The impact of adverse childhood experiences and social support on psychological abuse of elderly females in rural areas of China: a cross-sectional study

Abstract

Background

As the population continues to age rapidly, the issue of elder abuse has become increasingly prominent. Compared to men, elderly women generally encounter greater challenges and are more susceptible to abuse, with psychological abuse being the most prevalent form. Psychological abuse adversely affects both the physical and mental health of older adults, and even results in premature mortality. This study aims to explore the impact of adverse childhood experiences and social support on psychological abuse among elderly females in rural areas of China.

Methods

A cross-sectional questionnaire survey was conducted to investigate psychological abuse and its influencing factors among elderly females in Hebei Province, China. Participants were surveyed using a demographic questionnaire, perceived social support scale (PSSS), adverse childhood experiences questionnaire, and elder psychological abuse scale. Hierarchical multiple regression was conducted to examine the association between adverse childhood experiences, social support, and psychological abuse.

Results

A total of 455 elderly females participated in the study, with an effective response rate of 96.25%. Hierarchical multiple regression analysis revealed that age, marital status, source of income, monthly income, presence of chronic diseases, satisfaction with life, and weekly social frequency were significantly associated with psychological abuse scores among older women. Entering adverse childhood experiences and social support in separate blocks raised the explained variance by 2.9% and 5.6% (F = 28.461, 33.880; all p < 0.001). Social support partially buffered the impact of adverse childhood experiences on psychological abuse.

Conclusions

This research demonstrated that adverse childhood experiences and social support were significantly associated with the severity of psychological abuse among elderly females. Elderly females who had experienced three or more types of adverse childhood events exhibited higher levels of psychological abuse. Future research should focus on developing targeted interventions based on identified relevant factors to improve the mental well-being of elderly females, and enhance their quality of life in later years.

Background

According to a report by the World Health Organization (WHO), the global population aged 60 and older is projected to reach 1.4 billion by 2030, accounting for approximately one-sixth of the total population. By 2050, this figure is expected to more than double. Among this population, elderly females represent a significant portion, and their numbers are continuously increasing, with projections indicating that they will exceed 1 billion by 2050 [1]. Meanwhile, data from the National Bureau of Statistics of China indicate that by the end of 2024, the population of individuals aged 60 and older in China reached 310 million, accounting for 22.0% of the total population. Notably, the proportion of elderly women in China is significantly higher than that of elderly men, and their life expectancy is notably greater [2]. In the context of a globally aging society, research on elder abuse has gained increasing importance, particularly for females. Elder abuse is a global public health and human rights problem [3]. Elder abuse is classified into five types, including psychological abuse (PA), physical abuse, neglect, financial abuse, and sexual abuse. Among these, psychological abuse is the most prevalent [4]. However, due to its often-concealed nature, there is less research on psychological abuse compared to neglect and physical abuse.

Psychological abuse refers to behavior meant to inflict emotional agony or harm on elderly people, including insults, threats, humiliation, disrespect, and controlling behavior [5]. Among the five major forms of elder abuse, PA exerts the most direct and pronounced impact on the mental health of older adults. Numerous studies have demonstrated that older adults who experience PA are more susceptible to anxiety, depression, sleep disorders, and even suicidal thoughts [6–8]. Furthermore, long-term PA can result in a range of physiological consequences for older adults, including chronic pain, gastrointestinal disorders, stress-related symptoms, gynecological issues, chest pain [9–11]. A longitudinal study in rural Malaysia found that females who experienced PA had nearly a threefold increase in mortality risk [12]. A prospective study involving 9,831 elderly people reported that those who experienced PA were nearly 4 times more likely to have metabolic disorders compared to their intact counterparts [13]. Therefore, elder abuse leads to medical consequences that extend beyond a single health domain and reverberate across multiple physiological systems.

PA is common among the elderly, but its incidence varies in different countries. A systematic review of 52 studies conducted in 28 countries reported that the global prevalence of overall elder abuse among women in the past year was 14.1%, with PA being the most common type (11.8%) [14]. The research indicated that the incidence of PA among European countries varies between 19.4% and 34%, and this occurred more often in Sweden (29.7%) and Poland (27.1%) [15, 16]. A survey conducted in Europe on PA against elderly women revealed that 23.6% of participants reported experiencing PA [17]. A nationally representative study in the United States found that PA had the highest prevalence, ranging from 4.6% to 9% [18, 19]. The prevalence of PA in Korea was 9.4%~11% [20, 21]. The prevalence of PA in Japan ranged from 11.12% to 50% [22, 23]. Research on PA among the elderly in China began relatively recently, and the subsequent studies were poor. A study involving 7,466 elderly individuals randomly recruited from six regions in China found that the prevalence of PA in this population was 22.84% [24]. An investigation was carried out on 2036 elderly people in a rural area in Hubei, China. The incidence of elder abuse was 36.2%, with PA accounting for the largest percentage (27.3%) [25]. The prevalence of PA among rural older women in Anhui Province was 72.9% [26]. Notably, rural older women constitute a particularly vulnerable group. Because of their longer life expectancy and accompanying physical and cognitive decline, elderly females in rural areas face a substantially higher risk of PA limitations than older men [15]. Therefore, it is of great significance to analyze the influencing factors of PA experienced by elderly females in rural areas.

The key factors that contribute to elderly people being vulnerable to PA can be broken down into three categories, including the characteristics of the elderly, their caregivers and the social environment. Gender is an important factor in PA. Notwithstanding older men as well experience abuse, studies provide evidence that women are more often victims of abuse than men [23]. Current research indicates that the age, education level, economic status, and physical condition of elderly adults all influence their experiences of PA [23, 27]. Caregiver-related factors, including stress levels, emotional status, and family relational, is significantly associated with the occurrence of PA [8]. The residential area and social network are also associated with PA [28, 29]. Due to cultural and regional differences among various countries, the causes of PA against the elderly may differ significantly. However, existing work has concentrated on short-term, individual factors, leaving unclear how distal social factors over the life course influence the risk of PA.

Adverse childhood experiences (ACEs) are distal social determinants that exert enduring effects on PA and warrant further investigation in both Western and Chinese contexts [30]. ACEs refer to the frequent and intense stressful or traumatic events individuals encounter before the age of 18 [31]. The Cumulative Disadvantage Theory (CDT) provides a strong framework for interpreting the long-term effects of ACEs. Originally proposed by sociologist Robert K. Merton in 1968, the theory was developed to explain the Matthew effect in the scientific community—the phenomenon whereby the rich get richer and the poor get poorer [32]. CDT posits that a minor disadvantage or negative event in early life, through interacting social, economic, psychological, and health mechanisms, becomes progressively magnified across the life course, ultimately yielding substantial disparities in outcomes in later life [30]. This theory was subsequently applied widely in fields such as sociology, education, economics, and gerontology. A growing number of studies grounded in CDT indicates that ACEs elevate the risk of encountering subsequent negative events. ACEs, as major adverse events in early life, accumulate over time and are associated with progressively greater vulnerability in later physical and mental health. These experiences can trigger a cascade of negative outcomes throughout their lives, including chronic illnesses, declining health, depression, suicidal ideation, and late-life dementia [33–36]. This cumulative burden can affect neurodevelopment, emotional regulation, and interpersonal relationship patterns, thereby increasing the risk of experiencing PA in adulthood [37, 38]. These factors may subsequently contribute to the psychological maltreatment of older adults.

Social support, which encompasses care, understanding, comfort, guidance, and assistance from family, friends, and the broader environment, serves as a crucial indicator of social health [39]. The Social Support Theory (SST) provides a fundamental framework for understanding its protective effects. According to SST, emotional, informational, instrumental, and evaluative resources obtained through formal or informal networks buffer the adverse impact of stressful events on physical and mental health, thereby sustaining well-being [40]. This theory operates primarily through two models: the main-effect model posits that social support exerts a universal and direct beneficial impact on an individual’s physical and mental health, regardless of whether the individual experiences stress; the buffering model further indicates that social support primarily functions when individuals confront stressful life events, enhancing coping skills and attenuating stress responses [41]. Within this framework, it is hypothesized that higher levels of social support not only reduce the risk of PA among rural older women but also mitigate emotional trauma and negative consequences after abuse occurs. The research indicates that greater social support can create a protective environment, reducing the likelihood of victimization and alleviating harm when abuse occurs [42, 43]. Therefore, this study examines social support as a protective factor against PA among rural older women.

However, the current situation of psychological abuse, social support and adverse childhood experience among Chinese elderly females in rural areas has not been investigated, limiting the potential to develop personalized interventions to prevent their psychological abuse. Therefore, the purpose of this study is to: explore the impact of adverse childhood experience and social support on psychological abuse among elderly females in rural areas of China.

Methods

Research design

This study used a cross-sectional design to examine the associations of adverse childhood experiences and social support with psychological abuse among rural older women.

Setting and study sample

The study utilized a self-report assessment to evaluate psychological abuse among Chinese elderly females living at home. The sample was composed of 455 elderly females. Participants were recruited from Hebei province in northern China. The inclusion criteria were elderly females aged ≥ 60, who had chosen home care. This study excluded participants who had been diagnosed with a cognitive impairment or a linguistic disability.

Data collection

Before the survey, all researchers received uniform training to ensure the consistency of study results. Two researchers, as a team, conducted a survey of elderly females with informed consent. The elderly females were informed of the purpose, significance, cooperation, and confidentiality of the study before beginning the survey. The elderly themselves filled out the questionnaire. However, for elderly people who did not fill in the questionnaire on their own due to physical limitations or low literacy, the researchers read the questionnaire content in a neutral tone and recorded their answers. If conditions permit, the elderly people should fill in the questionnaire in a quiet and private place to ensure the reliability of the survey content.

Measurement instruments

The sociodemographic questionnaire

The sociodemographic information included 12 variables, including age, marital status, education level, living style, source of income, monthly income, number of children, self-rated health status, number of chronic diseases, life satisfaction and social frequency.

Elder psychological abuse scale in domestic setting

This scale was developed by Jie [44]. The scale consisted of 16 items divided into 4 dimensions: disrespect (5 items), isolation (3 items), threat (3 items), and control (3 items). The scale has a Likert range of 1 to 5, and the scores for “never/not applicable, occasionally, sometimes, often, always” were 1, 2, 3, 4, and 5 points, respectively. Higher scores indicate greater levels of psychological abuse experienced by elderly people. The scale demonstrated a Cronbach’s α score of 0.954 [44]. In this study, the Cronbach’s alpha coefficient for the scale was 0.876.

Perceived social support scale, PSSS

This scale was developed by Zimet et al. [45]. It has the objective of evaluating social support of self-realization. The scale was divided into three dimensions: family support (4 items), friend support (4 items) and other support (4 items). Each items is scored on a 7-point Likert scale (from 1 = extremely disagree to 7 = extremely agree), with higher scores indicating better social support. The scale was reliable and valid, with a Cronbach’s α score of 0.88 [46]. In this study, the Cronbach’s alpha coefficient for the scale was 0.943.

Adverse childhood experiences questionnaire

Exposure to ACE was assessed using the ACEs questionnaire, which addresses 10 individual ACEs under three categories: (1) abuse: psychological, physical and sexual abuse; (2) neglect: psychological and physical neglect; (3) household dysfunction: parental separation/divorce, violence against mother, household substance abuse, household mental illness and incarceration of household member. All questions about ACEs pertained to the respondents’ first 18 years of life and were binary (“Yes” vs. “No”). We calculated a total ACE score for each participant (1 for each of the 10 types of ACE reported). The scale demonstrated a Cronbach’s α score of 0.84 [47]. In this study, the Cronbach’s alpha coefficient for the scale was 0.714.

Ethical considerations

The research protocol has received ethical approval from the Medical Ethics Committee of Tianjin University of Traditional Chinese Medicine. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. The collected data did not include any identifiable information about the participants (e.g., ID number). This study adhered to the ethical criteria outlined in the Helsinki Declaration of 1995 (revised in Edinburgh in 2000), including the principles of autonomy, confidentiality, and non-maleficence. During the entire research process, the participants’ rights and willingness were fully considered.

Data analysis

The IBM SPSS statistical software (version 26.0) was used for all of the analyses. Continuous variables were described by means and standard deviation (SD). Categorical variables were described by counts and percentages. To assess differences in psychological abuse scores across demographic characteristics, we employed independent Student’s t-tests for binary variables and analysis of variance (ANOVA) for categorical variables with three or more groups. Post-hoc comparisons were conducted using the Least Significant Difference (LSD) test, a method for comparing the means of multiple groups after a significant overall difference is indicated by ANOVA. Pearson’s or Spearman’s correlations were used to examine the correlations among various variables.

Hierarchical multiple regression was used to identify factors associated with PA in rural older abuse, with a significance level set at p = 0.05. This statistical method was chosen to systematically examine the unique contributions of different variable groups to predicting PA, while controlling for potential confounding factors. PA was used as the dependent variable. In the first step, demographic characteristics (e.g., age, marital status) were included as independent variables to establish a baseline model. In the second step, ACEs were incorporated as independent variables to examine their additional explanatory value for PA beyond demographic characteristics. In the third step, total PSSS scores were entered to assess their incremental prediction of PA after accounting for demographic characteristics and ACEs. This hierarchical approach enabled us to assess whether social support and adverse childhood experiences significantly enhanced the model’s explanatory power. In this study, most independent variables had variance inflation factors (VIFs) between 1 and 3, with a maximum VIF of 5.721, which was below 10, indicating that multicollinearity was not a serious issue.

Results

Demographic profile of participants

The final number of respondents was 455, and all were China in rural area elderly females aged 60 years and over (mean = 70.48, SD = 7.267). Additional demographic data is displayed in Table 1.

Table 1.

Relationship between demographic factors and the correlates of psychological abuse among rural older women (n = 455)

Variables	n (%)	Mean ± SD	t/F	p-value
Age			57.997	< 0.001
60 ~ 69	213 (46.8)	28.58 ± 5.51
70 ~ 79	184 (40.4)	29.66 ± 6.48
≥ 80	58 (12.7)	38.71 ± 8.99
Marital status			48.005	< 0.001
Spinsterhood/Divorced	6 (1.4)	26.50 ± 4.76
Married	341 (74.9)	28.67 ± 5.31
Widowed	108 (23.7)	35.69 ± 9.53
Education level			8.041	< 0.001
Illiteracy	204 (44.8)	31.70 ± 7.81
Primary	152 (33.4)	30.26 ± 7.46
Middle	62 (13.6)	27.94 ± 4.14
>Middle	37 (8.1)	26.81 ± 3.67
Number of children			−3.547	< 0.001
0 ~ 2	145 (31.9)	28.58 ± 5.80
≥ 3	310 (68.1)	31.12 ± 7.64
Living style			15.362	< 0.001
Live alone	64 (14.1)	33.89 ± 8.93
Live with spouse	186 (40.9)	28.31 ± 5.56
Live with children	72 (15.8)	33.17 ± 9.60
Live with spouse and children	133 (29.2)	29.83 ± 5.56
Source of income			8.370	< 0.001
Own income	106 (23.3)	29.33 ± 6.07
Pension	43 (9.5)	27.70 ± 5.26
Spouse income	102 (22.4)	29.09 ± 5.56
Child payment	176 (38.7)	31.34 ± 7.55
Government welfare subsidy	28 (6.2)	35.96 ± 11.81
Monthly income (RMB)			39.311	< 0.001
≤ 500	135 (29.7)	35.47 ± 7.91
501 ~ 1000	164 (36.0)	29.59 ± 6.36
1001 ~ 1500	67 (14.7)	28.01 ± 5.01
1501 ~ 2000	75 (16.5)	25.83 ± 3.22
> 2000	14 (3.1)	24.00 ± 1.62
Self-rated health status			48.766	< 0.001
Extremely poor	25 (5.5)	38.92 ± 10.92
Poor	87 (19.1)	36.10 ± 7.61
Fair	156 (34.3)	29.91 ± 6.40
Good	146 (32.1)	26.86 ± 3.51
Extremely good	41 (9.0)	26.56 ± 3.29
Number of chronic diseases			61.099	< 0.001
0	50 (11.0)	38.46 ± 8.42
1	159 (34.9)	27.09 ± 4.33
≥ 2	246 (54.1)	30.73 ± 7.02
Disability Yes No	28 (6.2) 427 (93.8)	31.46 ± 8.80 30.23 ± 7.09	0.877	0.381
Life satisfaction			76.068	< 0.001
Dissatisfaction	25 (5.5)	40.04 ± 9.86
Less satisfied	59 (13.0)	38.41 ± 7.62
Fair	121 (26.6)	31.50 ± 6.70
Less satisfaction	160 (35.2)	27.28 ± 3.61
Satisfaction	90 (19.8)	26.08 ± 3.16
Social frequency (Times/week)			91.044	< 0.001
≤ 1	51 (11.2)	40.39 ± 7.96
2 ~ 3	144 (31.6)	32.65 ± 7.67
4 ~ 5	193 (42.4)	27.43 ± 3.67
> 5	67 (14.7)	25.90 ± 2.70
ACE			67.652	< 0.001
0	94 (20.7)	26.52 ± 3.04
1	152 (33.4)	27.36 ± 3.73
2	78 (17.1)	30.63 ± 7.01
≥ 3	131 (28.8)	36.25 ± 8.55

Levels of psychological abuse, adverse childhood experiences, and social support among rural older women

Table 2 shows the scores for psychological abuse and social support. The mean psychological abuse score was (30.31 ± 7.20). The dimensions of disrespect and control received the highest and lowest scores, respectively. The total score for the PSSS was (55.95 ± 10.92), with family support highest and friend support lowest.

Table 2.

Scores of psychological abuse and social support among rural older women (n = 455)

Variables	Mean	SD	Min-max
Psychological abuse	30.31	7.20	19–59
Disrespect Isolation Threat	11.91 10.13 4.55	2.81 2.37 2.06	6–22 5–20 3–13
Control	3.72	1.30	2–11
Social support	55.95	10.92	29–74
Family support	19.28	4.23	8–27
Friend support	18.27	3.95	8–25
Other support	18.39	3.57	9–25

Of the 455 rural older women, exposure to ACEs was highly skewed. 79.3% reported at least one ACE, and 28.8% had multiple ACEs (three or more types). Childhood starvation was the most common (62.6%), whereas sexual abuse was the least common (2.2%).

Association between demographic characteristics and psychological abuse among rural older women

Independent-samples Student’s t-tests revealed a statistically significant difference in psychological abuse severity between older adults with 0–2 children and those with ≥ 3 children (t = − 3.547, p < 0.001). ANOVA revealed that the level of psychological abuse of the elderly females was significantly different in terms of age, marital status, education level, living style, source of income, monthly income, self-rated health status, number of chronic diseases, life satisfaction, social frequency and ACEs (p < 0.05) (Table 1).

Correlation of various variables among rural older women

Correlation analyses showed that PA correlated most strongly and positively with ACEs (r = 0.478, p < 0.01) and most strongly and negatively with social support (r = −0.636, p < 0.01). PA was also significantly negatively associated with monthly income, self-rated health, life satisfaction, and social participation (r = −0.544,−0.481, −0.568, and-0.553, all p < 0.01). Higher age and having more children were associated with higher PA scores (r = 0.292, 0.164, both p < 0.01). ACEs were significantly negatively correlated with social support (r = −0.586, p < 0.01) (Table 3).

Table 3.

Correlation of various variables among rural older women

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1.Age	1
2.Martial	0.405**	1
3.Education	− 0.347**	− 0.272**	1
4.Number of children	0.379**	0.166**	− 0.367**	1
5. Living style	− 0.134**	− 0.233**	0.097*	0.013	1
6. Source of income	0.475**	0.314**	− 0.297**	0.265**	0.017	1
7. Monthly income	− 0.354**	− 0.332**	0.337**	− 0.297**	0.034	− 0.329**	1
8. Self-rated health status	− 0.321**	− 0.285**	0.229**	− 0.158**	− 0.011	− 0.270**	0.465**	1
9. Chronic diseases	0.082	0.002	− 0.023	0.059	− 0.091	0.032	− 0.046	− 0.150**	1
10. Disability	0.037	0.007	0.027	0.021	− 0.015	− 0.038	0.020	0.030	− 0.054	1
11. Life satisfaction	− 0.190**	− 0.346**	0.207**	− 0.113*	0.015	− 0.181**	0.474**	0.659**	− 0.024	0.067	1
12. Social frequency	− 0.403**	− 0.310**	0.276**	− 0.173**	0.025	− 0.334**	0.466**	0.539**	0.018	− 0.040	0.550**	1
13.PSSS	− 0.179**	− 0.314**	0.292**	− 0.134 **	0.097*	− 0.149	0.444**	0.431**	− 0.027	0.051	0.571**	0.471**	1
14.ACEs	0.297**	0.355**	− 0.390**	0.240**	− 0.142**	0.234**	− 0.476**	− 0.415**	0.044	0.019	− 0.462**	− 0.431**	− 0.586**	1
15.PA	0.292**	0.312**	− 0.196**	0.164 **	0.004	0.156**	− 0.544**	− 0.481**	− 0.027	− 0.041	− 0.568**	− 0.553**	− 0.636 **	0.478**	1

Note: *p < 0.05, **p < 0.01

Hierarchical multiple regression analysis for psychological abuse among rural older women

Table 4 summarizes the value assignments for demographic characteristics. Hierarchical multiple regression was conducted with the total PA score as the dependent variable. Step 1 included demographic characteristics as predictors; Step 2 added the total ACEs score; Step 3 added the total PPSS score. Hierarchical multiple regression analysis showed that age, marital status, source of income, monthly income, number of chronic diseases, life satisfaction, social frequency, PSSS, and ACEs were significant predictors of PA.

Table 4.

Value assignments for demographic characteristics

Variables	Assigned value
Age	60 ~ 69 = 1; 70 ~ 79 = 2; ≥80 = 3
Marital status	Widowed (Z1 = 0, Z2 = 0); Married (Z1 = 1, Z2 = 0); Spinsterhood/Divorced(Z1 = 0, Z2 = 1)
Education level	Illiteracy (Z1 = 0, Z2 = 0, Z3 = 0); Primary (Z1 = 1, Z2 = 0, Z3 = 0); Middle (Z1 = 0, Z2 = 1, Z3 = 0); >Middle (Z1 = 0, Z2 = 0, Z3 = 1)
Number of children	0 ~ 2 = 1; ≥3 = 2
Living style	Live alone (Z1 = 0, Z2 = 0, Z3 = 0); Live with spouse (Z1 = 1, Z2 = 0, Z3 = 0); Live with children (Z1 = 0, Z2 = 1, Z3 = 0); Live with spouse and children (Z1 = 0, Z2 = 0, Z3 = 1)
Source of income	Government welfare subsidy (Z1 = 0, Z2 = 0, Z3 = 0, Z4 = 0); Own income (Z1 = 1, Z2 = 0, Z3 = 0, Z4 = 0); Pension (Z1 = 0, Z2 = 1, Z3 = 0, Z4 = 0); Spouse income (Z1 = 0, Z2 = 0, Z3 = 1, Z4 = 0); Child payment (Z1 = 0, Z2 = 0, Z3 = 0, Z4 = 1)
Monthly income	≤ 500 = 1; 501 ~ 1000 = 2; 1001 ~ 1500 = 3; 1501 ~ 2000 = 4; >2000 = 5
Self-rated health status	Extremely poor = 1; Poor = 2; Fair = 3; Good = 4; Extremely good = 5
Number of chronic diseases	0 = 1; 1 = 2; ≥2 = 3
Life satisfaction	Dissatisfaction = 1; Less satisfied = 2; Fair = 3; Less satisfaction = 4; Satisfaction = 5
Social frequency	≤ 1 = 1; 2 ~ 3 = 2; 4 ~ 5 = 3; >5 = 4

Higher PSSS scores were associated with lower PA among rural older women in China (β = −0.331, p < 0.001). Additionally, a greater number of ACEs was associated with higher levels of PA (β = 0.108, p = 0.008). After controlling for demographic variables, ACEs alone increased ΔR² by 0.029 (2.9%, p < 0.001) and adding social support raised ΔR² by an additional 0.056 (5.6%, p < 0.001). Together, the two factors explained 8.5% of the variance in PA (Table 5).

Table 5.

Hierarchical multiple regression analysis for psychological abuse among rural older women

Step	Variables	B	SE	Beta	t-value	p-value	R 2	Adjusted R2	F-value	p-value
1	Demographic characteristics						0.538	0.518	26.696	< 0.001
	Constant	46.892	1.936	-	24.220	< 0.001
	Age	1.455	0.446	0.140	3.263	< 0.001
	Martial (Married)	−2.820	1.034	−0.170	−2.728	0.007
Spinsterhood/Divorced		−5.255	2.161	−0.083	−2.432	0.015
Source of income (Child payment)		−2.488	1.044	−0.169	−2.383	0.018
Monthly income		−1.077	0.267	−0.171	−4.037	< 0.001
Life satisfaction		−1.804	0.321	−0.279	−5.624	< 0.001
Social frequency		−2.040	0.370	−0.247	−5.507	< 0.001
2	Adverse childhood experiences						0.567	0.547	28.461	< 0.001
	Constant	42.072	2.078	-	20.248	< 0.001
	Age	1.307	0.433	0.126	3.017	0.003
	Martial (Married)	−2.832	1.002	−0.171	−2.827	0.005
Spinsterhood/Divorced		−4.769	2.096	−0.076	−2.275	0.023
Source of income (Child payment)		−2.338	1.012	−0.158	−2.319	0.021
	Monthly income	−0.904	0.261	−0.144	−3.468	0.001
	Life satisfaction	−1.494	0.316	−0.231	−4.728	< 0.001
	Social frequency	−1.858	0.361	−0.225	−5.151	< 0.001
	ACEs	1.418	0.263	0.219	5.400	< 0.001
3	Social support						0.622	0.603	33.880	< 0.001
	Constant	51.601	2.291	-	22.528	< 0.001
	Age	1.410	0.406	0.136	3.474	0.001
	Martial (Married)	−2.973	0.938	−0.179	−3.170	0.002
Spinsterhood/Divorced		−4.352	1.963	−0.069	−2.217	0.027
Source of income (Child payment)		−2.034	− 0.949	−0.138	−2.144	0.033
	Monthly income	−0.820	0.244	−0.130	−3.358	0.001
	Chronic diseases	−0.953	0.328	−0.081	−2.602	0.010
	Life satisfaction	−0.782	0.309	−0.121	−2.527	0.012
	Social frequency	−1.449	0.341	−0.175	−4.242	< 0.001
	ACEs score	0.700	0.262	0.108	2.669	0.008
	PSSS score	−0.218	0.028	−0.331	−7.881	< 0.001

Discussion

This study addresses a critical gap in the literature by illustrating the relationship among the related factors and psychological abuse. It highlights the importance of contextual factors such as ACEs, social support, age, marital status, source of income, monthly income, presence of chronic diseases, satisfaction with life, and weekly social frequency in relation to psychological abuse among rural older women. These findings provide valuable insights into the factors related to psychological abuse among rural older women and offer a foundation for targeted interventions to reduce psychological abuse and improve quality of life in older age.

The mean total score of PA among older women was (30.31 ± 7.20), exceeds those reported in previous related studies [29]. This variation can be attributed to differences in populations and geographic regions. Firstly, the subjects of this study were all female. Previous studies have indicated that older women experience a higher incidence and greater severity of PA compared to older men [15]. Compared to males, females are more susceptible to PA due to a higher rate of widowhood, lower educational attainment, economic dependence, and longer average lifespan [14, 18]. In addition, the participants in this study resided in rural areas. The economic conditions, aged care resources, and social security mechanisms in rural areas are relatively underdeveloped, insufficient, and fragmented when compared to urban areas. For this reason, older people in rural areas are more prone to psychological abuse.

Relationship between psychological abuse and adverse childhood experiences

This study found that the severity of PA among older women escalated when the number of ACEs increased, particularly when three or more ACEs were reported. After controlling for demographic characteristics, ACEs still accounted for a small but statistically significant 2.9% of the unique variance in adult psychological maltreatment (β = 0.219, p < 0.001). A Malaysian study reported that the cumulative number of ACEs was significantly associated with the risk of PA, with individuals having three or more ACEs at higher risk [48]. Furthermore, a 2025 Japanese study confirmed that the severity of ACEs was positively correlated with the level of PA experienced in adulthood [49]. Additionally, a study conducted in China found that individuals with ACEs were at substantially increased risk for depression [50],a contribution that notably contributes to the incidence of PA [6].

From the perspective of CDT, adverse childhood experiences are not isolated events but rather the starting point of a long-term chain of disadvantage [30]. ACEs accumulated through multiple pathways. First, childhood abuse, neglect, or family dysfunction directly impair an individual’s mental health and social functioning. Second, these early traumas often lead to declines in educational and employment opportunities, increasing the likelihood of developing chronic diseases, disabilities, or depression in adulthood. Finally, the aggregation of these disadvantages heightens vulnerability to PA in old age. Therefore, the 2.9% unique contribution observed in this study should not be interpreted as evidence of limited influence; it should be regarded as a “visible fragment” within the long cumulative process.

Moreover, cumulative disadvantages extend beyond health outcomes, potentially exacerbating the risk of victimization in later life through mechanisms such as the atrophy of social networks, reductions in economic resources, and the loss of social roles. This suggests that although the direct effect of ACEs in statistical models appears limited, their long-term impact—generated through complex social and biological pathways—can not be overlooked. Therefore, future interventions should particularly focus on older women with high ACE levels by providing targeted psychological counseling, rebuilding social support networks, and offering chronic disease management to interrupt the cycle of cumulative disadvantage and reduce the likelihood and severity of PA.

Relationship between psychological abuse and social support

This study found that social support remained a significant negative predictor of PA even after controlling for demographic variables and ACEs (β = − 0.331, p < 0.001) and independently explained 5.6% of the variance. These finding support the main-effect model of SST, which posits that social support, as a sustainable resource, can generally mitigate the risk of individuals encountering adverse events [41]. For example, Chokkanathan [51] identified out that social support as a crucial protective factor against abuse, capable of alleviating the negative consequences of interpersonal strain and loneliness, thereby reducing both the incidence and severity of abusive encounters. Furthermore, a meta-analysis of 26 studies indicated that a pluralistic, heterogeneous, and non-burdensome social support network is more effective in reducing the risk of elder abuse than a single, emotionally burdensome relationship [28]. This underscores that the protective role of social support depends not only on its presence but also on its structure and quality.

Importantly, this study revealed the buffering effect of social support: after social support was entered, the standardized regression coefficient for ACEs predicting psychological abuse decreased from 0.219 to 0.108 (p < 0.001), indicating that social support partially buffered the relationship between ACEs and PA. This finding lends empirical support to the buffer model of SST, which suggests that social support can disrupt the life-course chain of cumulative disadvantage by enhancing psychological resilience, improving coping strategies, and alleviating interpersonal tension and loneliness [23, 52]. In other words, ACEs do not necessarily culminate in victimization in later years; rather, the presence of a robust adult support system can substantially attenuate their detrimental impact.

However, when the abuser is also the primary supporter, such as a spouse or adult children, the buffering effect of social support is notably weakened or even nullified. This phenomenon is particularly pronounced in the context of China [53]. Given the deep-rooted tradition of “family support for the elderly”, older women often rely heavily on family members for emotional and instrumental support. When such relationships devolve into “care as control” or “emotional blackmail”, the support network may transform into a risk network. In such instances, the absence of external non-familial support systems (such as neighborhood and community organizations) can trap elderly individuals in a structural dilemma of “nowhere to escape”. These findings highlight the imperative for targeted interventions aimed at strengthening social support frameworks, such as establishing support groups, community participation programs, and caregiver education, to reduce the incidence of PA among rural older women, particularly those with ACEs.

Demographic factors associated with psychological abuse

Compared with people aged 60 to 70, older women over 70 were more likely to experience PA, which aligned with the findings of studies conducted in other countries [15, 54]. This can be attributed to age advancing, which involves physiological decline and reduced self-care capacity, leading to increased dependence on family members for daily living and financial support. This elevates the caregiving burden on families and subsequently increases the risk of PA [55].

Compared to married elderly individuals, widowed seniors were more likely to experiencing PA. This was consistent with previous research findings [25]. The reasons may be manifold. Firstly, older women in rural areas lose emotional support from their spouses after widowhood. The loss of spousal support within the traditional family structure often results in emotional deprivation, diminished capacity to manage family affairs, and increased financial pressures, thereby increasing the vulnerability of older women to PA. In addition, Chiao et al. [56] found that marital status was a significant predictor of loneliness among older adults. Hubatkov et al. [57]further noted that loneliness is positively associated with increased risk of abuse. Finally, widowed elderly people often exhibit a more vulnerable mental state and are at increased risk of issues such as depression [58]. Notably, depression was a recognized risk factor for suffering from PA [46]. In the future, it is recommended to implement support programs and mental interventions to reduce the vulnerability of widowed elderly people, alongside increased dissemination of laws against abuse.

The study found that, older women whose primary source of income was financial support from their children demonstrated significantly lower levels of PA compared to those dependent on government subsidies. This finding contradicts the commonly held view that economic independence serves as a protective factor [59], underscoring the complexity of the interplay between the economic well-being of older adults and the cultural context of their families. With Chinese society, financial support from children carries profound symbolic significance related to filial piety. Such monetary assistance constitutes a fundamental means through which children fulfilled their filial obligations, conveying respect and care [60]. This form of support embodies family cohesion and intergenerational reciprocity [61]. As a result, elderly recipients of financial aid from their offspring tend to experience an enhanced sense of familial belonging and emotional value, which may serve to reduce the incidence of PA.

Our results showed that PA was negatively associated with monthly income. Du and Chen [62] identified economic status as a significant factor contributing to elder abuse. Older women in rural areas with low monthly income often lack the capacity for independent living and rely heavily on family members for financial support. This dependency exacerbates caregiver stress and can provoke behaviors such as verbal insults or restrictions on the autonomy of the elderly [29]. Therefore, higher monthly income among the older women significantly enhances their quality of life in later life and, to some extent, reduces the risk of PA. In rural China, the pension system requires further improvement to adequately meet the basic living needs of the elderly.

Contrary to expectation, this study found that older women without chronic diseases were more likely to experience psychological abuse than those with chronic diseases. Li and Chen indicated that among older adults in China with chronic illnesses and frailty, the risk of abuse was lower [63]. This may be because the presence of chronic diseases increases the likelihood that elderly individuals become central members within their family, prompting family members and the community to pay greater attention to their health and needs. Consequently, this attention may help diminish PA. In addition, the high burden of chronic diseases among older people may have contributed to the occurrence of false-negative results [64].

Psychological abuse was negatively associated with life satisfaction. A study in Turkey found a negative correlation between elder abuse and life-satisfaction assessments [65]. This phenomenon may represent a bidirectional, self-reinforcing vicious cycle. Older women with low life satisfaction may exhibit symptoms such as depression, anxiety, and self-neglect. This mental state is perceived by family members as a burden or trouble, which can further exacerbate PA. In addition, older women with low life satisfaction may withdraw from social interactions due to depression or mobility impairments [66]. This social isolation reduces their support networks, increasing their vulnerability to abuse.

Greater social participation frequency among older women was associated with a lower risk of PA. This was consistent with previous research findings [62]. Lower social interaction frequency will weaken the social network of the elderly, limits opportunities to establish new close relationships, and constrains channels for emotional expression, ultimately leading to social isolation [67]. It is important to note that social isolation elevates the risk of PA among elderly individuals [57]. In addition, according to social support theory, social loneliness can weaken the elderly’s support network, depriving them of essential protective resources and increasing their vulnerability to PA [68].

Limitations

This study has certain limitations. First, as a cross-sectional survey, it cannot establish causal relationships between related factors and psychological abuse or its underlying mechanisms, nor can it capture longitudinal changes in psychological abuse among rural older women. Second, all variables were self-reported; hence, the results may be susceptible to social desirability or recall bias. Finally, this study did not include dimensions of family relationship quality, such as parent–child closeness and intergenerational conflict, as core predictors or covariates. Consequently, key influences on PA may remain unmeasured. Future work should employ longitudinal, multi-region designs with larger samples and incorporate these family-dynamic variables as central predictors, to clarify the mechanisms through which family dynamics exacerbate or buffer PA among rural older women.

Conclusion

ACEs and social support were closely associated with the occurrence of PA. Social support partially buffered the impact of adverse childhood experiences on PA. To reduce PA among rural older women, a collaborative effort across multiple sectors is essential to address the underlying factors. Particular focus should be placed on vulnerable females in disadvantaged positions. Further research is critical for developing effective, systematic strategies and management systems to prevent elder psychological abuse.

Authors’ contributions

Li Pei oversaw the conceptualization, manuscript writing, and research supervision. Zeying Hao supervised and participated in data collection and wrote the initial draft. Zeying Hao, Limin Duan and Futing Cao performed data collection, software application, and data analysis, and validated the data. Xiaoli Pang provided methodological guidance on data analysis and delivered novel analytical insights. Haoying Dou was responsible for conceptualization, project administration, and funding acquisition.

Funding

The authors declare that financial support was received for the research, authorship, and/or publication of this article. This study was supported by the National Administration of Traditional Chinese Medicine’s Project of High-level Construction of Key Traditional Chinese Medicine Disciplines (zyyzdxk-2023008) and the Key Project of Undergraduate Teaching Quality and Teaching Reform Research Program of Tianjin Ordinary Higher Education Institutions (No. A231006302).

Data availability

The original contributions presented in this study are included in this article/supplementary material, further inquiries can be directed to the corresponding author.

Declarations

Ethics approval and consent to participate

The research protocol has received ethical approval from the Medical Ethics Committee of Tianjin University of Traditional Chinese Medicine. During the entire research process, the participants’ rights and willingness were fully considered. All participants provided written informed consent prior to participation.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.