
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39266693
72410
10.1038/s41598-024-72410-2
Article
Latent profile analysis of family adaptation in breast cancer patients-cross-sectional study
Ding Zhangyi 1
Fan Yarong 3
Li Enguang 1
Ai Fangzhu 1
Cui Huixia 1319447367@qq.com

2
1 https://ror.org/02yd1yr68 grid.454145.5 0000 0000 9860 0426 School of Nursing, Jinzhou Medical University, No.40, Section 3, Songpo Road, Linghe District, Jinzhou City, 121000 Liaoning Province China
2 https://ror.org/037ejjy86 grid.443626.1 0000 0004 1798 4069 School of Nursing, Wannan Medical College, Wenchang West Road, Wuhu Higher Education Park, Wuhu, 241002 Anhui Province China
3 https://ror.org/0265d1010 grid.263452.4 0000 0004 1798 4018 School of Nursing, Shanxi Medical University, 56 Xinjian South Road, Yingze District, Taiyuan City, 030000 Shanxi Province China
12 9 2024
12 9 2024
2024
14 2135724 5 2024
6 9 2024
© The Author(s) 2024
2024
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When individuals face life pressure or significant family changes, individuals with better family adaptation can better survive the crisis. Although the influencing factors of family adaptation have been investigated, the application of potential profile analysis has yet to be found. This analytical approach can reveal different potential categories of family adaptation, providing new perspectives for theoretical development and interventions. This study used latent profile analysis to explore family adaptation levels in breast cancer patients and identify different latent categories, examining their characteristic differences. A cross-sectional study was conducted in Jinzhou, China, from July 2023 to March 2024. The questionnaire included Sociodemographic and clinical characteristics, Benefit Finding Scale (BFS), Dyadic Coping Scale (DCI), Chinese Perceived Stress Scales (PSS), and Family adaptability and cohesion evaluation scales (FACES). Mplus8.3 and SPSS26.0 software were used for data analysis. The latent profile analysis (LPA) method was used to fit the family adaptations of breast cancer patients. Three latent categories of family adaptation were identified: low-level family adaptation (21.5%), medium level family adaptation (47.8%), and high-level family adaptation (30.6%). All 14 items with high levels of family adaptation scored higher than the other two groups. In particular, out of all the categories, item 9, "The idea of educating children is sound," scored highest. Compared with the low-level group, the influential factors of family adaptation in the high-level group were BFS, DCI, PSS, relapse and personal monthly income; The factors influencing family adaptation at the middle level are DCI, BFS, breast cancer type, family history of breast cancer, and personal monthly income. Compared with the medium level group, PSS and DCI were the influential factors of family adaptation in the high-level group. Family adaptation in breast cancer patients can be divided into three categories: low-level, medium-level, and high-level. There were significant differences among different categories of family adaptation levels in “personal monthly income”, “family history of breast cancer”, “type of breast cancer”, “recurrence”, “dyadic coping”, “benefit finding”, and “perception stress”.

Keywords

Latent profile analysis
Family adaptation
Breast cancer
Family stress coping theory
Benefit finding
Dyadic coping
Perception stress
Subject terms

Cancer
Psychology
Health occupations
Medical research
doctoral research Fund of Wannan Medical CollegeWYRCQD2023043 Cui Huixia issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

According to the latest figures released by the International Agency for Research on Cancer (IARC), the number of breast cancer cases reached 2.3 million, overtaking lung cancer to become the world's most common cancer1. In China, the number of new cases of breast cancer is 357,000, ranking first in the number of new cases of cancer among Chinese women2. The Global Cancer Survival Project (CONCORD) database shows that the survival rate of breast cancer in Asia continues to increase, and the 5-year survival rate of breast cancer patients in China is between 80 and 84%3. As a result, breast cancer patients have become one of the largest groups of cancer survivors4. The high survival rate of breast cancer has caused more and more researchers to pay attention to the long-term quality of life of patients, among which the family adaptation of cancer patients is considered to be one of the critical factors affecting the quality of life5–8.

Family members provide various support, including emotional, nursing, and financial support, so families are an essential source of emotional support for patients to fight the disease9. Family adaptation is the family's direct response to stressful events, meaning that the family is aware of the need to adjust the structure to restore stability and improve family happiness and satisfaction10. Patients with low family adaptation levels will increase caregivers' burden, lead to a decrease in family happiness, and are also unfavorable to the rehabilitation of patients11,12. Studies have shown that negative emotions, such as anxiety, depression, and suicidal ideation, are associated with low family adaptation13–15. A family adaptation crisis can stress patients tremendously, reducing effective communication and active coping between spouses. As a result, some couples choose to divorce15. Some breast cancer patients have to undergo mastectomy, which may lead to problems in the sexual life of the couple, which in turn affects family harmony, resulting in a decline in the family's ability to adapt16. Good family adaptability can promote the cultivation of patients' positive emotions and help couples establish an excellent intimate relationship so family members can support each other and get through this crisis together17,18.

Previous studies have explored the influence of various factors on family adaptation, including related factors such as religious belief, family economic status, age, marital status, and stress19–21. However, most of these studies use the overall score of the Family adaptation Scale or set a numerical value to assess the severity of family adaptation22. This approach fails to take into account the actual situation of the participants fully, ignores the intrinsic characteristics of the individuals, and does not stratify the population. To better understand, we need to take a person-centered approach, observe the relationship of relevant variables among participants, and identify subgroups of individuals based on their response patterns to a set of variables23.

Latent profile analysis (LPA) is a human-centered statistical method used to identify potential, unobserved subgroups or latent profiles in the data. It aims to discover potential, relatively unique groups in the data that show different patterns or characteristics on the observed variables. LPA is often used to study latent types or subgroups in a population to understand the data better and provide personalized intervention or treatment options (the observed variables. LPA is often used to study latent types or subgroups in a population to understand the data better and provide personalized intervention or treatment options24. Latent Class analysis (LPA) has been applied to various populations, including cancer patients25–28. Xixi Jiang et al. analyzed the endogenous levels of family adaptation in adolescents and children and found three subgroups of family adaptation (low, medium, and high)29. However, to our knowledge, no studies have used LPA to investigate family adaptation in breast cancer patients. Therefore, the main objective of this study was to use LPA methods to identify subgroups of family adaptation in breast cancer patients to address patient heterogeneity. Secondly, we will explore the influencing factors of different family adaptation subgroups to understand the characteristics of family adaptation in breast cancer patients.

This study explores the potential profile analysis of family adaptation in breast cancer patients through family stress coping theory. Family stress coping theory30, also known as the ABC-X theoretical model, was proposed by Reuben Hill, the father of family stress theory, in 1949. It is a relatively comprehensive model of family stress theory at present. The model includes four factors, A, B, C and X, as shown in Fig. 1. Factor A represents the stressor event, that is, any event that can cause an individual to produce a stress response; Factor B represents resources that can exist at the individual, family and community levels; Factor C represents cognition or evaluation of stressful events; X factor is the outcome, that is, the impact of stress or crisis on an individual, which is influenced by multiple factors of stressors, resources and cognition. In this study, A represents Perceived Stress; B stands for Dyadic Coping; C stands for Benefit Finding; and X stands for Family Adaptation.Fig. 1 ABC-X theoretical model.

Methods

This study used a cross-sectional design and convenient sampling method to select breast cancer patients in breast surgery, oncology, radiotherapy and chemotherapy departments in two general hospitals in Jinzhou City, China, from July 2023 to March 2024. The members of the research team recruited and collected data on study subjects. We use face-to-face data collection to address patients' difficulties when filling out the questionnaire. Eligibility criteria for participants include: (a) ≥ 18 years of age, (b) Pathological diagnosis of breast cancer, (c) clear-headed and willing to participate in research, (d) Ability to communicate normally. Exclusion criteria include: (a) the patient has been diagnosed with a mental illness or cognitive impairment; (b) Metastasis or spread of the tumor. According to the recommendation, the LPA method was used in this study to ensure a sample size of 300–500 people31, and ultimately, a total of 325 breast cancer patients participated. The flow diagram was shown in Fig. 2.Fig. 2 Flow diagram.

Measures

Sociodemographic and clinical characteristics

The demographic information of patients was collected using self-made questionnaires. Such as occupation, marital status, Residency and personal monthly income, etc. At the same time, clinical characteristics of patients was obtained through medical record review. Such as Whether there is a family history of breast cancer, Your type of breast cancer, Clinical classification of your breast cancer and whether it recurs, etc.

Dyadic Coping Inventory (DCI)

DCI was developed by Bodenmann32 in 2008 to assess how well couples cope with stress. In 2016, Chinese scholar Xu Feng33 Sinicized the DCI scale in Chinese. There are 37 items on the scale, including 6 dimensions: pressure communication (8 items), empowering dyadic coping (10 items), agent dyadic coping (4 items), joint dyadic coping (5 items), negative dyadic coping (8 items) and coping quality evaluation (2 items), among which the coping quality evaluation dimension is not included in the total score. The Likert 5-level score ranges from 1 (very rarely) to 5 (very often). The total scale score ranges from 35 to 175 points. A score below 111 indicates a low level of dyadic coping, 111 to 145 is a moderate level, and a score above 145 is a high level of dyadic coping, with a higher score representing a better ability to provide coping. In this study, Cronbach's α was 0.942 for the patients.

Benefit finding scale (BFS)

The Benefit Finding Scale, initially invented by Antoni et al.34, emphasizes that when facing challenges in life, individuals do not simply deal with difficulties but can find opportunities for growth, learning and development through these experiences. This process is not only a process of coping with crises but also a process of psychological growth. In this study, the Chinese version of the Benefit Finding Scale adapted by Liu zhunzhun et al.35 was used to assess the level of benefit finding in breast cancer patients. The scale consists of 22 items and six dimensions, including the acceptance dimension, family relationship dimension, worldview dimension, personal growth dimension, social relationship dimension, health behaviour dimension, etc. A 5-point Likert scale is used, ranging from 1 (none at all) to 5 (very much). Scores range from 22 to 110points. The higher the total score, the higher the level of benefit finding. In this study, Cronbach's α was 0.923 for patients.

Family adaptability and cohesion evaluation scales (FACES)

FACES is the most commonly used family adaptation scale. FACES was developed by Olson36 in 1979. Chinese scholars translated the FACES scale into Chinese. They revised it to form the Chinese version of the FACES II-CV scale37, which contains 30 items divided into two subscales: family intimacy and family adaptability. Among them, intimacy contains 16 items, and adaptability contains 14 items. A 5-point Likert scale is used, ranging from 1 (never) to 5 (always). In the scale, the content of the family adaptability dimension is more appropriate, which can better reflect the individual's satisfaction with family adaptation. In this study, Cronbach's α was 0.957 for the patients.

Chinese perceived stress scales (PSS)

The Perceived Stress Scales was developed by Cohen et al. in 198338 and revised in Chinese by Chinese scholar Tingzhong Yang in 200339. This scale is mainly used to assess individuals' perception of stressful events, including the two dimensions of tension (7 items) and sense of loss of control (7 items), with 14 items. A Likert 5-level score was used, with higher scores representing more significant perceived stress. In this study, Cronbach's α was 0.941 for the patients.

Data analysis

The data were analyzed using Mplus version 8.3 and IBM SPSS Statistics version 25.0. The statistical methods included descriptive statistical calculations, and t test, a one-way ANOVA, or a chi-square (χ2) test were used to compare the variables. Nonconditional logistic regression was used for multifactor analysis. The differences were statistically significant at p < 0.05 or p < 0.01.

To identify Family adaptation of breast cancer patients, we performed LPA using Mplus8.3. Data for the 14 items were entered into the LPA, with one class initially and additional classes added incrementally until a unique solution could be determined with maximum likelihood methods. In deciding on the number of profiles retained, we relied on a combination of statistical indexes and substantive interpretation in comparing competing models with different numbers of classes and used the Lo–Mendell–Rubin likelihood ratio test (LMRT) and bootstrapped likelihood ratio test (BLRT) as significance tests to compare models with different profiles. A significant LMRT or BLRT(with p < 0.05) would indicate that the more complex model (k class model) outperformed the simpler model (k-1 class model) with the increased model fit. We considered a combination of indexes for model selection, including Akaike information criterion (AIC), Bayesian information criterion (BIC), sample size-adjusted Bayesian information criterion (aBIC), and entropy. The model with lower AIC, BIC, and aBIC would indicate a better fit, whereas the model with an entropy value approaching 1 would indicate a clear delineation of the classes constructed in the model. To test the differences in sociodemographic characteristics and to determine the psychological characteristics of the latent profile based on LPA, SPSS 25.0 was used, and all statistical tests were two-sided (α = 0.05).

Results

Participant characteristics

Three hundred sixty patients were collected for this study, and 35 incomplete data were excluded, resulting in 325 valid samples. Most participants were company employees (51.6%, n = 168), married for the first time (77.2%, n = 251), and lived in a city (49.5%, n = 161). Regarding personal monthly income, 128 patients reported a monthly income of more than 8000 yuan (RMB). Regarding education, 38 patients had a bachelor's degree or above. According to the report, 241 patients had a family history of breast cancer, 319 had breast-related disease, and 255 patients had no recurrence, 309 had breast cancer that occurred in the left breast. See Table 1 for more details.Table 1 Sociodemographic and clinical characteristics (n = 325).

Variable	Patient	
Classification	Frequency	Percent	
Occupation	Worker	22	6.70	
Farmer	39	12.00	
Employee	168	51.60	
Health care workers	37	11.30	
Teacher	39	12.00	
Retired	20	6.10	
Marital status	First marriage	251	77.20	
Remarriage	74	22.70	
Residency	City	161	49.50	
Town	125	38.40	
Countryside	39	12.00	
Personal monthly income	 < 1000	4	1.20	
1000–3000	42	12.90	
3001–5000	51	15.60	
5001–8000	100	30.70	
 > 8000	128	39.30	
Education level	Bachelor degree or above	38	11.60	
High school	78	24.00	
Primary school, Middle school	209	64.30	
Whether there is a family history of breast cancer	No	84	25.80	
Yes	241	74.10	
Have you ever been diagnosed with other breast diseases?	No	6	1.80	
Yes	319	98.10	
Your type of breast cancer	Carcinoma in situ	315	96.90	
Invasive cancer	10	3.07	
Clinical classification of your breast cancer	I	204	62.70	
II	110	33.80	
III	11	3.30	
What kind of breast cancer surgery did you have	Radical resection + lymph node dissection	157	48.30	
Modified radical resection + lymph node dissection	98	30.10	
Breast conservancy	70	21.50	
Whether it recurs	Yes	70	21.50	
No	255	78.40	
Medical payment	At your own expense	4	1.20	
Full reimbursement	29	8.90	
Partial reimbursement	292	89.80	
Your breast cancer location	Left	309	95.08	
Right	9	2.77	
Both sides	7	2.15	

Latent profile analysis

In this study, latent profile analysis was performed on 14 items of family adaptation in the Family adaptability and cohesion evaluation scales, and one to four latent categories were fitted sequentially. The fitting indices of different types of profile models are shown in Table 2. The observations showed that Profiles 4 had p values of LMRT probability greater than 0.05, indicating that it did not reach the significance level and were therefore excluded. At the same time, the aBIC value of Profile 3 is lower than that of Profile 1, which is more in line with the optimal criteria. Finally, we also need to consider the entropy value. The entropy value of Profile 3 is closer to 1 than Profile 1 and Profile 2, so Profile 3 has the best classification effect. Taking the above analysis together, it can be concluded that Profile 3 is the optimal model.Table 2 Comparison of fit indices between models.

Profile	AIC	BIC	aBIC	Entorpy	LMR(P)	BLRT(P)	Category probability	
1	10,723.41	10,829.35	10,740.54	1				
2	8517.937	8680.641	8544.249	0.946	0.010	 < 0.001	0.596,0.403	
3	7325.556	7545.018	7361.046	0.968	0.011	 < 0.001	0.212, 0.483, 0.304	
4	6851.151	7127.37	6895.82	0.991	0.654	 < 0.001	0.150,0.313,0.212,0.323	

In order to verify the reliability of the above latent profile analysis results, we calculated the average attribution probability of the three class samples in each class. The results showed that the correct classification probability of the latent class 1 was 98.8%, the latent class 2 was 98.1%, and the latent class 3 was 99.4%. These probabilities are all greater than 90%, indicating that the results of latent profile analysis in this study are relatively reliable. See Table 3 for details.Table 3 Average latent class probabilities for most likely latent class membership (row) by latent class (column).

Class	Profile1	Profile2	Profile3	
Profile1	0.988	0.012	0.000	
Profile2	0.012	0.981	0.007	
Profile3	0.000	0.006	0.994	

Naming of latent profile

Figure 3 reflected the mean values of the three profiles of family adaptation level of breast cancer patients in terms of the scores of each item. The categories were named “low-level family adaptation”, “mid-level family adaptation” and “high-level family adaptation” according to the characteristics of the mean values of the scores of the items in the different categories. The “mid-level family adaptation” had the highest percentage of 47.8% of all subjects, followed by the “high-level family adaptation” with 30.6%, and the low-level family adaptation with 21.5%.Fig. 3 Latent profile model of family adaptation in breast cancer patients.

F1-14, Family closeness and adaptability scale item

Inter-profile characteristic differences

Table 4 compares differences in demographic characteristics between the three underlying family adaptation types. Table 5 shows the scores of different groups for family adaptation, dyadic coping, benefit finding, Perceived Stress and Sociodemographic and clinical characteristics. The findings revealed statistically significant differences between breast cancer patient with different underlying family adaptation categories involving multiple factors. These factors included Marital status, Personal monthly income, Whether there is a family history of breast cancer, Your type of breast cancer, What kind of breast cancer surgery did you have, whether it recurs, benefit finding, dyadic coping, and perceived stress. For the remaining categorical differences, we did not observe statistically significant differences.Table 4 Demographic characteristics of the different profiles.

Characteristics	Total sample	Low level family adaptation	Medium level family adaptation	High level family adaptation	F/X2	P	
Occupation					7.467	0.681	
 Worker	22	6	8	8			
 Farmer	39	8	20	11			
 Employee	168	34	86	48			
 Health care workers	37	9	18	10			
 Teacher	39	6	20	13			
 Retired	20	6	5	9			
Marital status					8.232	0.016	
 First marriage	251	45	123	83			
 Remarriage	74	24	34	16			
Residency					5.164	0.271	
 City	161	38	82	41			
 Town	125	23	55	47			
 Countryside	39	8	20	11			
Personal monthly income					24.741	0.002	
  < 1000	4	1	1	2			
 1001–3000	42	20	16	6			
 3001–5000	51	9	27	15			
 5001–8000	100	19	53	28			
  > 8000	128	20	60	48			
Education level	
 Bachelor degree or above	38	9	20	9	3.204	0.524	
 High school	78	20	32	26			
 Primary school, middle school	209	40	105	64			
Whether there is a family history of breast cancer					7.578	0.023	
 No	84	9	47	28			
 Yes	241	60	110	71			
Have you ever been diagnosed with other breast diseases?					2.455	0.293	
 No	6	2	1	3			
 Yes	319	67	156	96			
Your type of breast cancer					21.337	0.000	
 Carcinoma in situ	315	61	156	98			
 Invasive cancer	10	8	1	1			
Clinical classification of your breast cancer					1.039	0.904	
 I	204	45	98	61			
 II	110	21	55	34			
 III	11	3	4	4			
What kind of breast cancer surgery did you have					42.870	0.000	
 Radical mastectomy + lymph node dissection	157	37	89	31			
 Modified radical mastectomy + lymph node dissection	98	26	47	25			
 Breast conservancy	70	6	21	43			
Whether it recurs					15.005	0.001	
 Yes	70	24	36	10			
 No	255	45	121	89			
Medical payment					0.854	0.931	
 At your own expense	4	1	2	1			
 Full reimbursement	29	8	13	8			
 Partial reimbursement	292	60	142	90			
Your breast cancer location					5.375	0.251	
 Left	309	64	151	94			
 Right	9	3	5	1			
 Both side	7	2	1	4			
Bfs	325	69	157	99	8.111	0.000	
Dci	325	69	157	99	10.785	0.000	
Pss	325	69	157	99	7.340	0.000	
Bfs benefit finding scale, dci dyadic coping inventory, pss perceived stress scales.

Table 5 The scores of different groups.

Characteristics	Low level family adaptation	Medium level family adaptation	High level family adaptation	
Occupation	
 Worker	33.67 ± 2.733	42.63 ± 3.543	54.25 ± 2.188	
 Farmer	29.88 ± 2.850	42.80 ± 3.238	53.09 ± 2.300	
 Employee	33.00 ± 3.970	44.20 ± 3.597	56.38 ± 4.394	
 Health care workers	32.11 ± 1.573	43.50 ± 2.358	53.10 ± 1.912	
 Teacher	31.17 ± 3.371	43.45 ± 2.819	56.00 ± 3.937	
 Retired	34.33 ± 2.503	44.40 ± 3.75	55.67 ± 3.536	
Marital status	
 First marriage	32.27 ± 3.208	44.11 ± 3.251	55.02 ± 3.848	
 Remarriage	33.04 ± 3.973	42.56 ± 3.413	57.31 ± 3.665	
Residency	
 City	32.82 ± 3.262	43.73 ± 3.228	55.20 ± 3.219	
 Town	33.00 ± 3.754	44.18 ± 3.512	56.11 ± 4.507	
 Countryside	29.88 ± 2.850	42.80 ± 3.238	53.09 ± 2.300	
Personal monthly income	
 < 1000	34.00 ± 0.000	45.00 ± 0.000	54.50 ± 2.121	
 1001–3000	31.10 ± 2.360	43.94 ± 3.642	51.67 ± 2.160	
 3001–5000	31.56 ± 4.304	43.89 ± 3.523	55.47 ± 4.926	
 5001–8000	32.53 ± 3.687	43.81 ± 3.418	55.61 ± 4.022	
 > 8000	34.35 ± 3.313	43.62 ± 3.141	55.75 ± 3.540	
Education level	
 Bachelor degree or above	29.44 ± 2.936	43.20 ± 3.238	52.56 ± 2.068	
 High school	32.45 ± 3.170	43.34 ± 3.366	53.96 ± 4.054	
 Primary school, middle school	33.28 ± 3.419	44.01 ± 3.353	56.38 ± 30,680	
Whether there is a family history of breast cancer	
 No	34.44 ± 4.065	43.72 ± 3.888	57.64 ± 3.413	
 Yes	32.25 ± 3.333	43.79 ± 3.092	54.51 ± 3.730	
Have you ever been diagnosed with other breast diseases?	
 No	31.00 ± 0.000	38.00 ± 0.000	52.33 ± 0.577	
 Yes	32.58 ± 3.525	43.81 ± 3.316	55.49 ± 3.915	
Your type of breast cancer	
 Carcinoma in situ	32.74 ± 3.530	43.78 ± 3.348	55.44 ± 3.888	
 Invasive cancer	31.00 ± 2.828	43.00 ± 0.000	51.00 ± 0.000	
Clinical classification of your breast cancer	
 I	32.98 ± 3.265	44.01 ± 3.323	55.49 ± 3.876	
 II	31.90 ± 3.948	43.44 ± 3.452	55.59 ± 4.001	
 III	30.33 ± 2.517	42.50 ± 1.291	52.25 ± 2.217	
What kind of breast cancer surgery did you have	
 Radical mastectomy + lymph node dissection	32.16 ± 3.833	43.97 ± 3.443	54.71 ± 4.149	
 Modified radical mastectomy + lymph node dissection	33.38 ± 2.886	43.21 ± 3.196	55.28 ± 3.803	
 Breast conservancy	31.17 ± 3.251	44.19 ± 3.188	55.95 ± 3.760	
Whether it recurs	
 Yes	31.04 ± 3.057	42.86 ± 3.208	50.50 ± 1.354	
 No	33.33 ± 3.464	44.04 ± 3.340	55.94 ± 3.697	
Medical payment	
 At your own expense	28.00 ± 0.000	42.50 ± 0.707	51.00 ± 0.000	
 Full reimbursement	31.13 ± 3.137	43.92 ± 3.252	53.63 ± 2.925	
 Partial reimbursement	32.80 ± 3.483	43.77 ± 3.376	55.60 ± 3.934	
Your breast cancer location	
 Left	32.80 ± 3.358	43.72 ± 3.339	55.52 ± 3.937	
 Right	27.00 ± 2.646	45.00 ± 3.742	51.00 ± 0.000	
 Both side	32.50 ± 2.121	45.00 ± 0.000	53.50 ± 1.732	
Bfs	55.33 ± 11.261	62.2. ± 7.825	73.46 ± 11.219	
Dci	102.90 ± 16.311	111.88 ± 7.989	129.94 ± 13.936	
Pss	29.83 ± 9.223	27.25 ± 4.656	16.96 ± 10.337	
Faces	32.54 ± 3.483	43.77 ± 3.338	55.39 ± 3.894	
BFS benefit finding scale, DCI dyadic coping inventory, PSS Perceived Stress Scales, FACES Family Adaptability and Cohesion Evaluation Scales.

Across the three family adaptation categories, a statistically significant majority of patients were married for the first time, had a personal monthly income of more than 8,000 yuan (RMB), had a family history of breast cancer, had cancer in situ, had undergone radical mastectomy and lymph node dissection, and had no recurrence.

Multinomial logistic regression of family adaptation profiles

Low and High levels were referenced in this study, with family adaptation categories as the dependent variable, demographic variables that were statistically significant in the univariate analysis as independent variables, and correlates explored through multinomial logistic regression. The results showed no significant differences in marital status and surgery mode among the three family adaptation level categories. Compared with "low-level family adaptation," (1) "high-level family adaptation" is affected by personal monthly income of 1001–3000 yuan(OR = 0.131, P = 0.01), breast cancer recurrence(OR = 0.303, P = 0.04), benefit finding(OR = 1.093, P = 0.002), dyadic coping(OR = 1.153, P = 0.000), and Perceived Stress(OR = 0.923, P = 0.025). (2) "Medium level family adaptation" is affected by personal monthly income of 1001–3000 yuan(OR = 0.298, P = 0.021), family history of breast cancer(OR = 2.64, P = 0.043), type of breast cancer in situ(OR = 22.266, P = 0.022), benefit finding(OR = 1.065, P = 0.003), and dyadic coping(OR = 1.068, P = 0.000). In contrast to "high-level family adaptation," “medium-level family adaptation" is affected by dyadic coping (OR = 0.926, P = 0.000) and perceived stress(OR = 1.079, P = 0.005)(Table 6) .Table 6 Multinomial logistic regression of depression profiles.

Variable	Low vs high	Low vs medium	Medium vs high	
OR (95%CI)	P	OR (95%CI)	P	OR (95%CI)	P	
Marital status	
 First marriage	2.299(0.710–7.422)	0.165	1.902(0.874–4.136)	0.105	0.828(0.312–2.196)	0.703	
Personal monthly income	
 < 1000	0.546(0.028–10.872)	0.692	0.160(0.009–2.912)	0.216	0.292(0.017–5.053)	0.398	
 1001–3000	0.131(0.028–0.615)	0.010	0.298(0.107–0.831)	0.021	2.268(0.612–8.405)	0.221	
 3001–5000	0.355(0.087–1.877)	0.152	0.739(0.250–2.190)	0.585	2.077(0.736–5.864)	0.167	
 5001–8000	0.611(0.199–1.877)	0.390	0.935(0.404–2.161)	0.874	1.528(0.657–3.556)	0.325	
Whether there is a family history of breast cancer	
 Yes	2.121(0.620–7.256)	0.231	2.64(1.030–6.792)	0.043	1.247(0.526–2.958)	0.616	
Your type of breast cancer	
 Carcinoma in situ	16.154(0.592–440.738)	0.099	22.266(1.574–314.869)	0.022	1.378(0.063–29.963)	0.838	
What kind of breast cancer surgery did you have	
 Radical mastectomy + lymph node dissection	0.785(0.192–3.215)	0.737	1.322(0.393–4.452)	0.652	1.684(0.668–4.245)	0.269	
 Modified radical mastectomy + lymph node dissection	0.393(0.092–1.675)	0.207	0.820(0.241–2.783)	0.750	2.086(0.779–5.588)	0.143	
Whether it recurs	
 Yes	0.303(0.097–0.948)	0.040	0.540(0.252–1.161)	0.115	1.784(0.691–4.608)	0.232	
BFS	1.093(1.033–1.155)	0.002	1.065(1.022–1.110)	0.003	0.975(0.934–1.018)	0.250	
DCI	1.153(1.102–1.206)	0.000	1.068(1.034–1.103)	0.000	0.926(0.895–0.958)	0.000	
PSS	0.923(0.860–0.990)	0.025	0.996(0.944–1.050)	0.870	1.079(1.023–1.137)	0.005	
BFS benefit finding scale, DCI dyadic coping inventory, PSS Perceived Stress Scales.

Discussion

In this study, LPA was used to group the family adaptation level of breast cancer patients. Based on the scores, we identified three different types of groupings, namely "low-level family adaptation "(21.5%), "medium-level family adaptation" (47.8%), and "high-level family adaptation" (30.6%).

As shown in Fig. 2, in our study, the results of "medium-level family adaptation" and "high-level family adaptation" were more prominent in item 5 (in the family, we take turns to share different chores), item 7 (in the family, members give in to each other to achieve compromise when there is conflict in the family), and item 9 (The idea of educating children is sound). Previous studies have shown that in A well-adjusted family, Family members are willing to take on their obligations, and compromise is possible when problems arise40,41, reflecting the virtues of love, filial piety, and loyalty in Chinese culture42. When family members suffer from illness, they can be considerate, empathetic, assume patients' original family responsibilities, and help the family overcome the crisis43. Patients' families with low-level family adaptation had lower scores in item 5 (in the family, we take turns sharing different household chores) than those with medium- and high-level family adaptation. This also reflects that when one of the family members is ill and cannot undertake the original responsibility, other family members can undertake the responsibility of the patient so that the family can better overcome the crisis41. In addition, people with "high levels of family adaptation" scored lower on item 14 (When there is conflict in the family, family members will not express their ideas). This may be due to family members being afraid to confront conflicts and arguments for fear of exacerbating the conflict or causing a bigger problem, and therefore, choosing to keep their thoughts to themselves to avoid an unpleasant situation44. People with " medium-family adaptation" scored lowest in item 13 (at home, family members are free to make their demands). This may be because, in some family cultures, people have fixed roles and expectations that cause some family members to feel that making their demands is inappropriate or untraditional. These norms and traditions sometimes prevent people from expressing their needs and desires45.

According to our findings, marital status, personal monthly income, family history of breast cancer, type of breast cancer, type of surgery, recurrence, “benefit finding”, “dyadic coping”, and “Perception Stress “ are all factors that influence family adaptation in breast cancer patients. Patients' marital status has an essential influence on the level of family adaptation. In our study, we found that remarried patients had better family adaptation than first-married patients. This may be because, remarried patients, they have a fuller understanding of marriage and family relationships and are, therefore, better able to cope with challenges. In addition, patients who remarry may be more mature in conflict resolution and increased communication and able to emerge from crises more effectively. Previous research has found that a close relationship between couples can help patients gain support and understanding, and this support can enable patients to cope better with the disease46. Moreover, The understanding and support of the spouse can reduce the psychological burden of the patient and make the patient respond to the crisis with a positive attitude47. Couples develop coping strategies together, support and understand each other, and work together to find ways to solve problems. This positive coping can reduce psychological stress for patients and family members48. Clinical staff should provide psychological support and education to help patients with first marriages improve family adaptation. In addition, marriage counselling, coping skills training, and effective communication strategies can be provided to patients and their spouses to help them better cope with family challenges. The results of this study show that high-income families weathered the crisis better than low-income families, consistent with previous research findings49. Higher incomes mean families have easier access to the resources needed for basic living, including food, housing, health care, and education. These resources can help family members cope better with challenges and stress50. In addition, patients with low personal monthly income are often stressed by the cost of treatment during the treatment process, which could be more unconducive to patients surviving the crisis51. Therefore, clinical staff can advise low-income people to actively seek appropriate medical insurance or social benefits and policies to ease the financial pressure brought about by treatment costs. Our findings suggest that the type of breast cancer is also an essential factor in a patient's family adaptation. Different types of breast cancer require different treatments, including surgery, radiation, chemotherapy, targeted therapy, etc. Some treatments may require longer recovery, affecting family members' living and work schedules52. In addition, different treatments can have different effects on the body, such as fatigue, nausea, hair loss, etc. These side effects may affect the patient's daily life and ability to work, requiring more support and help from family members53. Therefore, clinical staff need to provide more psychological support to patients with higher malignancy so that patients understand that they are not alone in fighting the disease. Encourage patients to maintain a positive attitude towards life, help them find the meaning of life, and improve their confidence in treatment and rehabilitation. Our findings suggest that a family history of breast cancer can influence family adaptation. This may be due to their fear that other family members will develop the same disease, thus increasing feelings of anxiety and fear among family members. This constant anxiety and fear can affect the mental health and daily life of family members, which in turn can cause conflict and discomfort among family members54. Therefore, clinical staff should promptly provide genetic counselling services for patients with a family history of breast cancer and their families and take corresponding prevention and screening measures. Second, patients with a family history of breast cancer and their families are advised to undergo regular breast cancer screening, including mammograms and breast ultrasounds. In addition, clinical staff should closely observe the patient's physical condition and detect any abnormalities in time. The type of surgery for breast cancer can affect a patient's family adaptation. This is due to the impact that a mastectomy can have on the sex life and relationship between the patient and the partner. Patients may face challenges with body image discomfort, while partners may need to adjust to a new sexual lifestyle. This condition can lead to strained relationships and reduced family adaptation55. Therefore, clinical staff should provide patients with detailed surgical information and follow-up care plans before surgery to ensure that patients fully understand the purpose, process and possible results of surgery to reduce their anxiety and fear. In addition, for patients who are unable to undergo mastectomy, we can recommend breast augmentation surgery when the patient is in good health. In our findings, 'relapse or not' affects the patient's family adaptation. This may be because cancer recurrence requires family members to readjust their daily routines and take on different family roles. Family members may need to take on the responsibility of caring for the patient, which may lead to conflict between family members56. In addition, cancer recurrence may be accompanied by a longer and more expensive course of treatment, which can put a financial burden and stress on families57. Therefore, clinical staff should take the patient as the centre when nursing patients with cancer recurrence, pay full attention to the physical, psychological and social needs, and provide professional care and support to help patients recover as soon as possible and improve the quality of life. At the same time, we should also pay attention to the opinions and needs of patients and their families and establish a good cooperative relationship with them to face challenges together.

"Benefit finding" is a cognitive adaptation method that people adopt to actively cope with the external environment, which refers to finding benefits from adverse life events58. Our study found that "benefit finding" can influence a patient's family adaptation. Previous research has confirmed this view59. This may be because family members are more willing to respond positively to a crisis, such as paying more attention to the patient's health status and actively participating in rehabilitation programs and treatment. In addition, "benefit finding" allows patients to approach challenges positively60. Therefore, clinical staff can help patients develop a positive attitude to deal with challenges and difficulties and encourage them to find hope in difficult situations.

"Dyadic coping" means that both spouses deal with crisis events together32. Consistent with previous findings61,62, our findings suggest that 'dyadic coping' can influence patients' “family adaptation”. Zhang Nan et al. study pointed out that the proactive response of both spouses to stressful events will improve the adaptability of the whole family21. The positive response of both spouses can promote the unity of family members, provide better support for patients, contribute to patients' recovery, and improve the quality of life63. Clinical staff can encourage couples to collaborate to deal with the disease together. This includes taking part in medical decisions, making treatment plans, etc. By working together, couples can better support and understand each other and support each other as they cope with the disease. In addition, Clinical staff can listen to the feelings and needs of both spouses and provide emotional support, encourage them to share each other's concerns and frustrations and help them face challenges together.

Consistent with previous findings38,64, our findings suggest that "Stress" can affect patients' "family adaptation." This may be because the patient is stressed during the treatment of the disease, with problems such as mood swings, anxiety and depression. These emotional problems can affect their family relationships65,66. In addition, cancer patients find it difficult to express their needs and feelings because of physical discomfort, resulting in family members being unable to understand the patient's true thoughts, increasing the conflict within the family67. Clinical staff can teach patients emotional management skills, such as deep breathing, relaxation training, and other methods, to help them cope with stress, calm down emotions, and maintain mental balance.

Conclusions

The "family adaptation" of breast cancer patients is heterogeneous among individuals. It can be divided into three types: low-level, medium-level, and high-level family adaptation. Moreover, different categories of "family adaptation" have differences in personal monthly income, whether there is a family history of breast cancer, the type of breast cancer, whether there is a recurrence," Dyadic coping ", "Benefit finding", and " Perception Stress ". Nursing staff should timely find the low level of family adaptation of the population, provide them with family as a whole care, and help breast cancer patients through the crisis with a positive attitude to cope with the pressure and challenges to improve the quality of life of patients.

Limitations

This study has the following limitations : (a) This study is the first to use LPA to explore family adaptation in patients with different characteristics of breast cancer, so more research is needed to support our findings. (b) The cross-sectional study design does not allow for establishing causal relationships between variables and only allows discussion of factors influencing family adaptation. Therefore, a longitudinal study design is recommended in the future. (c) The sample is only from Liaoning Province in northern China, which may limit its representativeness. Future researchers are advised to recruit larger samples from more regions of China or other regions。

Supplementary Information

Supplementary Information 1.

Supplementary Information 2.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-72410-2.

Acknowledgements

The authors wish to acknowledge the cooperation of all those who participated in this study.

Author contributions

Z.D and Y.F. developed the study design, organized the sample recruitment, collected data, and contributed to writing the manuscript’s introduction, discussion, and references sections. C.H. contributed to the study design and writing of the manuscript’s introduction, discussion, and reference sections. E.L. assisted in the data collection and research design. Y.F. contributed to the research design and literature review of this study. All authors read and approved the final manuscript.

Funding

This work was supported by the doctoral research Fund of Wannan Medical College (Approval No. WYRCQD2023043). Funders have no role in research design, data collection and analysis, publication decisions, or manuscript preparation.

Data availability

The dataset used and analysed during the current study is available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.

Ethical approval

This study was conducted by the ethical standards of the Helsinki Declaration and approved by the Ethics Committee of Jinzhou Medical University (approval number: JZMULL2023026). All participants provided written informed consent.

Publisher's note

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

These authors contributed equally: Zhangyi Ding, Yarong Fan, Enguang Li, and Fangzhu Ai.
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