (corrected item-to-total correlations, commonality, and factor load). The critical ratio involved ranking the sum of the questionnaire needs scores of the participants and dividing the top 27% and bottom 27%. An independent samples t -test was conducted for the two groups, and the items with P > 0.05 were deleted. The items with a correlation coefficient lower than 0.4, corrected item-total correlations lower than 0.4, commonality values lower than 0.2, and factor loadings lower than 0.45 were deleted [ 24 ].

For the cross-validation of construct validity, we collected data from two populations. Sample 1 was used for EFA, and sample 2 was used for CFA. Before EFA, it was necessary to determine that the data were suitable for factor analysis. We used Kaiser–Meyer–Olkin (KMO) index and Bartlett’s sphericity test were applied. Principal component analysis (PCA) with drect oblimin oblique rotation was used for EFA to account for potential correlations among factors. An eigenvalue of 1.00 or more and a cumulative contribution rate of 70% or more were the criteria for extracting appropriate common factors. Factor loadings were regarded as significant when they exceeded 0.40.

We estimated the model fit indices for the CFA based on the model extracted from the EFA. We used the following indicators to evaluate the model fit (with the acceptance criteria within brackets). For absolute fit indices, we used the following: goodness of fit index (GFI > 0.85), adjusted goodness of fit index (AGFI > 0.85), and root mean square error of approximation (RMSEA < 0.05 = good fit and < 0.08 = reasonable fit). For incremental fit indices, we used the normed c 2 (c 2 /df < 3.00), normed fit index (NFI > 0.85), incremental fit index (IFI > 0.85), Tucker–Lewis index (TLI > 0.85), and comparative fit index (CFI > 0.85) [ 25 , 26 ].

Test-retest reliability was assessed with a subset of 30 participants, with a two-week interval between administrations. Test-retest reliability was assessed using a two-way mixed-effects model for absolute agreement, calculating Intraclass Correlation Coefficients (ICCs) [ 27 ]. The ICC for the total needs sub-questionnaire score was 0.877 (95% CI: 0.828–0.914), and for the total supply sub-questionnaire score was 0.803 (95% CI: 0.735–0.857). The ICCs for the four dimensions ranged from 0.752 to 0.865, indicating excellent stability.

For internal consistency, the Cronbach’s alpha was computed to test how consistently the items in the questionnaire measured the intended construct. Our criterion was a value higher than 0.70 [ 28 ].

For split-half reliability, We randomly divided all questionnaire items into two groups, each containing the same number of items, and then calculated the correlation coefficient between the two groups. Spearman-Brown coefficients were above 0.70, indicating good reliability [ 29 ].

Results

Instrument development

Item generation

By contrasting and analyzing the results that emerged from the literature review and interview sources, we identified the four dimensions of supportive care needs and supply matching questionnaires for family caregivers of patients with multiple myeloma. A total of 22 items were selected by referring to the theoretical framework of supportive care [ 14 ] and the published caregiver needs scale for cancer patients [ 18 ], and then combining the disease and treatment characteristics of multiple myeloma. Ten items were developed based on the interview results. These 32 items formed the initial questionnaire (Table 1 ), which had needs and supply sub-questionnaires.

Content validity test

We revised some items according to the opinions of the experts. C2, C3, C5, and D6 were deleted. D2 and D3 were merged, and A4, A6, D1, and D5 were modified to improve comprehension, clarity, and relevance. Item D4 was reworded for clarity based on expert feedback. D4 was changed to “Provide accurate contact information of the medical and nursing team, to facilitate timely contact with medical and nursing staff when necessary.” Despite factor loadings near the 0.4 threshold in the initial EFA, items A10 and D5 were retained due to their consistent emergence as salient needs in our qualitative interviews with MM caregivers. After content validation, the preliminary questionnaire was formed, including 29 items in four dimensions. The I-CVIs of the overall items ranged from 0.93 to 1.00, and the S-CVI was 0.998.

Psychometric tests

Participant characteristics

Table 2 provides the demographic characteristics of the caregivers who participated in our study.

Item analysis

We noted a statistical significance in the scores of the high (top 27%) and low groups (bottom 27%) of the needs and supply sub-questionnaires ( P < 0.05). The correlation coefficient between each item of the needs sub-questionnaire and total score of the questionnaire ranged from 0.570 to 0.790; for the supply sub-questionnaire, the range was from 0.689 to 0.901. The corrected item-total correlation coefficients of the 29 items in the needs and supply sub-questionnaires ranged from 0.536 to 0.767 and from 0.662 to 0.892, respectively. The commonality value ranged from 0.410 to 0.806 and from 0.539 to 0.858 in the needs and supply sub-questionnaires, respectively. The factor loading ranged from 0.574 to 0.781 and from 0.677 to 0.903 in the needs and supply sub-questionnaires, respectively. After the item analysis, we retained all 29 items of this questionnaire.

Construct validity test

In the EFA, we performed PCA using the 29 items of the needs sub-questionnaire. The KMO index (0.923) was calculated and a Bartlett test of sphericity (χ2 = 4210.689, P < 0.001) was conducted to confirm that sample 1 ( n = 156) was suitable for factor analysis. PCA with 29 items extracted four factors with eigenvalues of 1.00 or greater; these components accounted for the cumulative variance explained of 70.160%. Through the drect oblimin oblique rotation, we found that the 29 items had a large load (0.488 to 0.915) on each common factor, which could better explain the original questionnaire structure. The dimensions of some items were changed. A10 and A11 were adjusted to the fourth dimension, whereas D1 and D2 were adjusted to the third dimension. The third and fourth dimensions were renamed “psychosocial” and “medical service,” respectively, according to the content of the adjusted items (Table 3 ).

Considering that supply was feedback under the premise of needs, we performed the EFA of the supply sub-questionnaire under the factor matrix results of the needs sub-questionnaire after suggestions from statistical experts and discussion within the research group. The KMO index of the corresponding items in each dimension ranged from 0.802 to 0.931. Bartlett’s test of sphericity, χ 2 = 482.824–2034.690, P < 0.001. The factor loading was 0.723 to 0.939. (Table 3 )

Next, we conducted CFA with sample 2 ( n = 204) to assess the factor structure. For the needs sub-questionnaire, the model fitting results were found to be reasonable (RMSEA = 0.065, c 2 /df = 1.846, NFI = 0.883, IFI = 0.943, TLI = 0.931, CFI = 0.942), except for GFI (0.833) and AGFI (0.787). The results of the convergent validity analysis demonstrated that the standardized item loadings onto the factors ranged from 0.45 to 0.91 (Fig. 1 ).

For the supply sub-questionnaire, the model fitting results were similar to those of the needs sub-questionnaire. Except for GFI (0.807) and AGFI (0.756), the indicators were all within the standard range (RMSEA = 0.075, c 2 /df = 2.136, NFI = 0.867, IFI = 0.925, TLI = 0.910, CFI = 0.924). The results of the convergent validity analysis demonstrated that the standardized item loading onto the factors ranged from 0.42 to 0.95 (Fig. 2 ).

Test-retest reliability

The ICC for the total needs sub-questionnaire score was 0.877 (95% CI: 0.828–0.914), and for the total supply sub-questionnaire score was 0.803 (95% CI: 0.735–0.857). The ICCs for the four dimensions ranged from 0.752 to 0.865, indicating excellent stability.

Internal consistency

The Cronbach’s α of the needs sub-questionnaire was 0.962, and the coefficients for the four dimensions ranged from 0.863 to 0.937. The Cronbach’s α of the supply sub-questionnaire was 0.981, and the coefficients for dimensions ranged from 0.913 to 0.972 (Table 4 ).

Split-half reliability

For the needs sub-questionnaire, the correlation coefficient of the total score between the two parts was 0.845 and that of the four dimensions ranged from 0.712 to 0.890. For the supply sub-questionnaire, the correlation coefficient of the total score was 0.914 and that of the four dimensions ranged from 0.793 to 0.927.

Score distributions

Descriptive statistics for the needs and supply sub-questionnaire scores are presented in Table 5 . The total needs score ranged from 29 to 145, with a mean of 126.74 (SD = 17.76). The total supply score ranged from 29 to 145, with a mean of 97.17 (SD = 29.91). Distributions for all subscales were approximately normal.

Discussion

The burden and unmet supportive care needs of family caregivers of patients with multiple myeloma are increasingly recognized as critical components of comprehensive cancer care [ 9 ]. While existing research has effectively quantified their caregiver burden and general needs [ 30 , 31 ], a deeper qualitative understanding of their specific lived experiences remains less explored [ 6 ].

Selecting an appropriate instrument for assessing supportive care needs is a prerequisite for effective needs investigation by healthcare providers. However, a significant limitation of many existing tools is their focus solely on the degree of need, frequently overlooking the crucial dimension of whether and to what extent these needs are currently being met. This omission makes it difficult to identify the precise gap representing unmet needs, thereby limiting the ability to inform targeted interventions. Our study aimed to address this gap by developing and validating a dual-scale questionnaire specifically for MM family caregivers. The Supportive Care Needs and Supply Matching Questionnaire (SCNS-SM-MM) is designed to assess both the level of need and the level of service provision simultaneously, enabling a direct calculation of unmet needs.

Validity is the degree to which a new instrument can accurately measure the same structure. It can ensure that different researchers have a consistent understanding of the meaning and connotation of a certain research variable [ 32 ]. We used construct and content validity testing in this study. Of the EFA results for the construct validity tests, the load of all items in the questionnaire was greater than 0.4, and no multiple loads emerged. Our evaluation questionnaire included two parts—the needs and supply sub-questionnaires. Four common factors were extracted from the needs sub-questionnaire, which was consistent with our assumption at the stage of item development.

The purpose of this study was to conduct a one-to-one comparative analysis of the difference between the needs and supply of family caregivers of patients with multiple myeloma. After discussion by the research team, we conducted a dimensional factor analysis in our EFA of the supply sub-questionnaire, according to the results of the needs sub-questionnaire factor matrix. The cumulative variance contribution rate and factor load of each dimension were higher than the standard (cumulative variance contribution rate of common cause, > 40%; factor load, > 0.4) [ 23 ]. A similar analysis method has been reported [ 33 ]. We carried out three rounds of expert consultation to revise the draft questionnaire, ultimately reducing the number of items in the questionnaire from 32 to 29. The questionnaire items did not change after item and exploratory factor analyses. The content validity result of our report was derived from the item importance assessment of the third round of expert consultation evaluation. Both I-CVI and S-CVI exceeded 0.8 [ 34 ], indicating the satisfactory content validity of the questionnaire.

Most of the psychometric test indicators in our study met the standard thresholds (for CFA: χ²/df < 3.00, RMSEA < 0.08, CFI > 0.90, TLI > 0.90). Notably, in the CFA model fitting for construct validity, the two goodness-of-fit indexes (GFI and AGFI) were slightly below their respective reference values (GFI > 0.85, AGFI > 0.85). Nevertheless, cut-off values for model fitting are not necessarily absolute, as using reference values for model fitting as the only criterion may lead to the false rejection of acceptable models [ 35 ]. We believe that the theoretical model matches the actual survey data of the questionnaire, and has good model fit and construct validity.

Reliability reflects the degree of trustworthiness of tool measurement results. We confirmed the test-retest reliability, internal consistency, and split-half reliability of the new questionnaire. Test-retest reliability refers to the stability of results measured by tools over time [ 36 ]. The correlation coefficients of the two measurements of the needs sub-questionnaire and each dimension were all above 0.75, the criterion of the test-retest reliability. Two dimensions of the supply sub-questionnaire did not reach but were very close to 0.75 [ 37 ]. Thus, the questionnaire satisfied the requirement and had cross-time stability. In terms of internal consistency, the Cronbach’s α of the two sub-questionnaires and each dimension exceeded 0.85. Regarding split-half reliability, both sub-questionnaires showed a high level of reliability. As such, the questionnaire accurately measured the same underlying latent trait for each item.

To summarize, our questionnaire was confirmed to be suitable for investigating the supportive needs of family caregivers of patients with multiple myeloma, as well as the supply of such needs. It can be adopted by medical institutions and filled out by caregivers themselves. The questionnaire can be used to assess changes in caregiver needs and supply satisfaction for a patient’s illness. Health education and other services may then be adjusted according to the identified demand and supply. Compared with other tools, the questionnaire we developed is specific in content and system. While the factor structure showed good overall fit, the interpretation of the psychosocial and medical service subscales should consider the specific MM-caregiver context from which the items were generated. From the perspective of matching needs and supply, our questionnaire was designed to combine the supportive needs of family caregivers of patients with multiple myeloma.

Nevertheless, our study had several limitations. For one, we could only investigate family caregivers of patients with multiple myeloma in the hematology department of a tertiary hospital in Fuzhou, China. Another limitation was that the EFA and CFA results were from data provided by the same research center. Therefore, the generalizability of the questionnaire may be partially affected. In future research, our questionnaire can be used for multi-center and large-sample investigation to increase its applicability and popularization. Furthermore, this study did not formally assess the concurrent validity of the questionnaire against established, general cancer caregiver needs instruments. This limits the direct comparison of our disease-specific tool with broader measures at this stage.

Conclusion

We developed and verified the Supportive Care Needs and Supply Matching Questionnaire for Family Caregivers of Patients with multiple myeloma multiple myeloma, containing 29 items across four dimensions (including disease information, care skills, psychological and emotional, medical service) scored on a five-point Likert-type response format. The questionnaire exhibited good psychometric properties on two validity indicators and three reliability indicators.

This study focuses on the vital role of family caregivers in the treatment and rehabilitation of patients with multiple myeloma, whose unmet needs for supportive care have long been neglected. The questionnaire can be used to evaluate and match the needs and supply of supportive care for family caregivers of patients with multiple myeloma. It can also help healthcare professionals identify service weaknesses, narrow the gap between supply and needs, and reflect the service characteristics of family therapy for patients with multiple myeloma.

In future studies, supportive nursing intervention programs could be developed for nurses according to the questionnaire evaluation results, the questionnaire developed in this study can be used to conduct surveys before and after intervention, and the application of the questionnaire as an evaluation indicator can be further discussed.

Implications for nursing

For nursing practice, this questionnaire provides a structured and quantifiable tool to systematically assess the supportive care needs of family caregivers and the extent to which these needs are currently met. By identifying specific areas of unmet need, nurses can develop targeted, personalized support plans. The tool can facilitate communication between nurses and caregivers, ensuring that supportive interventions are aligned with caregivers’ prioritized needs and thereby potentially reducing caregiver burden and improving the quality of care delivered to patients.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1

Acknowledgements

We would like to thank all participants for their time and feedback. The authors would also like to thank Chunfeng Wang for revising the manuscript.

Abbreviations

Adjusted Goodness of Fit Index

Confirmatory Factor Analysis

Comparative Fit Index

Content Validity Index

Exploratory Factor Analysis

Goodness of Fit Index

Item-level CVIs

Incremental Fit Index

Kaiser–Meyer–Olkin

Multiple Myeloma

Normed Fit Index

Principal Component Analysis

Root Mean Square Error of Approximation

Scale-level CVI

Tucker–Lewis Index

Author contributions

Yanfang Lin: Conceptualization, methodology, data curation, formal analysis, project administration, writing-original draft, writing-review & editing. Yidan Yang: Data curation, formal analysis, writing original draft, writing-review & editing. Wenkui Xu: Methodology, data curation, writing-review & editing. Chunrong Chen: Data curation. Yong Wu: Resources, project administration. Rong Hu: Conceptualization, methodology, supervision, project administration, writing-review & editing.

Funding

This study was supported by the Science and Technology Innovation Joint Fund Project of Fujian Province (grant no. 2019Y9029).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was performed according to current bioethical principles and approved by the Ethics Committee on Biomedical Research of Fujian Medical University on September 29, 2017 (IRB Ref No: 2017/49) and was carried out in strict accordance with the World Medical Association Declaration of Helsinki. All participants provided written informed consent before the research. Participants were informed that they could refuse to answer the questions or withdraw from the study at any time. The information of the participants was anonymized.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yanfang Lin and Yidan Yang contributed equally to this work.

Contributor Information

Yong Wu, Email: wuyong9195@126.com.

Rong Hu, Email: ronghu1246@fjmu.edu.cn.

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Associated Data

Supplementary Materials

Supplementary Material 1

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.