You are viewing the site in preview mode

Skip to main content
Download PDF

Care needs profiles of Crohn’s disease patients and their associations with symptom clusters, post-traumatic growth, and family function: a latent profile analysis

BMC Gastroenterology volume 25, Article number: 351 (2025) Cite this article

Abstract

Background and aims

The care needs of patients with Crohn’s disease (CD) may be heterogeneous. This study aimed to explore the latent class of care needs of patients with CD and differences in their characteristics and to analyze the factors influencing the different latent classes.

Methods

A convenience sampling method was used to select 250 patients with CD who attended a tertiary-level hospital in Nanjing from August to November 2024 for the study. They were surveyed via the General Information Questionnaire, the Crohn’s Disease Care Needs Scale (CD-CNS), the Inflammatory Bowel Disease (IBD) Patient Symptom Clusters Assessment Scale, the Family Adaptability and Cohesion Scale (FACES), and the Post-traumatic Growth Inventory (PTGI). The latent classes of care needs of CD patients were identified via latent profile analysis (LPA), and the factors influencing their latent classes were analyzed via multiple logistic regression analyses.

Results

(1) The LPA results revealed that the care needs of CD patients were divided into three profiles as the best model fitting indicators: the “low-care-needs-adaptation group” (n = 96, 38.4%), the “moderate-care-needs-growth group” (n = 81, 32.4%), and the “high-care-needs-distress group” (n = 73, 29.2%). (2) Regression analyses revealed that current disease status, the presence of a stoma, symptom burden, family adaptability and cohesion, and post-traumatic growth (PTG) were influential factors in different latent classes.

Conclusion

There is significant heterogeneity in the care needs of CD patients. Care needs to focus on patients with high care needs and enhance their symptom management and psychological interventions to improve their PTG and reduce their disease burden.

Peer Review reports

Introduction

Crohn’s disease (CD) is a chronic nonspecific intestinal inflammatory disease with unclear etiology and pathogenesis [1]. In recent years, the incidence of CD has been increasing globally [2], and China, as an Asian country with a high incidence of CD [3], has an average annual incidence rate of approximately 1.22 per 100,000 people [4], with the rate still increasing. The disease is recurrent and incurable [5], and long-term maintenance treatment places an enormous economic burden on patients [6], while symptoms such as chronic diarrhea, abdominal pain, and fatigue can seriously affect patients’ work, life, and socialization [7]. Under the combined effects of various factors, CD patients generally have a large psychological burden [8], and both the body and mind are in a state of high demand.

Care needs refer to all kinds of help and services that patients need to be provided in the process of disease diagnosis, treatment, and follow-up, including physiological, informational, emotional, psychological, and social aspects [9]. Focusing on care needs during an illness can help individuals cope better with their illness [10]. Research [11–12] has shown the existence of numerous unmet needs in people with CD. For example, a systematic review revealed that patients with CD have numerous informational, medical, and psychological needs at different stages across their lifespan and urgently require personalized supportive care interventions from professionals [13]. However, providing individualized supportive care to patients is premised on an accurate assessment of each patient’s needs. Previous widely used tools for assessing care needs are only applicable to cancer patients, such as the 34-item Supportive Care Needs Survey (SCNS-SF34) [14], and there is a lack of appropriate tools to measure the care needs of patients with CD. The Crohn’s Disease Care Needs Scale (CD-CNS), a specific scale for assessing the care needs of CD patients, was previously developed by our research team through a systematic literature review, qualitative interviews, and the Delphi method [15]. CD-CNS reliability and validity have been demonstrated in evaluations and were determined to be suitable for assessing the care needs of CD patients in a Chinese clinical research setting [15]. Therefore, the CD-CNS was used in this study to assess the care needs of patients with CD.

In addition, previous research on CD care needs has been limited to the use of high and low scores on scales to determine individuals’ level of need [16], a variable-centered approach that ignores the heterogeneity of individuals at different levels. In contrast, latent profile analysis (LPA) is an individual-centered statistical method that explores the underlying group structure and thus identifies groups with different characteristics, allowing subgroup classification based on different characteristics of variables [17]. This approach allows for the identification of CD patients with different characteristics, thus enabling the provision of more targeted care needs. Compared with cluster and factor analyses, it is more accurate, objective, flexible, and comprehensive [18–19].

Furthermore, few existing studies have assessed the care needs of people with CD at multiple levels, including patients’ physical and mental health and family. Social-ecological theory [20] states that changing only the intrinsic level of an individual has a limited effect on maintaining long-term health behaviors and that multiple levels of intervention together are the most effective way to change health behaviors. Specifically, the care needs of people with CD may be influenced by both the individual level (e.g., sociodemographic, disease-related, and psychological factors) and the interpersonal level (e.g., family factors). However, the previous studies on psychological factors of care needs mostly focused on negative aspects [21], and positive studies were scarce. With the rise of positive psychology, studies have found that patients with chronic diseases will also experience positive psychological changes through complex cognitive adjustments after struggling with traumatic events such as diseases, which in turn promotes them to adopt a positive attitude to re-understand themselves and deal with diseases and focus on physiological, psychological, and social needs to reshape their lives [22, 23]. The CD is undoubtedly a traumatic event for patients, and it may also have an impact on their physical and psychological needs. Therefore, this study explored the latent classes of care needs of patients with CD based on LPA and analyzed their influencing factors at multiple levels concerning socioecological theories to inform the development of precise care intervention plans.

Methods

Study design and participants

This study had a cross-sectional research design. The convenience sampling method was used to select CD patients who attended a gastroenterology treatment center in a tertiary-level A hospital in Nanjing city from August to November 2024.

The inclusion criteria were as follows: (1) Age ≥ 18 years; (2) Meet the diagnostic criteria for CD in the Consensus Opinion on the Diagnosis and Treatment of Inflammatory Bowel Disease (Beijing 2018) [1]; and (3) Primary school education and above, and be able to understand the questionnaire correctly.

The exclusion criteria were as follows: (1) Patients with mental illness or taking psychotropic drugs; and (2) Patients with severe comorbidities, such as organ insufficiency or malignant tumors.

Sample size of the study

According to Kendal’s [24] sample size estimation method, the sample size is 5–10 times the number of variables. The total number of variable factors in this study is 24. The sample size should be between 120 and 240 cases, and the sample size of the included cases should be at least 144 cases or more, accounting for 20% of invalid questionnaires. To ensure the accuracy of the model and test its efficacy [25], 250 CD patients were ultimately included.

Ethical considerations and consent to participate

This study followed the Declaration of Helsinki and was approved by the ethics committee of Nanjing Second Hospital (No. 2023-LS-Ky-022). All study subjects gave informed consent and voluntarily participated in this study. In addition, this study was an anonymous survey, did not involve unethical behavior, and did not cause adverse health consequences to the participants’ physical or mental health.

Measures

General information questionnaire

A self-designed general information questionnaire was used to collect data on sociodemographics and disease characteristics.

CD-CNS

The CD-CNS was used to assess the needs of patients. This scale was developed by Chen [15] in 2024 to assess the care needs of patients with CD. The scale consists of 27 items in five dimensions: medical needs (6 items), information needs (5 items), physical needs (7 items), psychological needs (5 items), and external support needs (4 items). Responses were rated on a 5-point Likert response scale (1 = not applicable, 2 = satisfied, 3 = low need, 4 = moderate need, and 5 = high need). The overall Cronbach’s alpha coefficient for the CD-CNS was 0.940 [15]. The Cronbach’s alpha for this scale in this study was 0.939.

Inflammatory bowel disease (IBD) patient symptom clusters assessment scale

This scale was used to assess symptom burden in patients with CD. The scale was developed by Gu [26] in 2020 to assess the symptoms of patients with CD. The scale consists of five dimensions, namely, the abdominal symptom cluster (3 items), intestinal symptom cluster (5 items), nutritional symptom cluster (3 items), systemic symptom cluster (4 items), and psychiatric-psychological symptom cluster (3 items), for a total of 18 entries, in which each of the entries includes 3 modules of frequency of occurrence, severity, and degree of distress and is based on a 5-point Likert scale according to the symptoms of patients with IBD. When the score ranges from 1 to 5, the higher the score is, the more severe the symptoms of IBD patients. The total Cronbach’s alpha coefficient for this scale was 0.856 [26]. The Cronbach’s alpha in this study was 0.883.

Family adaptability and cohesion scales, second edition (FACES II)

The FACES II was used to assess patients’ family function. The scale was developed by Oison et al. [27]. And translated and validated in Chinese by Fei et al. [28]. The scale consists of 30 items, including 2 subscales of cohesion (16 items) and adaptability (14 items). The scale is scored on a 5-point Likert scale ranging from 1 to 5, from “not” to “always”; the higher the score is, the better the family cohesion and adaptability. The Cronbach’s alpha coefficients for the FACES II ranged from 0.68 to 0.85 [28]. The Cronbach’s alpha of this scale in this study was 0.895.

Post-traumatic growth inventory (PTGI)

The PTGI was used to assess post-traumatic growth (PTG) in patients. The scale was developed by Tedeschi [29] and translated and validated in Chinese by Wang [30]. The scale includes five dimensions—life perception, personal strength, new possibilities, relationships with others, and self-transformation—with 20 items, each of which is scored on a 6-point Likert scale, with 0, 1, 2, 3, 4, and 5 representing not at all, very little, few, some, many, and very much, respectively, and a total score of 100 points; higher scores indicate higher levels of PTG. The overall Cronbach’s alpha coefficient for the PTGI is 0.874 [30]. The Cronbach’s alpha for this scale in this study was 0.966.

Harvey-Bradshaw index (HBI)

IBD disease activity was assessed via the Harvey-Bradshaw Index in patients with Crohn’s disease with HBI scores > 5, which is considered an active disease [31]. This scoring system consists of five items: general condition, abdominal pain, abdominal mass, diarrhea, and concomitant symptoms.

Data collection

The questionnaire for this study was distributed and collected by the researcher. Before the survey, patients were informed of the purpose and significance of the study and the requirements for questionnaire completion via uniform instructions, and an informed consent form was signed by the patients after their consent was obtained. During the survey, the questionnaire was filled out independently by the patients, and when the patients had questions about the questionnaire expression, the researcher answered them via a unified statement. After the survey, the paper questionnaires were collected on-site. After collection, two researchers performed a rigorous screening to exclude any questionnaires that contained logical errors, patterned responses, or incomplete fields.

Data analysis

In the first step, this study employed SPSS 27.0 for descriptive data analysis and a common method bias test. Qualitative data are described using n (%). The quantitative data obey the normal distribution by ( x ± s ), and the non-normal distribution by M (Q1, Q3).

In the second step, Mplus 8.3 was used for LPA. The fit indicators included (1) the Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample size-adjusted BIC (aBIC), with smaller values. A smaller value corresponds to a better model fit. (2) A closer entropy to 1 indicates that the model classification is more accurate when entropy ≧ 0.8, which indicates that the classification accuracy is greater than 90%. (3) The Lo‒Mendell‒Rubin (LMR) and bootstrap likelihood ratio test (BLRT) results when P < 0.05 indicate that the k - class model fits better than the k − 1 class model [32].

The third step is to compare qualitative data between groups by the χ2 test, for quantitative data with non-normal distribution, pairwise comparisons between multiple groups of data were performed by the Kruskal-Wallis test and Bonferroni correction.

Finally, multivariate logistic regression analysis was used to analyze the influencing factors of profile categories, with profile categories as dependent variables, meaningful categorical variables in univariate analysis as factors, and continuous variables as covariates. The difference was statistically significant with P < 0.05. To make the multivariate analysis results more intuitive, we constructed the forest plot using R version 4.3. 3.

Results

Care needs scale scores of CD patients, sociodemographic characteristics, and disease information

A total of 259 questionnaires were distributed and returned in this study, 9 invalid questionnaires were excluded, and the recovery rate of valid questionnaires was 96.5%. The total CD-CNS score was (74.28 ± 23.96), which included medical needs (18.54 ± 6.69), information needs (17.46 ± 5.62), physical needs (18.04 ± 7.69), psychological needs (9.71 ± 5.39), and external support needs (10.54 ± 5.28). In this survey, the ages of 250 patients with CD ranged from 18 to 73 years, with a mean age of 36.60 ± 12.08 years. Of these, the majority (64.4%) were under 40 years of age, 71.2% of the patients had high a school education level or above, most of the patients (61.6%) were male, more than half (50.4%) were currently unemployed, most (67.2%) had CD intestinal surgery, more than half (80%) were treated with biological agents, 36% were in the active disease stage, and 51.6% needed gastrointestinal nutritional support. Baseline characteristics of patients with CD are presented in Table 1.

Table 1 Descriptive statistics for sociodemographic and disease information (n = 250)
Full size table

Results of the common method bias test

This study was self-reported by patients, which may lead to common method bias. The common method bias test was performed via the Harman one-way method, and the results revealed that there were 20 factors with eigenvalues > 1 and that the variance contribution rate of the first factor was 30.876% (< 40% of the recommended standard), suggesting that there was no serious common method bias, which indicates that the observed variable relationship can reflect the real theoretical correlation, and the variation of data is not the systematic bias caused by the measurement method itself.

Results of LPA of CD patients’ care needs

In this study, the five dimensions of the CD-CNS were used as exogenous variables, and the number of model classes was increased sequentially starting from a single-class model to obtain the model of latent profiles from 1 to 5 classes; the fitting results are shown in Table 2. With the increase in the number of model classes, the values of Log L, AIC, BIC, and aBIC decreased continuously, but when the number of classes was 3, the entropy was greater; the difference was statistically significant, with P < 0.01 for LMR and BLRT. Whereas the BLRT and LMR for the category 4 and 5 models showed non-significant p-values ( P > 0.05) and did not provide statistically better fits, the entropy for the category 3 (0.082) model was greater than that for category 2 (0.868 ), suggesting that the category 3 categorization was more accurate. In a comprehensive comparison, the category 3 model was identified as the best latent profile model in this study. In addition, the average probabilities of class attribution of the category 3 model were 95.6%, 93.0%, and 95.7%, suggesting that the accuracy of category attribution was high and that the results were credible.

Table 2 Potential classes of care needs among patients with CD
Full size table

Based on the model determination, the mean values of each category on the 5 dimensions of CD-CNS were plotted to create a distribution of category features in Fig. 1, and the 3 classes were named according to the fluctuations in the mean values of the entry scores. Class 1 mainly comprises patients in remission (93.8%). The CD-CNS score is (50.77 ± 10.93) points. The average score of each item is 1.5 to 2.3 points. The score is low, indicating that this type of patient can adapt to the physiological, psychological, social, and other effects of the disease, so it is named the “low-care-needs-adaptation group”. The CD-CNS score of the Class 2 is (77.68 ± 12. 98) points. Although the physiological needs score is higher than that of Class 1, the psychological needs are similar to those of C1, so it is named the “moderate-care-needs-growth group”. The CD-CNS score of Class 3 was (101.44 ± 11.95) points, of which 69.9% were in the active phase and 23.3% of patients had a stoma, reflecting multidimensional distress; Moreover, these patients have high needs scores in five dimensions, especially the physical and psychological needs are significantly higher than other categories, so they are named “high-care-needs-distress group”.

Fig. 1
figure 1

The characteristic distribution of 3 potential classes of care needs among patients with CD

Full size image

Univariate analysis of potential profile classes of care needs of CD patients

The results of the univariate analysis showed that the care needs of the 3 classes of patients were statistically significant (P < 0.05) in terms of monthly household income (χ2 = 12.993, P = 0.043), current work status (χ2 = 18.583, P = 0.004), disease status (χ2 = 74.520, P < 0.01), the purpose of admission (χ2 = 30.676, P < 0.01), complications (χ2 = 11.503, P < 0.01), nasal feeding tube (χ2 = 27.318, P < 0.01), stoma (χ2 = 16.733, P < 0.01) and current diet (χ2 = 35.080, P < 0.01). At the same time, compared with classes 1 and 2, patients in class 3 are more likely to be unemployed or frequently take sick leave, have lower monthly household income, and are more likely to have active disease, complications, stoma, and need nutritional support, as shown in Table 3.

The differences in the IBD symptom clusters assessment scale scores for Class 1, Class 2, and Class 3 were statistically significant (P < 0.05), and the differences in abdominal were not statistically significant except for Class 2 and Class 3 (P > 0.05), the rest were statistically significant; In intestinal, except for Class 1 and Class 2, the difference was not statistically significant (P > 0.05), and the rest were statistically significant; the differences in the scores of whole body, nutritional, psychosomatic, and other dimensions were statistically significant (P < 0.05). The differences in the family cohesion and adaptation scale scores of Class 1, Class 2, and Class 3 were statistically significant (P < 0.05). Among them, the scores of family cohesion, family adaptation, and other dimensions were statistically significant (P < 0.05). The differences in PTG scale scores Class 1, Class 2, and Class 3 were statistically significant (P < 0.05), among which the scores of life lessons, personal power, new possibilities, relationships with others, self-transformation, and other dimensions were statistically significant (P < 0.05), as shown in Table 4.

Table 3 Univariate analysis of potential classes of care needs among patients with CD
Full size table
Table 4 Comparison of scores on different dimensions of the family cohesion, adaptation, PTG and IBD symptom cluster scale across the three different models
Full size table

Results of multifactorial analysis of latent profile classes of care needs of CD patients

Multiple logistic regression analysis was performed with the latent profile classes of care needs of CD patients as the dependent variable and the variables that were statistically significant in the univariate analysis as the independent variables. The results of multivariate logistic regression analysis showed that: ① Comparison of the C1 and C3 groups, patients with disease activity, high symptom burden, poor family function, and low PTG were easily classified into the C3 group. Among them, the probability of active patients belonging to group C3 was higher than that in remission (OR = 0.130, P = 0.029); Patients with higher symptom burden had a higher probability of belonging to group C3 than patients with lower symptom burden (OR = 0.948, P < 0.01); Patients with poor family function had a higher probability of belonging to group C3 than patients with good family function (OR = 1.108, P < 0.01); Patients with low PTG had a higher probability of belonging to group C3 than patients with high PTG (OR = 1.042, P = 0.018). ② Comparison of the C2 and C3 groups, patients with no stoma, low symptom burden, good family function, and high PTG were easily classified into group C2. Among them, patients without stoma had a higher probability of belonging to group C2 than patients with stoma (OR = 0.232, P = 0.025); Patients with lower symptom burden had a higher probability of belonging to group C2 than patients with higher symptom burden (OR = 0.971, P < 0.01); Patients with good family functioning had a higher probability of belonging to group C2 than patients with poor family functioning (OR = 1.057, P = 0.016); Patients with high PTG had a higher probability of belonging to group C2 than patients with low PTG (OR = 1.032, P = 0.027). ③ Comparison of the C1 and C2 groups, patients with low symptom burden, good family function, and disease in remission were easily classified into the C1 group. Among them, patients in remission had a higher probability of belonging to group C1 than in the active phase (OR = 6.804, P = 0.022); Patients with lower symptom burden had higher probability of belonging to group C1 than patients with higher symptom burden (OR = 1.025, P = 0.023); Patients with good family functioning had a higher probability of belonging to group C1 than patients with poor family functioning (OR = 0.954, P = 0.01), See Table 5. To intuitively see the influencing factors of different potential classes of care needs, we added a forest diagram for visualization. See Figs. 2 and 3, and Fig. 4.

Table 5 Results of the multivariate logistic analysis of the factors influencing latent profiles associated with care needs in patients with CD
Full size table
Fig. 2
figure 2

Comparison of the results of multivariate analysis of Class 1 and Class 3 care needs

Full size image
Fig. 3
figure 3

Comparison of the results of multivariate analysis of Class 2 and Class 3 care needs

Full size image
Fig. 4
figure 4

Comparison of the results of multivariate analysis of Class 2 and Class 1 care needs

Full size image

Discussion

There is heterogeneity in the care needs of CD patients, and we need to pay attention to the high-care-needs-distress group

The results of this study show that the care needs of CD patients can be divided into three potential classes: the “low-care-needs-adaptation group”, the "moderate-care-needs-growth group” and the “high-care-needs-distress group”, suggesting that there is a pronounced heterogeneity in the care needs of CD patients, which further supplements the previous study [33–34] that the care needs of CD patients are regarded as a homogeneous whole, can better meet the differentiated needs of patients, and provide guidance for the formulation of targeted interventions in further research.

The high-care-needs-distress group accounted for 29.2% (73/250) of all CD patients, and patients in this class scored higher than the overall level on all CD-CNS dimensions. The reasons for this are as follows: (1) Patients are in the active stage of the disease and are in urgent need of medical support in the face of changes in their condition. (2) The high cost of medication and the risk of surgery creates some subjective and objective economic toxicity for patients and their families [6]. (3) Changes in self-image caused by changes in intestinal function and the uncertainty of treatment aggravate the psychological burden of patients [7]. According to Maslow’s hierarchy of needs theory, somatic function is the prerequisite for safeguarding physiological needs and the basis for realizing higher-level needs [35], which suggests that healthcare professionals need to focus on this group of patients, encourage active participation in treatment, strengthen symptom management, and guide them to seek management experience from patients who have better control of their diseases.

The moderate-care-needs-growth group accounted for 32.4% (81/250) of all CD patients, and patients in this class scored higher in information needs and lower in psychological needs. This suggests that patients in this class always remain hopeful in the face of disease distress and are eager to seek health information related to disease self-management, wanting to promote disease recovery through positive lifestyle adjustments. Health information needs refer to the needs of patients who are in a particular time or situation and recognize that the information they obtain is insufficient to achieve a goal [36]. Adequate information can reduce patients’ disease-related concerns [37]. The Healthy China 2030 Planning Outline explicitly proposes the promotion of Internet + Healthcare services to meet the needs of patients for personalized services and precision medicine [38]. These findings suggest that healthcare professionals can use Internet healthcare to provide patients with professional and targeted care services such as symptom monitoring, medication, diet, emotion, exercise, etc. A study [39] has demonstrated that a feedback-based health education model based on a cloud platform imparting knowledge of self-management of IBD patients, remote monitoring of disease symptoms, and guidance meets the needs of patients and improves their self-management skills.

The low-care-needs-adaptation group accounted for 38.4% (96/250) of all CD patients, and the lower scores of this class of patients on the dimensions of the CD-CNS may be related to the fact that this class of patients is in remission, with a lower burden of symptoms and a higher level of family function and psychology. This suggests that patients in this category can correctly understand their disease and actively adapt to the changes in their lives brought about by the disease; at the same time, the patient’s family members can provide the attentive care and financial and emotional support they need. Although the needs of this group of patients are low, the disease is long-lasting with recurrent episodes, so healthcare professionals still need to warn patients of the importance of long-term self-management and change the traditional misconception of “slow disease, slow treatment” to maintain a long-term low level of need.

Analysis of factors influencing different classes of care needs of CD patients

Differences in the characteristics of different classes of diseases

Disease active phase

The results of this study revealed that patients in the active phase were more likely to belong to the high-care-needs-distress group than those in the other two groups. This may be because, during the onset of the disease, the aggravation of symptoms can lead to sudden impairment of the patient’s physical function, which not only hurts the patient’s daily life and psychology but also increases the difficulty of treatment and the economic burden [40]. These findings suggest that healthcare professionals need to assess patients’ acceptance of symptoms promptly during the active period and provide appropriate interventions to promote disease relief and enable them to resume normal work and life. Second, positive psychological guidance is offered to patients, and research [41] shows that the presence of severe symptoms prompts patients to change their health behaviors. Patients realize that the present is a good time for symptom management, prompting them to set their mindset right and actively engage in disease management. In addition, single-disciplinary care makes it difficult to cope with the multiple needs CD patients face during the active period. With the progress of medical research, multidisciplinary combined therapy is gradually becoming a key direction of disease management. Taylor [42] used a nurse-led multidisciplinary nursing model, in which nurses and general practitioners provided personalized supportive care, and the unmet needs of lymphoma patients were reduced. Therefore, it can be applied to CD patients to alleviate negative emotions during the period and meet their diverse care needs during the active period.

Stomas

The results of this study showed that patients with stoma were more likely to belong to the high-care-needs-distress group than patients in the moderate-care-needs-growth group. Patients with stomas may suffer from disturbances in body image due to changes in body shape, and some of them may even suffer from psychological problems such as a sense of shame and a decrease in self-confidence [43]. Therefore, CD patients with stomas should be instructed to adopt appropriate self-emotion regulation methods, such as acceptance and commitment therapy, which is a psychotherapeutic model pioneered based on cognitive behavioral therapy, and its role in helping patients to enhance their positive emotions has been verified in the domestic IBD group, through which stoma patients can be helped to determine the meaning of life, improve their negative emotions, and enhance their self-identity [44].

Relationships between symptom burden and the care needs of CD patients

The results revealed differences in the level of symptom burden among the three groups of CD patients, with patients with greater symptom burdens being more likely to belong to the high-care-needs-distress group. This is similar to the findings of Wang [45]. These patients not only have gastrointestinal symptoms of diarrhea and abdominal pain due to the disease itself [46]. They may also be accompanied by systemic symptoms such as fatigue, sleep disturbances, weight loss, and psychological symptoms such as anxiety and depression [47]. Studies [48] have shown that although symptoms are particularly severe for patients during exacerbations, patients in remission are not completely symptom-free, and these symptoms can directly or indirectly affect the optimal management of the disease and quality of life. Therefore, healthcare professionals need to assess the frequency and severity of patients’ symptoms dynamically and develop patient-centered symptom management plans in terms of remission-phase symptom prevention, such as changes in diet, work and rest, and exercise, respectively, and active-phase symptom coping, such as active medical treatment, to reduce the symptom burden on patients and improve their quality of life. Secondly, symptom management for CD patients is a long-term process. Therefore, it is recommended that healthcare organizations combine with communities and families to build a tripartite support system for patient data sharing, communication, and interaction to meet the ongoing symptom management needs of CD patients [49].

Relationships between family function and the care needs of CD patients

The results of this study revealed differences in the levels of family cohesion and adaptability among the three groups of CD patients, and patients with better family cohesion and adaptability were more likely to belong to the low-care-needs-adaptation group, which is similar to the findings of Qin [50]. Because the family function is the ability of the family as a whole to meet the needs of its members, the better the family function is, the more it can respect the patient’s wishes in medical decision-making so that the patient can feel respected and be more objective in recognizing his or her physical condition, reducing inner turmoil, and accordingly reducing unmet needs [50]. Second, home enteral nutrition support and dietary management are important for the development and prognosis of CD [51], and daily supervision and comanagement by family members can play a substantial role in the recovery of patients. In the high-care-needs-distress group, the family function was poor. This may be because young adults constitute the main group of individuals with this disease, who are in a rising period of academic, career, and family development, and patients in the period of severe disease activity have to take a break from school, frequently leave or even quit their jobs to cooperate with the treatment of the disease [52], and some families have difficulty adapting to this unexpected situation. Here, family adaptability can be understood as the family’s ability to cope with the emergent situation [28]. In addition, although CD has been included in outpatient special diseases and outpatient chronic diseases in some regions of China, the reimbursement of medical insurance is limited, and long-term outpatient treatment and repeated hospitalization still bring serious financial pressure to families, which makes patients feel guilty and think that they are a burden on the family. Therefore, for this type of patient, it is recommended that caregivers focus on the patient’s family and encourage family members to participate in disease management and diagnostic and therapeutic decision-making to promote the patient’s perception of family intimacy and help him or her establish a good family support system. Second, they should take the initiative to understand the patient’s financial pressure and inform the patient of the reimbursement rate of medical insurance and the channels of financial support that can be sought to improve the patient’s financial situation. Finally, Zhao [53] has shown that family participation in psychological care also has significant effects on improving patient needs. Therefore, for patients with enterostomy and active CD, family members should be encouraged to give full play to the support function of the family system and actively participate in the patient’s care work, and patients should be given more emotional support and value affirmation from the family to meet the patient’s psychological and support needs and reduce guilt.

Relationships between PTG and the care needs of CD patients

Interestingly, the study found that patients with higher levels of PTG were more likely to belong to the low-care-needs-adaptation group and the moderate-care-needs-growth group (P > 0.05), with no significant difference between the two groups, consistent with the results of the profiling analysis. PTG is a positive psychological change experienced by individuals in the process of struggling with traumatic events [29] and can alleviate negative emotions and improve quality of life [54]. The higher scores in the moderate-care-needs-growth group may be because this group of patients experienced a positive psychological response to the illness, were able to cope positively even in a state of illness-induced discomfort, and were eager to seek information related to knowledge about the illness, diet, and exercise. Stress coping theory states that individuals fully mobilize internal and external resources through cognition and behavior to cope with stressful events [55]. Here, the desire to seek information support can be considered a form of coping that helps patients reappraise stressful events and discover internal and external resources to face illness with a positive attitude. This also demonstrates how illness or trauma can not only negatively affect an individual but also positively influence personal growth and health behaviors [56]. Secondly, patients with this type of CD may have achieved personal growth by relying on their own efforts and external support. They reflect on their experiences and learn to continuously adjust their internal understanding and sense of self, effectively “rebuilding themselves after the disease” [57]. As a result, these patients may have higher scores in PTG. For such individuals, clinical medical staff can utilize mobile information technology for patient management, such as offering professional and targeted disease management information through the IBD health education app network platform [58]. For the low-care needs-adaptation group, patients with higher levels of psychological function were more able to view the disease dialectically, reduce the negative impact of the disease through the internal and external environments, adapt to the disease, and adopt more health-promoting behaviors to manage the disease [59]. For the high-care-needs-adaptation group, the activity of the disease may cause trauma to the patient, which in turn will cause the patient to have symptoms of anxiety, depression, and fatigue and aggravate the patient’s physical and psychological needs [23]. It is suggested that medical staff can help patients express their emotions through narrative therapy, such as story listening and positive response, to meet their psychological needs [60].

The complexity of sociological demographic variables

Although the demographic characteristics of CD patients are not easy to intervene with, understanding the inter-patient differences in different care needs categories can help healthcare workers identify high-care-need patients early. The results of the univariate analysis of this study showed that the proportion of patients with full-time employment in the high-care-needs distress group (22.0%) was significantly lower than that in the other two groups (51.0%, 33.3%), and the proportion of household monthly income ≤ 3000 was higher (27.4% vs. 11.1%, 10.4%). Combined with Yu’s [6] research, economic vulnerability may exacerbate healthcare burden and anxiety levels, which in turn leads to higher demand. In addition, patients in this group received nasogastric feeding more frequently (51.2%), total enteral nutrition (43.8%), and complication rate (45.2%), which may lead to body image changes and may induce self-identity crisis, further increasing psychological burden [7]. Although these factors are not insignificant in multivariate models, their importance in univariate analyses remains alarming. In addition, univariate analysis showed no statistically significant difference in nursing needs between the three groups of patients in age and gender (P > 0.05). Possibly because heterogeneous sample stratification may weaken statistical power, the age-sex distribution in this study was consistent with the epidemiological characteristics of CD (< 40 years 64.4%; males 61.6%) [4]. In addition, the results of this study are consistent with the view put forward by Mak [3] that “the high needs of young and middle-aged patients are mainly due to disease activity rather than age itself”. In the future, the association of sociodemographic variables with care needs can be further explored through stratified sampling or expanded sample size.

Limitations

Despite the inclusion of this study from rural and urban areas of more than 40 districts in 11 provinces of China and the sample institution as an authoritative tertiary-level A hospital in China in the field of CD diagnosis and treatment, its patient population has a wide geographical coverage and diversity of demographic characteristics. However, the following limitations still need to be addressed. First, at the level of sampling method, given the very limited number of CD-specialized diagnostic and treatment institutions in China, the use of convenience sampling in this study may lead to sample structure bias, and it is suggested that stratified random sampling or probability sampling based on the regional healthcare institution registration system may be used in subsequent studies to enhance the extrapolation validity of the sample to the national CD patient population. Second, at the level of data collection, the assessment system based on subjective reports in this study may introduce social expectation bias and recall bias, and it is suggested that future studies may construct a comprehensive assessment model combining subjective and objective data to validate self-reported data by testing fecal calreticulin levels and C-reactive protein concentrations of validated biomarkers [61]. Furthermore, in terms of study design, cross-sectional studies limit the inference of causality, and it is suggested that prospective longitudinal study designs could be conducted in the future to systematically track the dynamic trajectory of the care needs of patients with CD at different stages. Meanwhile, collaborative multi-center studies can be conducted to effectively expand the sample size and enhance the reliability of results. Finally, at the tool application level, the validation of the CD-CNS scale is currently limited to the Chinese population. To enhance the cross-cultural adaptability of the assessment tool, it is suggested that future validation studies can be conducted in different healthcare systems and socio-cultural contexts, and cross-cultural comparisons can be carried out to enhance confidence in its use.

Conclusion

In summary, our findings have important implications for the management of patients with CD in the Chinese clinical setting. First, the study used LPA for the first time to explore the care needs of patients with CD, identifying three classes. Healthcare workers can develop individualized supportive care plans based on the characteristics of patients in different classes. Second, based on social-ecological system theory, this study analyzed the influencing factors of different classes at multiple levels and revealed that disease status, the presence of a stoma, symptom burden, family adaptability and cohesion, and PTG affect patients’ care needs. In the future, it is recommended that clinical medical staff evaluate CD care needs in multiple dimensions and set up interdisciplinary teams to collaboratively manage diseases; At the same time, combined with the results of this study and incorporating CD-CNS into the outpatient routine process, a dynamic monitoring system of “periodic routine assessment + special assessment during active period” was constructed to more accurately capture the care needs of CD patients and ensure the accurate matching of nursing measures with the real-time needs of patients.

Data availability

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

Abbreviations

CD:

Crohn’s disease

SCNS-SF34:

34-item Supportive Care Needs Survey

CD-CNS:

Crohn’s Disease Care Needs Scale

LPA:

Latent profile analysis

IBD:

Inflammatory bowel disease

FACES II:

Family Adaptability and Cohesion Scales, Second Edition

PTGI:

Post-traumatic Growth Inventory

PTG:

Post-traumatic growth

HBI:

Harvey-Bradshaw Index

AIC:

Akaike information criterion

BIC:

Bayesian information criterion

aBIC:

Sample size-adjusted BIC

LMR:

Lo‒Mendell‒Rubin

BLRT:

Bootstrap likelihood ratio test

Log L:

Log Likelihood

CI:

Confidence interval

OR:

Odds ratio

References

  1. Inflammatory Bowel Disease Group, Digestive Diseases Branch of Chinese Medical Association. Consensus opinions on the diagnosis and treatment of inflammatory bowel disease (2018, Beijing). Chin J Dig. 2018;38(9):292–311.

    Google Scholar 

  2. Torres J, Mehandru S, Colombel JF, Peyrin-Biroulet L. Crohn’s disease. Lancet. 2017;389(10080):1741–55.

    Article  PubMed  Google Scholar 

  3. Mak WY, Zhao M, Ng SC, Burisch J. The epidemiology of inflammatory bowel disease: East Meets West. J Gastroenterol Hepatol. 2020;35(3):380–9.

    Article  PubMed  Google Scholar 

  4. Ng SC, Kaplan GG, Tang W, Banerjee R, Adigopula B, Underwood FE, et al. Population density and risk of inflammatory bowel disease: a prospective population-based study in 13 countries or regions in Asia-Pacific. Am J Gastroenterol. 2019;114(1):107–15.

    Article  PubMed  Google Scholar 

  5. Lamb CA, Kennedy NA, Raine T, Hendy PA, Smith PJ, Limdi JK, et al. British society of gastroenterology consensus guidelines on the management of inflammatory bowel disease in adults. Gut. 2019;68(Suppl 3):s1–106.

    Article  PubMed  Google Scholar 

  6. Yu Q, Zhu C, Feng S, Xu L, Hu S, Chen H, et al. Economic burden and health care access for patients with inflammatory bowel diseases in China: web-based survey study. J Med Internet Res. 2021;23(1):e20629.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Schoefs E, Vermeire S, Ferrante M, Sabino J, Lambrechts T, Avedano L, et al. What are the unmet needs and most relevant treatment outcomes according to patients with inflammatory bowel disease? A qualitative patient preference study. J Crohns Colitis. 2023;17(3):379–88.

    Article  PubMed  Google Scholar 

  8. Regev S, Odes S, Slonim-Nevo V, Friger M, Schwartz D, Sergienko R, et al. Differential relationships of somatization, depression, and anxiety to severity of Crohn’s disease. J Health Psychol. 2021;26(13):2390–401.

    Article  PubMed  Google Scholar 

  9. Fitch MI. Supportive care needs of patients with advanced disease undergoing radiotherapy for symptom control. Can Oncol Nurs J. 2012;22(2):84–100.

    Article  PubMed  Google Scholar 

  10. Zhou L, Li H, Zhang Z, Wang L. Analysis of longitudinal trajectory and influencing factors of supportive care needs in colorectal Cancer patients with enterostomy. J Clin Nurs. 2024;33(5):789–95.

    Google Scholar 

  11. orouzkhani N, Faramarzi M, Bahari A, Shirvani JS, Eslami S, Tabesh H. Inflammatory bowel disease patients’ perspectives of nonmedical needs. BMC Gastroenterol. 2024;13(1):134.

    Article  Google Scholar 

  12. Hart A, Miller L, Büttner FC, Hamborg T, Saxena S, Pollok RCG, et al. Fatigue, pain and fecal incontinence in adult inflammatory bowel disease patients and the unmet need: a National cross-sectional survey. BMC Gastroenterol. 2024;24(1):481.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Volpato E, Bosio C, Previtali E, Leone S, Armuzzi A, Pagnini F, et al. The evolution of IBD perceived engagement and care needs across the life-cycle: a scoping review. BMC Gastroenterol. 2021;21(1):293.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Au A, Lam WW, Kwong A, Suen D, Tsang J, Yeo W, et al. Validation of the Chinese version of the short-form supportive care needs survey questionnaire (SCNS-SF34-C). Psychooncology. 2011;20(12):1292–300.

    Article  CAS  PubMed  Google Scholar 

  15. Chen D, Liu Q, Yu Z, Pan T, Zhang A, Chen Y, et al. Development and validation of a scale to measure the care needs of Crohn’s disease patients: a mixed-methods study. BMC Nurs. 2024;23(1):472.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Wu Q, Zhong J. Disease-related information requirements in patients with Crohn’s disease. Patient Prefer Adherence. 2018;12:1579–86.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Charzyńska E, Habibi Soola A, Mozaffari N, Mirzaei A. Patterns of work-related stress and their predictors among emergency department nurses and emergency medical services staff in a time of crisis: a latent profile analysis. BMC Nurs. 2023;22(1):98.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Pastor DA, Barron KE, Barron BJ, Miller SL, Davis. A latent profile analysis of college students’achievement goal orientation. Contemp Edu Psychol. 2007;32(1):8–47.

    Article  Google Scholar 

  19. Howard MC, Hoffman ME, Variable-Centered. Person-Centered, and Person-Specific approaches: where theory Meets method. Organizational Res Methods. 2018;21(4):846–76.

    Article  Google Scholar 

  20. Trinh L, Larsen K, Faulkner GE, Plotnikoff RC, Rhodes RE, North S, et al. Social-ecological correlates of physical activity in kidney cancer survivors. J Cancer Surviv. 2016;10(1):164–75.

    Article  PubMed  Google Scholar 

  21. Xi Y, Liu R, Tang Y, Peng Y, Jin G, Song J. Trajectory patterns and influencing factors of supportive care needs in stroke patients: A longitudinal study. J Adv Nurs. 2025;81(2):809–19.

    Article  PubMed  Google Scholar 

  22. Tedeschi RG, Lawrence G, Calhoun. Posttraumatic growth: conceptual foundations and empirical evidence. Psychol Inq. 2004;15(1):1–18.

    Article  Google Scholar 

  23. Azman N, Leong Bin Abdullah MFI, Musa KI, Hassan N, Mohd Shariff N. Prospective cohort study of unmet supportive care needs, post-traumatic growth, coping strategy and social supports among patients with breast cancer: the PenBCNeeds study. J Psychosoc Oncol. 2024;42(5):688–708.

    Article  PubMed  Google Scholar 

  24. Kendall SM, Stuart A, Ord JK. Kendall’s advanced theory of statistics. Volume 1: Distribution theory. 5th ed. JR Stat Soc Series. 1988;84(407):41.

  25. Ni P, Chen JL, Liu N. The sample size Estimation in quantitative nursing research. Chin J Nurs. 2010;45(04):378–80.

    Google Scholar 

  26. Gu FC, Lin Z, Shang XC, Bian QG, Lin L, Zhang HJ, et al. Construction and preliminary application of symptom cluster scale for inflammatory bowel disease. Chin J Nurs. 2020;55(12):1819–24.

    Google Scholar 

  27. Olson DH, Sprenkle DH, Russell CS. Circumplex model of marital and family system: I. Cohesion and adaptability dimensions, family types, and clinical applications. Fam Process. 1979;18(1):3–28.

    Article  CAS  PubMed  Google Scholar 

  28. Fei LP, Shen QJ, Zhen YP, Zhao JP, Jiang SA, Wang LW et al. Preliminary evaluation of the Chinese version of Faces II and FES: comparison of normal families and families of schizophrenic patients. Chin Ment Health J. 1991;(05):198–202, 238.

  29. Tedeschi RG, Calhoun LG. The posttraumatic growth inventory: measuring the positive legacy of trauma. J Trauma Stress. 1996;9(3):455–71.

    Article  CAS  PubMed  Google Scholar 

  30. Wang J, Chen Y, Wang YB, Liu XH. Revision of the posttraumatic growth inventory and testing its reliability and validity. J Nurs Sci. 2011;26(1):26–8.

    Google Scholar 

  31. Harvey RF, Bradshaw JM. A simple index of Crohn’s-disease activity. Lancet. 1980;1(8167):514.

    Article  CAS  PubMed  Google Scholar 

  32. Wang J, Wang X. Structural equation modeling: applications using Mplus. 2nd ed. Hoboken, NJ: Wiley; 2019.

    Book  Google Scholar 

  33. Zhu ZH, Lin Z, Bian QG. A qualitative study on supportive care needs of patients with inflammatory bowel disease. Chin J Pract Nurs. 2023;39(3):222–7.

    Google Scholar 

  34. Knowles S, Andrews JM, Porter A, Hons B. Predictors of impaired mental health and support seeking in adults with inflammatory bowel disease: an online survey. Gastroenterol Nurs. 2018;41(1):38–46.

    Article  PubMed  Google Scholar 

  35. Maslow AH. A theory of human motivation. Psychol Rev. 1943;50(4):370–96.

    Article  Google Scholar 

  36. Daher S, Khoury T, Benson A, Walker JR, Hammerman O, Kedem R, et al. Inflammatory bowel disease patient profiles are related to specific information needs: A nationwide survey. World J Gastroenterol. 2019;25(30):4246–60.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Eberhart L, Aust H, Schuster M, Sturm T, Gehling M, Euteneuer F, et al. Preoperative anxiety in adults-a cross-sectional study on specific fears and risk factors. BMC Psychiatry. 2020;20:1–14.

    Article  Google Scholar 

  38. Central Committee of the Communist Party of China, State Council. Healthy China 2030 Planning Outline. 2016 Oct 25 [cited 2025 Apr 15]. Available from: http://www.gov.cn/xinwen/2016-10/25/content_5124174.htm

  39. Atreja A, Khan S, Rogers JD, Otobo E, Patel NP, Ullman T et al. Impact of the mobile healthpromise platform on the quality of care and quality of life in patients with inflammatory bowel disease: study protocol of a pragmatic randomized controlled trial. JMIR Res Protoc. 2015;18;4(1):e23.

  40. Larsson K, Lööf L, Nordin K. Stress, coping and support needs of patients with ulcerative colitis or C Rohn’s disease: a qualitative descriptive study. J Clin Nurs. 2017;26(5–6):648–57.

    Article  PubMed  Google Scholar 

  41. Chen L, Zhou Y. The symptom experience of newly diagnosed Chinese patients with Crohn’s disease: A longitudinal qualitative study. J Adv Nurs. 2023;79(10):3824–36.

    Article  PubMed  Google Scholar 

  42. Taylor K, Chivers P, Bulsara C, Joske D, Bulsara M, Monterosso L. Care after lymphoma (CALy) trial: A phase II pilot pragmatic randomised controlled trial of a nurse-led model of survivorship care. Eur J Oncol Nurs. 2019;40:53–62.

    Article  PubMed  Google Scholar 

  43. Qin F, Zhen L, Ye X, Wei H, Zhu M, Chen J, et al. Stigma and its influence on patients with temporary ostomy: A Cross-sectional survey. J Wound Ostomy Cont Nurs. 2020;47(3):244–8.

    Article  Google Scholar 

  44. Peng LF, Hu DY, Xiong Y, Hu LZ, Li MM. Application of acceptance commitment group therapy in patients with inflammatory bowel disease. Nurs Sci. 2024;39(09):94–8.

    Google Scholar 

  45. Wang S, Li Y, Li S, Zhang E, Dai Z, Cui J, et al. Association between type D personality and supportive care needs in elderly patients with breast cancer: a prospective longitudinal observational study. BMC Geriatr. 2023;23(1):721.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Abraham BP. Symptom management in inflammatory bowel disease. Expert Rev Gastroenterol Hepatol. 2015;9(7):953–67.

    Article  CAS  PubMed  Google Scholar 

  47. Kamp K, Yang PL, Tsai CS, Zhang X, Yoo L, Altman MR, et al. Gender and sex differences in abdominal pain, fatigue, and psychological symptoms among adults with inflammatory bowel disease: A network analysis. Inflamm Bowel Dis. 2025;31(2):442–9.

    Article  PubMed  Google Scholar 

  48. Barberio B, Zamani M, Black CJ, Savarino EV, Ford AC. Prevalence of symptoms of anxiety and depression in patients with inflammatory bowel disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2021;6:359–70.

    Article  PubMed  Google Scholar 

  49. Lu XP, Wang WJ, Wei HX, Yang X, Zhang X, Zheng TH. Construction of a hospital-community linkage continuous care quality evaluation index system for patients with inflammatory bowel disease. Nurs Res. 2024;38(24):4371–7.

    Google Scholar 

  50. Qin SW, Zhang YJ, Zhang Y, Wang y, Fan JW, Shi XQ, et al. Mediating role of symptom distress between family function and supportive care needs among esophageal cancer patients after esophagectomy. J Nurs Sci. 2022;37(07):5–8.

    Google Scholar 

  51. Inflammatory Bowel Disease Group, Chinese Society of Gastroenterology, Chinese Medical Association. Group of gastroenterology and nutrition, Chinese society of parenteral and enteral nutrition. Expert consensus on nutritional support therapy of inflammatory bowel disease. Chin J Inflamm Bowel Dis. 2018;2(3):154–72. 2nd ed.

    Google Scholar 

  52. Popov J, Farbod Y, Chauhan U, Kalantar M, Hill L, Armstrong D, et al. Patients’ experiences and challenges in living with inflammatory bowel disease: A qualitative approach. Clin Exp Gastroenterol. 2021;14:123–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zhao L, Ma L, Chen X, Liu Z. Psychological nursing intervention improves the mental health status of young patients with lung cancer surgery during the perioperative period. Medicine. 2021;100(31):e26736.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Liu Z, Doege D, Thong MSY, Arndt V. The relationship between posttraumatic growth and health-related quality of life in adult cancer survivors: A systematic review. J Affect Disord. 2020;276:159–68.

    Article  PubMed  Google Scholar 

  55. Folkman S, Lazarus RS, Gruen RJ, DeLongis A. Appraisal, coping, health status, and psychological symptoms. J Pers Soc Psychol. 1986;50(3):571–81.

    Article  CAS  PubMed  Google Scholar 

  56. Seligman ME, Csikszentmihalyi M. Positive psychology. An introduction. Am Psychol. 2000;55(1):5–14.

    Article  CAS  PubMed  Google Scholar 

  57. Wang Y, Zhang C, Zhou Y. Reconstructing self from the illness: a constructivist grounded theory study of posttraumatic growth in patients with Crohn’s disease. BMC Gastroenterol. 2023;23(1):244.

    Article  PubMed  PubMed Central  Google Scholar 

  58. McNamara J, Connor SJ, Andrews JM. The evolving role of technology in delivering patient-centric, empowered health care in inflammatory bowel disease: patient experience using Crohn’s colitis care e-Health consumer platform. Inflamm Bowel Dis. 2023;29(9):1510–1.

    Article  PubMed  Google Scholar 

  59. Xu G, Liu T, Jiang Y, Xu Y, Zheng T, Li X. Heterogeneity in psychological adaptation patterns and its predictive factors among patients with inflammatory bowel disease: A latent profile analysis. Psychol Res Behav Manag E. 2024;17:219–35.

    Article  Google Scholar 

  60. Sun XX, Wang YL, Lu W, Lu W, Zhu LH. Application of narrative nursing to the management of symptom clusters and post-traumatic growth of lung cancer surgery patients. Chin J Lung Cancer. 2025;28(01):40–6.

    Google Scholar 

  61. Verstockt B, Noor NM, Marigorta UM, Pavlidis P, Deepak P, Ungaro RC, et al. The results of the seventh scientific workshop of ECCO: precision medicine in IBD—disease outcome and response to therapy. J Crohns Colitis. 2021;15(9):1410–30.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank all the CD patients, nurses, and doctors who participated in this study. We also sincerely thank Nanjing Second Hospital for its support and help.

Funding

This study was supported by the special fund project plan of Nanjing Health Science and Technology Development (Grant number: YKK22128) and the 13th Five-Year Nanjing Health Youth Talent Training Project (Grant number: QRX17155).

Author information

Authors and Affiliations

  1. School of Nursing, Nanjing University of Chinese Medicine, Nanjing, 210023, China

    Rongfei Duan, Wan Mei, Danlei Chen & Ting Pan

  2. Jiangsu Health Vocational College, Nanjing, 211800, China

    Ming Lei

  3. Gastroenterological Disease Diagnosis and Treatment Centre, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, 210003, China

    Fang Kong

  4. Department of Nursing, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, 1 Zhongfu Road, Gulou District, Nanjing, 210003, Jiangsu Province, China

    Yan Chen

Authors
  1. Rongfei Duan
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Wan Mei
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Ming Lei
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Danlei Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Ting Pan
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Fang Kong
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Yan Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

All authors contributed to the study conception and design. DRF: data collection, data analysis, first draft of thesis. MW: help with data analysis and thesis translation. LM, CDL, CY, PT: study design and conceptualization, manuscript revision. KF: clinical assistance and patient co-ordination.

Corresponding author

Correspondence to Yan Chen.

Ethics declarations

Ethics approval and consent to participate

This study followed the Declaration of Helsinki and was approved by the ethics committee of Nanjing Second Hospital (No. 2023-LS-Ky-022). All study subjects gave informed consent and voluntarily participated in this study. In addition, this study was an anonymous survey, did not involve unethical behavior, and did not cause adverse health consequences to the participants’ physical or mental health.

Consent for publication

Not applicable.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

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

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Duan, R., Mei, W., Lei, M. et al. Care needs profiles of Crohn’s disease patients and their associations with symptom clusters, post-traumatic growth, and family function: a latent profile analysis. BMC Gastroenterol 25, 351 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12876-025-03953-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12876-025-03953-5

Keywords

BMC Gastroenterology

ISSN: 1471-230X

Contact us