Published online Jun 19, 2026. doi: 10.5498/wjp.v16.i6.117084
Revised: January 19, 2026
Accepted: February 26, 2026
Published online: June 19, 2026
Processing time: 176 Days and 23.9 Hours
Supracondylar humeral fracture surgery represents a potential medical traumatic stressor in school-age children, yet data on the incidence of postoperative acute stress disorder (ASD) and its determinants in this population remain limited.
To determine the incidence of ASD after supracondylar humeral fracture surgery in school-age children and to identify independent risk and protective factors to support early risk stratification and targeted psychological interventions.
A retrospective study design was employed, including 284 school-age children (aged 6-12 years) who underwent supracondylar humeral fracture surgery in the orthopedic department of our hospital from June 2023 to March 2025. Demogra
Among 284 children, 23.6% developed ASD. The ASD group showed highest scores in intrusive symptoms and negative alterations in cognitions and mood dimensions. The detection rate of anxiety disorder was 55.2%, and depression symptoms was 46.3%, both significantly higher than the non-ASD group (P < 0.001). Multivariate logistic regression analysis revealed that Gartland type III fracture, severe pain intensity, postoperative complications, and previous trauma history were independent risk factors, while good family support was a protective factor. The predictive model showed good discrimination with an area under the curve of 0.823.
School-age children have a high incidence of ASD following supracondylar humeral fracture surgery, often accompanied by anxiety and depression symptoms. Fracture severity, pain intensity, postoperative complications, and previous trauma history are major risk factors, while good family support serves as a protective factor. Clinical practice should focus on high-risk patients, strengthen pain management, prevent complications, and provide family support interventions.
Core Tip: Acute stress disorder is a frequent but underrecognized psychological complication in school-age children after supracondylar humeral fracture surgery. In this study, 23.6% of children developed acute stress disorder, often accompanied by anxiety and depression. Multivariate analysis identified Gartland type III fractures, severe pain, postoperative complications, and prior trauma history as independent risk factors, while strong family support was protective. Our findings highlight the importance of early screening, effective pain control, complication prevention, and family-centered interventions to reduce psychological trauma and improve recovery in pediatric orthopedic patients.
- Citation: Yan GJ, Cheng T, Liu CX, Shan JX, Cen Y. Incidence and determinants of acute stress disorder after supracondylar humeral fracture surgery in school-age children. World J Psychiatry 2026; 16(6): 117084
- URL: https://www.wjgnet.com/2220-3206/full/v16/i6/117084.htm
- DOI: https://dx.doi.org/10.5498/wjp.v16.i6.117084
Supracondylar humeral fracture is the most common type of elbow fracture in children, accounting for approximately 50%-60% of all pediatric elbow fractures, with particularly prominent incidence in school-age children[1,2]. This type of fracture is mostly caused by accidental events such as falls and sports injuries. According to the Gartland classification system, type III fractures usually require emergency surgical intervention to avoid serious complications such as neurovascular injury[3]. Although surgical treatment can effectively restore anatomical structure and function, the surgical process itself and related experiences such as pain and hospitalization may cause significant psychological trauma to children[4].
Acute stress disorder (ASD) refers to psychological stress reactions occurring within one month after an individual experiences a traumatic event, manifested as core symptom clusters including intrusive symptoms, avoidance behaviors, negative alterations in cognitions and mood, and alterations in arousal and reactivity[5]. According to Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) diagnostic criteria, ASD not only affects children’s mental health but may also further develop into post-traumatic stress disorder (PTSD), causing long-term negative impacts on their learning, social interactions, and quality of life[6]. Population-based studies report that the overall incidence of ASD in children following various traumatic events ranges from 12% to 20%, with considerable variation depending on trauma type and severity. Medical trauma specifically has been associated with ASD rates of 10%-25% across diverse pediatric populations, though most research has focused on intensive care settings or life-threatening conditions. However, epidemiological data specific to orthopedic surgical trauma in school-age children remain notably sparse, with existing studies showing wide-ranging prevalence from 8% to 30%. Research on incidence rates and influencing factors in specific medical trauma contexts is relatively limited[7].
School-age children are in a critical period of psychological development, with immature cognitive abilities, emotion regulation skills, and coping strategies, making them more susceptible to acute stress reactions when facing surgical trauma[8]. While they have moved beyond the preverbal stage of early childhood, their cognitive capacities for threat appraisal, emotion regulation, and abstract reasoning are still maturing. This developmental window confers unique vulnerability to surgical trauma, yet targeted research in this age group remains limited. Existing research mainly focuses on adult PTSD or general traumatic stress reactions in children, while epidemiological investigations and risk factor analyses specifically targeting ASD following pediatric orthopedic surgery are relatively lacking[9]. Identifying characteristics of high-risk populations and modifiable risk factors is of great significance for developing targeted prevention strategies and improving children’s postoperative mental health status.
Therefore, this study employed a retrospective study design to systematically investigate the incidence of ASD following supracondylar humeral fracture surgery in school-age children and analyze independent risk factors from multiple dimensions including demographic characteristics, disease-related factors, and psychosocial factors, aiming to provide scientific evidence for early clinical identification of high-risk patients and development of individualized psychological intervention strategies, promoting comprehensive development of pediatric orthopedic medical services.
This study employed a retrospective study design, combining medical record review with telephone/outpatient follow-up to investigate the incidence of ASD following supracondylar humeral fracture surgery in school-age children and analyze risk factors. The study cohort consisted of school-age children who underwent supracondylar humeral fracture surgery in our hospital’s orthopedic department from June 2023 to March 2025, using standardized assessment criteria and instruments to conduct postoperative ASD tracking investigations and risk factor analyses for children meeting inclusion criteria.
Inclusion criteria: (1) School-age children aged 6-12 years; (2) Diagnosed with unilateral supracondylar humeral fracture by imaging examination, meeting Gartland classification criteria; (3) Underwent surgical treatment in our hospital’s orthopedic department, including closed reduction with percutaneous pinning or open reduction with internal fixation; and (4) Complete postoperative follow-up data.
Exclusion criteria: (1) Multiple injuries or combined severe trauma in other parts; (2) Pathological fractures or open fractures; (3) Previous history of mental illness or currently receiving psychiatric treatment; (4) Previous severe cognitive dysfunction or intellectual developmental delay; and (5) Combined severe internal medical diseases affecting psychological assessment.
Sample size calculation was based on statistical requirements for prevalence surveys. According to literature reports, the incidence of post-traumatic ASD in children is approximately 15%-20%[7]. This study preset the incidence of ASD following supracondylar humeral fracture surgery in school-age children at 18%. The prevalence survey sample size calculation formula was used: N = Z2 × p × (1-p)/d2, where Z is the confidence coefficient (Z = 1.96 when α = 0.05), p is the expected prevalence (P = 0.18), and d is the allowable error (set at 0.05). The calculated required sample size was 227 cases. Considering potential sample loss due to incomplete medical records and patient loss to follow-up in retrospective studies, adjusting for a 20% loss to follow-up rate, the final minimum sample size was determined to be 284 cases.
A self-designed general information questionnaire was developed, including the following three aspects.
Demographic characteristics survey: Collection of basic demographic information of children, specifically including: (1) Child’s age; (2) Gender, recorded as male or female; (3) Residence, based on household registration location, with cities referring to prefecture-level cities and above, and rural areas referring to county-level and below regions; (4) Family economic status, assessed using monthly family income, divided into three levels: Low income (< 5000 yuan), middle income (5000-10000 yuan), high income (> 10000 yuan); (5) Parental education level, recording the highest educational attainment of both father and mother, including primary school and below, junior high school, high school/vocational school, college and above; and (6) Family structure, categorized into nuclear family, extended family, single-parent family, and others.
Disease-related factors survey: Collection of clinical information related to supracondylar humeral fracture and treatment, specifically including: (1) Fracture type, using Gartland classification criteria, divided into type I, type II, and type III; (2) Injury mechanism, recorded as fall, traffic accident, sports injury, violence, and others; (3) Surgical method, including closed reduction with percutaneous pinning, open reduction with internal fixation, and other methods; (4) Pain intensity, assessed using the Wong-Baker Faces Pain Rating Scale, which contains 6 facial expression images corresponding to 0 points (no pain), 2 points (mild pain), 4 points (moderate pain), 6 points (severe pain), 8 points (very severe pain), and 10 points (worst pain), with children selecting the facial expression image that best matches their pain experience, where higher scores indicate more severe pain. Pain intensity was categorized as: Mild pain (Wong-Baker score 0-2), moderate pain (Wong-Baker score 4-6), and severe pain (Wong-Baker score 8-10), following established clinical practice guidelines. Pain was analyzed both as a continuous variable (mean scores across assessment timepoints) and as a categorical variable (maximum pain category experienced during the first 48 hours post-surgery). For multivariate analysis, pain was dichotomized as “severe” (score ≥ 8) vs “mild-to-moderate” (score < 8) based on clinically meaningful thresholds; and (5) Postoperative complications, recorded as present/absent, with detailed recording of complication types if present.
Psychosocial factors survey: Collection of factors affecting children’s psychological stress reactions, specifically including: (1) Previous trauma history, recorded as a binary variable (present/absent), with trauma defined as accidental injuries or major life events requiring medical intervention; (2) Family support status, assessed using the Chinese version of the Family Adaptability and Cohesion Evaluation Scales, fourth edition, which includes two dimensions of cohesion and adaptability, each with 10 items, using a 5-point Likert scale (1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always), with cohesion dimension scores ranging from 10-50 points, adaptability dimension scores ranging from 10-50 points, and total scores ranging from 20-100 points, where higher scores indicate better family functioning, closer family member relationships, and stronger family adaptability; and (3) Coping strategies, assessed using the Kidcope scale, including 10 coping strategies (distraction, social withdrawal, cognitive restructuring, self-criticism, blaming others, problem solving, emotional regulation, wishful thinking, social support, resignation), with each strategy including efficacy assessment (whether the strategy was used, 0 = no, 1 = yes) and effectiveness assessment (effectiveness of the strategy, 0 = completely ineffective, 1 = somewhat effective, 2 = very effective, 3 = extremely effective), with total efficacy scores ranging from 0-10 points, where higher scores indicate more types of coping strategies used; total effectiveness scores ranging from 0-30 points, where higher scores indicate better effectiveness of coping strategies used.
The Child ASD Scale (CASDS) was used to assess children’s ASD symptoms. This scale was developed based on DSM-5 ASD diagnostic criteria and contains 17 items covering four core dimensions: (1) Intrusive symptoms dimension (5 items, scores 0-15), including recurrent recollections of traumatic events, nightmares, flashbacks, and other symptom manifestations; (2) Avoidance symptoms dimension (2 items, scores 0-6), including avoidance of trauma-related thoughts and external reminders; (3) Negative alterations in cognitions and mood dimension (5 items, scores 0-15), including negative beliefs about traumatic events and persistent negative emotional states; and (4) Alterations in arousal and reactivity dimension (5 items, scores 0-15), including hypervigilance, startle response, attention deficits, and other physiological and psychological reactions. Each item uses a 4-point Likert scale (0 = never, 1 = occasionally, 2 = often, 3 = always), with total scores ranging from 0-51 points, where higher scores indicate more severe ASD symptoms, and ≥ 28 points indicates ASD diagnosis. The use of child self-report scales is justified by research demonstrating that school-age children (6-12 years) possess sufficient cognitive capacity for self-report of internal states, and validation studies show the CASDS has good psychometric properties in this age range (Cronbach’s α = 0.87). Self-report captures the child’s subjective experience, which is central to ASD diagnosis per DSM-5 criteria.
Childhood anxiety assessment: The Chinese version of the Screen for Child Anxiety Related Emotional Disorders was used to assess children’s anxiety symptoms. This scale contains 41 items covering 5 dimensions: (1) Somatic/panic disorder dimension (13 items, scores 0-26); (2) Generalized anxiety disorder dimension (9 items, scores 0-18); (3) Separation anxiety disorder dimension (8 items, scores 0-16); (4) Social phobia dimension (7 items, scores 0-14); and (5) School phobia dimension (4 items, scores 0-8). A 3-point Likert scale is used (0 = not true, 1 = sometimes true, 2 = often true), with total scores ranging from 0-82 points, where higher scores indicate more severe anxiety symptoms, and ≥ 25 points suggests the presence of anxiety disorders. Dimensional cutoff values are: Somatic/panic disorder ≥ 7 points, generalized anxiety disorder ≥ 9 points, separation anxiety disorder ≥ 5 points, social phobia ≥ 8 points, school phobia ≥ 3 points.
Childhood depression assessment: The Chinese version of the Children’s Depression Inventory was used to assess children’s depression symptoms. This scale contains 27 items, with each item containing 3 statements representing no symptoms (0 points), mild symptoms (1 point), and severe symptoms (2 points), with children selecting the statement that best matches their feelings over the past two weeks. Total scores range from 0-54 points, where higher scores indicate more severe depression symptoms, and ≥ 19 points suggests clinically significant depression symptoms, with 19-28 points indicating mild depression, 29-40 points indicating moderate depression, and ≥ 41 points indicating severe depression.
The Mini-Mental State Examination for children was used to assess children’s cognitive function to ensure they had the cognitive ability to complete questionnaire surveys. This scale includes 5 dimensions: (1) Orientation dimension (10 items, scores 0-10), assessing temporal and spatial orientation abilities; (2) Memory dimension (6 items, scores 0-6), assessing immediate memory and delayed recall abilities; (3) Attention and calculation dimension (5 items, scores 0-5), assessing attention concentration and simple calculation abilities; (4) Language ability dimension (8 items, scores 0-8), assessing naming, repetition, comprehension, and writing abilities; and (5) Visuospatial ability dimension (1 item, scores 0-1), assessing figure copying ability. Total score is 30 points, where higher scores indicate better cognitive function, ≥ 24 points indicates normal cognitive function, 20-23 points indicates mild cognitive impairment, 10-19 points indicates moderate cognitive impairment, and < 10 points indicates severe cognitive impairment.
SPSS 26.0 statistical software was used for data analysis, with a significance level of α = 0.05. Continuous variables were described using mean ± SD or median (interquartile range), with t-test or Mann-Whitney U test selected for between-group comparisons based on Shapiro-Wilk normality test results. Categorical variables were described using frequencies and proportions, with between-group comparisons using χ2 test or Fisher’s exact test. ASD incidence was expressed as counts and proportions with 95% confidence intervals (CIs) calculated. Prior to multivariate logistic regression, we systematically assessed multicollinearity using variance inflation factor with threshold > 5 and correlation matrices with r > 0.70. Variables demonstrating significant collinearity were evaluated for theoretical overlap and clinical modifiability. Variables with P < 0.10 in univariate analysis were included in multivariate logistic regression analysis using forward stepwise method for variable selection, calculating adjusted odds ratios (aORs) and their 95%CIs to evaluate independent effects of risk factors. Hosmer-Lemeshow goodness-of-fit test was used to evaluate model fit, and receiver operating characteristic curves were applied to assess discrimination of the predictive model, calculating the area under the curve (AUC). All statistical tests were two-sided, with P < 0.05 considered statistically significant.
This study included 284 school-age children with supracondylar humeral fractures, of which 67 cases (23.6%, 95%CI: 18.7%-28.5%) developed ASD, and 217 cases (76.4%, 95%CI: 71.5%-81.3%) did not develop ASD.
Demographic characteristic analysis showed no significant differences between the two groups in age, gender, and residence (P > 0.05), but significant differences existed in family structure (P = 0.033), with a higher proportion of single-parent families in the ASD group. Family economic status showed marginal significance (P = 0.073), with a higher proportion of low-income families in the ASD group (Table 1).
| Characteristic | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | Statistic | P value |
| Age (years) | 8.7 ± 1.8 | 8.9 ± 1.7 | 8.6 ± 1.8 | t = 1.234 | 0.218 |
| 6-8 | 118 (41.5) | 25 (37.3) | 93 (42.9) | ||
| 9-12 | 166 (58.5) | 42 (62.7) | 124 (57.1) | ||
| Gender | χ2 = 0.548 | 0.459 | |||
| Male | 167 (58.8) | 42 (62.7) | 125 (57.6) | ||
| Female | 117 (41.2) | 25 (37.3) | 92 (42.4) | ||
| Residence | χ2 = 2.698 | 0.100 | |||
| Urban | 179 (63.0) | 48 (71.6) | 131 (60.4) | ||
| Rural | 105 (37.0) | 19 (28.4) | 86 (39.6) | ||
| Family economic status | χ2 = 5.247 | 0.073 | |||
| Low income (< 5000 yuan) | 89 (31.3) | 28 (41.8) | 61 (28.1) | ||
| Middle income (5000-10000 yuan) | 128 (45.1) | 26 (38.8) | 102 (47.0) | ||
| High income (> 10000 yuan) | 67 (23.6) | 13 (19.4) | 54 (24.9) | ||
| Family structure | χ2 = 8.764 | 0.033 | |||
| Nuclear family | 198 (69.7) | 39 (58.2) | 159 (73.3) | ||
| Extended family | 56 (19.7) | 16 (23.9) | 40 (18.4) | ||
| Single-parent family | 24 (8.5) | 10 (14.9) | 14 (6.5) | ||
| Others | 6 (2.1) | 2 (3.0) | 4 (1.8) |
Disease-related factor analysis indicated that fracture type, pain intensity, and postoperative complications were important factors affecting ASD occurrence (P < 0.05). The ASD group had a higher proportion of Gartland type III fractures, more severe pain intensity, and higher incidence of postoperative complications (Table 2).
| Characteristic | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | Statistic | P value |
| Fracture type (Gartland classification) | χ2 = 8.472 | 0.014 | |||
| Type I | 47 (16.5) | 6 (9.0) | 41 (18.9) | ||
| Type II | 156 (54.9) | 32 (47.8) | 124 (57.1) | ||
| Type III | 81 (28.5) | 29 (43.3) | 52 (24.0) | ||
| Injury mechanism | χ2 = 6.741 | 0.150 | |||
| Fall | 162 (57.0) | 34 (50.7) | 128 (59.0) | ||
| Traffic accident | 48 (16.9) | 16 (23.9) | 32 (14.7) | ||
| Sports injury | 52 (18.3) | 12 (17.9) | 40 (18.4) | ||
| Violence | 15 (5.3) | 4 (6.0) | 11 (5.1) | ||
| Others | 7 (2.5) | 1 (1.5) | 6 (2.8) | ||
| Surgical method | χ2 = 4.127 | 0.127 | |||
| Closed reduction with percutaneous pinning | 201 (70.8) | 41 (61.2) | 160 (73.7) | ||
| Open reduction with internal fixation | 78 (27.5) | 24 (35.8) | 54 (24.9) | ||
| Others | 5 (1.8) | 2 (3.0) | 3 (1.4) | ||
| Pain intensity (Wong-Baker scale) | 5.8 ± 2.4 | 7.2 ± 2.1 | 5.4 ± 2.3 | t = 5.896 | < 0.001 |
| Postoperative complications | χ2 = 12.634 | < 0.001 | |||
| None | 241 (84.9) | 48 (71.6) | 193 (88.9) | ||
| Present | 43 (15.1) | 19 (28.4) | 24 (11.1) |
Psychosocial factor analysis found that the ASD group had a higher proportion of previous trauma history (P = 0.004), poorer family support (P < 0.001), and significantly lower coping strategy efficacy and effectiveness compared to the non-ASD group (P < 0.001; Table 3).
| Characteristic | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | Statistic | P value |
| Previous trauma history | χ2 = 8.129 | 0.004 | |||
| None | 201 (70.8) | 38 (56.7) | 163 (75.1) | ||
| Present | 83 (29.2) | 29 (43.3) | 54 (24.9) | ||
| Family support (FACES-IV) | 68.5 ± 12.3 | 61.2 ± 14.6 | 70.8 ± 10.4 | t = -5.823 | < 0.001 |
| Good (≥ 70 points) | 156 (54.9) | 22 (32.8) | 134 (61.8) | ||
| Moderate (50-69 points) | 102 (35.9) | 32 (47.8) | 70 (32.3) | ||
| Poor (< 50 points) | 26 (9.2) | 13 (19.4) | 13 (6.0) | ||
| Coping strategy efficacy total score (Kidcope) | 6.2 ± 2.1 | 5.1 ± 2.3 | 6.5 ± 1.9 | t = -4.968 | < 0.001 |
| High efficacy (≥ 7 points) | 118 (41.5) | 18 (26.9) | 100 (46.1) | ||
| Moderate efficacy (4-6 points) | 124 (43.7) | 32 (47.8) | 92 (42.4) | ||
| Low efficacy (< 4 points) | 42 (14.8) | 17 (25.4) | 25 (11.5) | ||
| Coping strategy effectiveness total score (Kidcope) | 18.4 ± 6.7 | 14.6 ± 7.2 | 19.6 ± 6.1 | t = -5.674 | < 0.001 |
| High effectiveness (≥ 22 points) | 89 (31.3) | 12 (17.9) | 77 (35.5) | ||
| Moderate effectiveness (15-21 points) | 127 (44.7) | 28 (41.8) | 99 (45.6) | ||
| Low effectiveness (< 15 points) | 68 (23.9) | 27 (40.3) | 41 (18.9) |
All children had Mini-Mental State Examination for children total scores ≥ 24 points, indicating normal cognitive function. There were no statistically significant differences in dimensional scores between the two groups (P > 0.05), indicating that cognitive function did not affect ASD occurrence (Table 4).
| Cognitive function dimension | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | Statistic | P value |
| MMSE-C total score | 27.8 ± 1.6 | 27.6 ± 1.8 | 27.9 ± 1.5 | t = -1.245 | 0.214 |
| Orientation score | 9.7 ± 0.6 | 9.6 ± 0.7 | 9.7 ± 0.5 | t = -1.089 | 0.277 |
| Memory score | 5.6 ± 0.7 | 5.5 ± 0.8 | 5.6 ± 0.6 | t = -1.156 | 0.248 |
| Attention and calculation score | 4.7 ± 0.6 | 4.6 ± 0.7 | 4.7 ± 0.5 | t = -1.078 | 0.282 |
| Language ability score | 7.5 ± 0.8 | 7.4 ± 0.9 | 7.5 ± 0.7 | t = -0.892 | 0.373 |
| Visuospatial ability score | 0.96 ± 0.2 | 0.94 ± 0.2 | 0.97 ± 0.2 | t = -1.201 | 0.231 |
The ASD group had significantly higher CASDS total scores and all four dimensional scores compared to the non-ASD group (P < 0.001), with intrusive symptoms and negative alterations in cognitions and mood being most prominent (Table 5).
| CASDS dimension | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | Statistic | P value |
| CASDS total score | 21.4 ± 12.8 | 35.2 ± 8.6 | 17.1 ± 9.4 | t = 15.896 | < 0.001 |
| Intrusive symptoms dimension | 6.8 ± 4.2 | 11.2 ± 3.1 | 5.4 ± 3.6 | t = 12.456 | < 0.001 |
| Avoidance symptoms dimension | 2.1 ± 1.8 | 3.9 ± 1.4 | 1.6 ± 1.5 | t = 11.234 | < 0.001 |
| Negative alterations in cognitions and mood dimension | 6.4 ± 3.9 | 10.8 ± 2.8 | 5.1 ± 3.2 | t = 13.567 | < 0.001 |
| Alterations in arousal and reactivity dimension | 6.1 ± 3.7 | 9.3 ± 2.9 | 5.0 ± 3.1 | t = 10.892 | < 0.001 |
The incidence rates of anxiety and depression symptoms in the ASD group were both significantly higher than those in the non-ASD group (P < 0.001). The detection rate of anxiety disorders was 55.2% (37/67), and depression symptoms was 46.3% (31/67), with risk ratios of 3.89 and 4.18, respectively (Tables 6 and 7).
| Scale and dimension | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | Statistic | P value |
| SCARED anxiety scale | |||||
| SCARED total score | 22.1 ± 14.6 | 32.8 ± 15.2 | 18.9 ± 12.4 | t = 7.456 | < 0.001 |
| Somatic/panic disorder | 6.2 ± 4.1 | 9.1 ± 4.8 | 5.3 ± 3.4 | t = 6.789 | < 0.001 |
| Generalized anxiety disorder | 7.8 ± 5.2 | 11.2 ± 5.6 | 6.8 ± 4.7 | t = 6.234 | < 0.001 |
| Separation anxiety disorder | 4.1 ± 3.2 | 6.3 ± 3.8 | 3.4 ± 2.7 | t = 6.456 | < 0.001 |
| Social phobia | 2.9 ± 2.8 | 4.2 ± 3.1 | 2.5 ± 2.5 | t = 4.567 | < 0.001 |
| School phobia | 1.1 ± 1.6 | 2.0 ± 1.9 | 0.9 ± 1.4 | t = 4.892 | < 0.001 |
| CDI depression scale | |||||
| CDI total score | 16.8 ± 11.2 | 25.4 ± 12.6 | 13.9 ± 9.4 | t = 7.892 | < 0.001 |
| Type of psychological disorder | Total (n = 284) | ASD group (n = 67) | Non-ASD group (n = 217) | χ2 | P value | OR (95%CI) |
| Anxiety disorders | ||||||
| Overall anxiety disorder (≥ 25 points) | 89 (31.3) | 37 (55.2) | 52 (24.0) | 24.567 | < 0.001 | 3.89 (2.18-6.95) |
| 95%CI | 25.9%-36.7% | 42.8%-67.6% | 18.3%-29.7% | |||
| Somatic/panic disorder (≥ 7 points) | 62 (21.8) | 28 (41.8) | 34 (15.7) | 19.865 | < 0.001 | 3.84 (2.02-7.31) |
| Generalized anxiety disorder (≥ 9 points) | 72 (25.4) | 31 (46.3) | 41 (18.9) | 20.123 | < 0.001 | 3.71 (2.01-6.85) |
| Separation anxiety disorder (≥ 5 points) | 53 (18.7) | 24 (35.8) | 29 (13.4) | 16.789 | < 0.001 | 3.58 (1.85-6.93) |
| Social phobia (≥ 8 points) | 40 (14.1) | 18 (26.9) | 22 (10.1) | 11.234 | 0.001 | 3.25 (1.62-6.52) |
| School phobia (≥ 3 points) | 33 (11.6) | 15 (22.4) | 18 (8.3) | 8.765 | 0.003 | 3.18 (1.48-6.84) |
| Depression symptoms | ||||||
| Depression symptoms (≥ 19 points) | 68 (23.9) | 31 (46.3) | 37 (17.1) | 23.456 | < 0.001 | 4.18 (2.26-7.73) |
| 95%CI | 19.0%-28.8% | 34.0%-58.6% | 12.1%-22.1% | |||
| Mild depression (19-28 points) | 45 (15.8) | 18 (26.9) | 27 (12.4) | 8.234 | 0.004 | 2.58 (1.31-5.08) |
| Moderate depression (29-40 points) | 18 (6.3) | 10 (14.9) | 8 (3.7) | 9.567 | 0.002 | 4.51 (1.71-11.89) |
| Severe depression (≥ 41 points) | 5 (1.8) | 3 (4.5) | 2 (0.9) | 3.128 | 0.077 | 5.11 (0.84-31.06) |
Univariate analysis results showed that among demographic characteristics, family structure (P = 0.033) and family economic status (P = 0.073) were related factors affecting ASD occurrence; among disease-related factors, fracture type (P = 0.014), pain intensity (P < 0.001), and postoperative complications (P < 0.001) were all significantly associated with ASD occurrence; among psychosocial factors, previous trauma history (P = 0.004), family support status (P < 0.001), coping strategy efficacy total score (P < 0.001), and coping strategy effectiveness total score (P < 0.001) were all significant influencing factors (Table 8).
| Influencing factor | ASD group (n = 67) | Non-ASD group (n = 217) | χ2/t value | P value |
| Demographic characteristics | ||||
| Age (years) | 8.9 ± 1.7 | 8.6 ± 1.8 | 1.234 | 0.218 |
| Gender | 0.548 | 0.459 | ||
| Male | 42 (62.7) | 125 (57.6) | ||
| Female | 25 (37.3) | 92 (42.4) | ||
| Residence | 2.698 | 0.100 | ||
| Urban | 48 (71.6) | 131 (60.4) | ||
| Rural | 19 (28.4) | 86 (39.6) | ||
| Family economic status | 5.247 | 0.073 | ||
| Low income | 28 (41.8) | 61 (28.1) | ||
| Middle income | 26 (38.8) | 102 (47.0) | ||
| High income | 13 (19.4) | 54 (24.9) | ||
| Family structure | 8.764 | 0.033 | ||
| Nuclear family | 39 (58.2) | 159 (73.3) | ||
| Extended family | 16 (23.9) | 40 (18.4) | ||
| Single-parent family | 10 (14.9) | 14 (6.5) | ||
| Others | 2 (3.0) | 4 (1.8) | ||
| Disease-related factors | ||||
| Fracture type | 8.472 | 0.014 | ||
| Type I | 6 (9.0) | 41 (18.9) | ||
| Type II | 32 (47.8) | 124 (57.1) | ||
| Type III | 29 (43.3) | 52 (24.0) | ||
| Pain intensity | 7.2 ± 2.1 | 5.4 ± 2.3 | 5.896 | < 0.001 |
| Postoperative complications | 12.634 | < 0.001 | ||
| Present | 19 (28.4) | 24 (11.1) | ||
| Psychosocial factors | ||||
| Previous trauma history | 8.129 | 0.004 | ||
| Present | 29 (43.3) | 54 (24.9) | ||
| Family support status | 61.2 ± 14.6 | 70.8 ± 10.4 | -5.823 | < 0.001 |
| Coping strategy efficacy total score | 5.1 ± 2.3 | 6.5 ± 1.9 | -4.968 | < 0.001 |
| Coping strategy effectiveness total score | 14.6 ± 7.2 | 19.6 ± 6.1 | -5.674 | < 0.001 |
Variables with P < 0.10 in univariate analysis were included in multivariate logistic regression analysis using forward stepwise method for variable selection (inclusion criterion P < 0.05, exclusion criterion P > 0.10). The final model revealed 5 independent influencing factors: Gartland type III fracture (aOR = 3.85, 95%CI: 1.50-9.88, P = 0.005), severe pain intensity (aOR = 1.26, 95%CI: 1.11-1.44, P < 0.001), postoperative complications (aOR = 2.68, 95%CI: 1.33-5.41, P = 0.006), and previous trauma history (aOR = 2.13, 95%CI: 1.14-3.98, P = 0.017) were risk factors; good family support status (aOR = 0.95, 95%CI: 0.93-0.98, P = 0.001) was a protective factor. During the stepwise regression process, family structure, family economic status, residence, coping strategy efficacy total score, and coping strategy effectiveness total score were excluded due to not meeting inclusion criteria or collinearity with other variables. The predictive model had an AUC of 0.823 (95%CI: 0.774-0.872), demonstrating good discrimination and predictive efficacy (Table 9).
| Influencing factor | B | SE | Wald | P value | aOR | 95%CI |
| Fracture type | 7.896 | 0.019 | ||||
| Type II vs type I | 0.892 | 0.457 | 3.814 | 0.051 | 2.44 | 0.99-6.00 |
| Type III vs type I | 1.347 | 0.482 | 7.805 | 0.005 | 3.85 | 1.50-9.88 |
| Pain intensity (per 1-point increase) | 0.234 | 0.067 | 12.125 | < 0.001 | 1.26 | 1.11-1.44 |
| Postoperative complications (present vs absent) | 0.987 | 0.358 | 7.608 | 0.006 | 2.68 | 1.33-5.41 |
| Previous trauma history (present vs absent) | 0.756 | 0.318 | 5.647 | 0.017 | 2.13 | 1.14-3.98 |
| Family support status (per 1-point increase) | -0.048 | 0.014 | 11.689 | 0.001 | 0.95 | 0.93-0.98 |
| Constant | 0.125 | 1.246 | 0.010 | 0.920 | 1.13 |
Hosmer-Lemeshow test χ2 = 6.342, P = 0.609, indicating good model fit. Receiver operating characteristic curve AUC = 0.823 (95%CI: 0.774-0.872), sensitivity 76.1%, specificity 78.3%, showing good predictive efficacy.
Our study identified an ASD incidence of 23.6% among school-age children following supracondylar humeral fracture surgery. This rate exceeds the previously cited general pediatric post-traumatic ASD rates of 15%-20% and falls in the upper range of medical trauma-related ASD (10%-25%), suggesting that orthopedic surgical trauma represents a higher-risk scenario than previously appreciated. Several factors likely contribute to this heightened vulnerability. First, supracondylar fractures, especially Gartland type III, involve significant tissue injury, neurovascular risk, and procedural complexity, creating a multi-layered traumatic experience. Second, school-age children possess sufficient cognitive development to form lasting traumatic memories while lacking the fully mature coping mechanisms of adolescents or adults. Third, the sudden, unexpected nature of traumatic injury may amplify acute stress reactions. Finally, the prolonged recovery period provides ongoing reminders of the traumatic event.
This study found that school-age children have a relatively high incidence of ASD following supracondylar humeral fracture surgery, which is consistent with previously reported incidence rates of post-traumatic ASD in children[10]. Supracondylar humeral fracture, as the most common type of elbow fracture in children, involves not only sudden traumatic events but also the superimposed effects of multiple stressors including surgical anesthesia, pain experience, and hospitalization environment[11]. School-age children, due to immature cognitive development, have stronger fears of medical environments and greater sensitivity to pain, making them more susceptible to acute stress reactions[12].
From symptom dimension analysis, this study found that children in the ASD group were most prominent in intrusive symptoms and negative alterations in cognitions and mood, which is consistent with typical manifestations of PTSD[13]. Intrusive symptoms such as recurrent recollections of surgical scenes and related nightmares reflect abnormal processing of traumatic memories by the brain. Negative alterations in cognitions and mood manifest as persistent fear of medical environments and excessive worry about personal safety. These symptoms not only affect children’s current psychological state but may also have long-term negative impacts on their future medical compliance[14].
The three disease-related independent risk factors identified in this study have important clinical guidance significance. Gartland type III fracture, as the most severe type of supracondylar humeral fracture, is usually accompanied by more complex surgical procedures, longer operative times, and higher complication risks[15]. Children with type III fractures experience greater trauma intensity and more significant surgical stress, which aligns with the trauma stress theory’s perspective that trauma severity positively correlates with psychological reaction intensity[16].
Pain intensity is another important predictor of ASD occurrence. Pain is not only a physiological sensation but also an important psychological stressor[17]. School-age children have limited pain cognition and expression abilities, and intense pain experiences are often accompanied by negative emotions such as fear and anxiety, forming a vicious cycle of “pain-fear-stress”[18]. In this study, children in the ASD group had significantly higher pain intensity, highlighting the importance of pain management. The mean maximum pain score in the ASD group was 7.3 ± 1.8, well into the severe range, compared to 4.6 ± 2.1 in the non-ASD group. Critically, a substantially higher proportion of children in the ASD group (68.7%) experienced severe pain (score ≥ 8) compared to those without ASD (28.3%), representing more than a two-fold difference. This highlights that severe pain is not merely statistically associated with ASD but represents a clinically pervasive experience among affected children, underscoring that optimal analgesia is both a humanitarian imperative and a form of primary psychological prevention.
The occurrence of postoperative complications significantly increases ASD risk. Complications not only prolong recovery time and increase frequency of medical contact but may also cause children and families to worry about treatment effectiveness, exacerbating psychological burden[19]. Common complications such as infection and fracture displacement often require additional medical intervention, further intensifying the strength and duration of traumatic experiences[20].
Previous trauma history is an important predictor of ASD occurrence. According to cumulative stress theory, individuals’ previous traumatic experiences lower their tolerance threshold for new trauma, increasing susceptibility to psychological stress reactions[21]. Children with previous trauma history often have already formed hypersensitive reaction patterns to threatening stimuli, making them more likely to activate previous traumatic memories when facing new medical trauma, leading to symptom amplification[22].
Family support status as a protective factor has important significance. Good family support not only provides emotional comfort but also helps children establish a sense of security and coping confidence[23]. Family members’ companionship and encouragement can alleviate children’s fear of medical environments and promote the formation of positive coping strategies[24]. This study found that children in the ASD group had poorer family support and a higher proportion of single-parent families, suggesting the important role of family structure integrity and functionality in children’s psychological recovery[25].
This study found significant comorbidity between ASD and anxiety-depression symptoms, with high detection rates for both anxiety disorders and depression symptoms. This comorbidity pattern aligns with the clustering characteristics of internalizing disorders[26]. ASD, anxiety, and depression have overlapping neurobiological mechanisms, all involving abnormal activation of the hypothalamic-pituitary-adrenal axis and imbalances in neurotransmitter systems[27].
From a developmental psychology perspective, school-age children are in a critical stage of emotional regulation ability development. When facing traumatic stress, they often lack mature coping mechanisms and are prone to multiple internalizing symptom manifestations[28]. This comorbidity pattern not only exacerbates children’s psychological burden but may also affect recovery processes and long-term prognosis, requiring sufficient attention from clinical healthcare providers[29].
The predictive model established in this study has good discrimination, providing a scientific tool for early clinical identification of high-risk children. Based on study results, recommendations for perioperative management of children with supracondylar humeral fractures include: (1) Focus on psychological assessment and intervention for children with Gartland type III fractures, previous trauma history, and poor family support; (2) Strengthen pain management using multimodal analgesic strategies to reduce negative psychological impacts of pain; (3) Actively prevent and manage postoperative complications to reduce additional traumatic stress; and (4) Develop family education and support programs to improve family coping abilities[30].
This study has the following limitations: First, as a single-center retrospective study, the generalizability of results may be limited, requiring multicenter prospective studies for further validation. The retrospective nature of data collection may introduce several specific biases. Recall bias may occur as psychosocial assessments were conducted 2-4 weeks post-surgery; children experiencing more severe symptoms may have heightened recall of pain and distress, potentially inflating associations. Selection bias may exist if families of children with severe psychological distress were less likely to complete follow-up, though comparison with lost-to-follow-up cases showed no significant differences in demographics or clinical characteristics. Information bias from medical record abstraction was minimized through systematic protocols and dual independent review. Despite these potential biases, the strong effect sizes observed, biological plausibility of risk factors, and consistency with trauma theory suggest our results represent genuine associations. Second, ASD assessment mainly relied on self-report scales, which may involve subjective bias; future studies could consider combining clinical interviews and biological markers for comprehensive assessment. Third, this study did not include biological factors such as genetic susceptibility and neurodevelopmental levels, which may have important impacts on ASD occurrence. Finally, the follow-up period was relatively short, preventing evaluation of long-term outcomes of ASD and its continued impact on quality of life.
Based on study findings, future research should focus on the following directions: (1) Conduct large-sample multicenter prospective studies to validate the stability and predictive efficacy of risk factor models; (2) Explore neurobiological mechanisms of ASD, including inflammatory factors, stress hormones, and neuroimaging changes; (3) Develop and evaluate targeted psychological intervention programs, such as the application effects of cognitive behavioral therapy and family therapy in pediatric orthopedic patients; (4) Establish long-term follow-up cohorts for ASD to evaluate its long-term impacts on children’s psychological development and quality of life; and (5) Study gene-environment interactions affecting ASD susceptibility to provide evidence for precision prevention.
Based on these findings, we propose comprehensive clinical implementation strategies. First, institutions should implement pre-surgical risk stratification using a validated scoring system incorporating Gartland classification, anticipated pain severity, complication risk factors, trauma history, and family support assessment. Second, pain management protocols should include multimodal analgesia with regional nerve blocks, scheduled non-opioid medications, and psychological components targeting pain scores consistently below 4/10. Third, complication prevention bundles should emphasize surgical excellence for complex fractures, systematic vascular monitoring, strict infection control, and multidisciplinary daily rounds. Fourth, family support interventions should include pre-operative psychoeducational meetings, liberal visitation policies, trauma-informed communication training for staff, and connection to community mental health resources for families with limited support. Fifth, universal psychological screening should occur at 2 weeks and 4 weeks post-discharge using validated brief questionnaires, with clear referral pathways for children screening positive. Finally, institutions should track quality metrics including ASD screening rates, mean pain scores, complication rates, and family satisfaction to enable continuous improvement.
In conclusion, this study is the first to systematically investigate the incidence and influencing factors of ASD following supracondylar humeral fracture surgery in school-age children, providing scientific evidence for early clinical identification and intervention. The study results emphasize the important roles of disease severity, pain management, complication prevention, and family support in maintaining children’s mental health, having important clinical guidance value.
| 1. | Samaila EM, Auregli L, Pezzè L, Colò G, Magnan B. Medium-term clinical results in the treatment of supracondylar humeral fractures in children: does the surgical approach impact outcomes? J Orthop Traumatol. 2024;25:43. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 1] [Cited by in RCA: 2] [Article Influence: 1.0] [Reference Citation Analysis (0)] |
| 2. | Lee CH, Jung ST, Park CG, Kim J, Kang GR, Kim S. Minimally invasive surgical technique for unstable supracondylar humerus fractures in children (Gartland type III or IV). Front Pediatr. 2024;12:1352887. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 3] [Reference Citation Analysis (0)] |
| 3. | Schultz RJ, Amaral JZ, Bridges CS, Allen JY, Bih ES, Cruz AT, Gladstein AZ, Henkel EB, Kraus SJ, Smith BG, Wall JC Jr, Kan JH. Gartland classification concordance of supracondylar fractures among pediatric emergency medicine physicians, radiologists, and orthopedic surgeons. Pediatr Radiol. 2024;54:1180-1186. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 2] [Reference Citation Analysis (0)] |
| 4. | Stanzel A, Sierau S. Pediatric Medical Traumatic Stress (PMTS) following Surgery in Childhood and Adolescence: a Systematic Review. J Child Adolesc Trauma. 2022;15:795-809. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 11] [Cited by in RCA: 24] [Article Influence: 6.0] [Reference Citation Analysis (0)] |
| 5. | Li ST, Chien WC, Chung CH, Tzeng NS. Increased risk of acute stress disorder and post-traumatic stress disorder in children and adolescents with autism spectrum disorder: a nation-wide cohort study in Taiwan. Front Psychiatry. 2024;15:1329836. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 4] [Reference Citation Analysis (0)] |
| 6. | Levin RY, Liu RT. Post-traumatic stress disorder in a national sample of preadolescent children 9 to 10 years old: Prevalence, correlates, clinical sequelae, and treatment utilization. Transl Psychiatry. 2024;14:152. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 7] [Cited by in RCA: 8] [Article Influence: 4.0] [Reference Citation Analysis (0)] |
| 7. | Christoffersen MN, Thorup AAE. Post-traumatic Stress Disorder in School-age Children: A Nationwide Prospective Birth Cohort Study. J Child Adolesc Trauma. 2024;17:139-157. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 6] [Reference Citation Analysis (0)] |
| 8. | Zhang L, Xu Y, Funkhouser CJ, Monteleone AM, Yu X. Childhood trauma, emotion regulation, peer attachment, and family functioning: A longitudinal network analysis. Child Youth Serv Rev. 2024;166:107900. [DOI] [Full Text] |
| 9. | May C, Miller PE, Naqvi M, Rademacher E, Klajn J, Hedequist D, Shore BJ. The Incidence of Posttraumatic Stress Symptoms in Children. J Am Acad Orthop Surg Glob Res Rev. 2023;7:e22.00245. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 2] [Reference Citation Analysis (0)] |
| 10. | Turgoose DP, Kerr S, De Coppi P, Blackburn S, Wilkinson S, Rooney N, Martin R, Gray S, Hudson LD. Prevalence of traumatic psychological stress reactions in children and parents following paediatric surgery: a systematic review and meta-analysis. BMJ Paediatr Open. 2021;5:e001147. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 4] [Cited by in RCA: 33] [Article Influence: 6.6] [Reference Citation Analysis (0)] |
| 11. | Ma X, Zhang Z, Bao Y, Zhao H. Impact of pediatric surgery on anxiety in children and their families and coping strategies: a narrative review. Transl Pediatr. 2025;14:718-727. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 12] [Reference Citation Analysis (0)] |
| 12. | Sprooten E. How early environment influences the developing brain and long-term mental health. JCPP Adv. 2024;4:e12230. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 1] [Reference Citation Analysis (0)] |
| 13. | Landi G, Pakenham KI, Mattioli E, Crocetti E, Agostini A, Grandi S, Tossani E. Post-traumatic growth in people experiencing high post-traumatic stress during the COVID-19 pandemic: The protective role of psychological flexibility. J Contextual Behav Sci. 2022;26:44-55. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 12] [Cited by in RCA: 23] [Article Influence: 5.8] [Reference Citation Analysis (0)] |
| 14. | Daughtrey HR, Ruiz MO, Felix N, Saynina O, Sanders LM, Anand KJS. Incidence of mental health conditions following pediatric hospital admissions: analysis of a national database. Front Pediatr. 2024;12:1344870. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 13] [Cited by in RCA: 10] [Article Influence: 5.0] [Reference Citation Analysis (0)] |
| 15. | Gosens T, den Oudsten BL. Psychology in orthopedics and traumatology: an instructional review. EFORT Open Rev. 2023;8:245-252. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 7] [Reference Citation Analysis (0)] |
| 16. | Wang SK, Feng M, Fang Y, Lv L, Sun GL, Yang SL, Guo P, Cheng SF, Qian MC, Chen HX. Psychological trauma, posttraumatic stress disorder and trauma-related depression: A mini-review. World J Psychiatry. 2023;13:331-339. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in CrossRef: 16] [Cited by in RCA: 42] [Article Influence: 14.0] [Reference Citation Analysis (0)] |
| 17. | Davis C, Turner-Cobb JM. The Perceived Stress Scale for Kids (PeSSKi): Initial development of a brief measure for children aged 7-11 years. Stress Health. 2023;39:125-136. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 1] [Cited by in RCA: 8] [Article Influence: 2.7] [Reference Citation Analysis (0)] |
| 18. | Harte N, Aaron RV, Bhattiprolu K, Bisby MA, Gandy M, Hathway T, Dear BF, Dudeney J. The association between anxiety and depression symptoms and pain and function in adolescents and young adults with chronic pain: A meta-analysis. J Psychosom Res. 2024;187:111945. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 12] [Reference Citation Analysis (0)] |
| 19. | Ko MSM, Poh PF, Heng KYC, Sultana R, Murphy B, Ng RWL, Lee JH. Assessment of Long-term Psychological Outcomes After Pediatric Intensive Care Unit Admission: A Systematic Review and Meta-analysis. JAMA Pediatr. 2022;176:e215767. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 11] [Cited by in RCA: 57] [Article Influence: 14.3] [Reference Citation Analysis (0)] |
| 20. | Kuhn AW, Troyer SC, Martus JE. Pediatric Open Long-Bone Fracture and Subsequent Deep Infection Risk: The Importance of Early Hospital Care. Children (Basel). 2022;9:1243. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 6] [Cited by in RCA: 7] [Article Influence: 1.8] [Reference Citation Analysis (0)] |
| 21. | Cruz D, Lichten M, Berg K, George P. Developmental trauma: Conceptual framework, associated risks and comorbidities, and evaluation and treatment. Front Psychiatry. 2022;13:800687. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 106] [Cited by in RCA: 54] [Article Influence: 13.5] [Reference Citation Analysis (2)] |
| 22. | Lawrence-Sidebottom D, Huffman LG, Beam AB, Guerra R, Parikh A, Roots M, Huberty J. Rates of Trauma Exposure and Posttraumatic Stress in a Pediatric Digital Mental Health Intervention: Retrospective Analysis of Associations With Anxiety and Depressive Symptom Improvement Over Time. JMIR Pediatr Parent. 2024;7:e55560. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 3] [Reference Citation Analysis (0)] |
| 23. | Segers EW, Ketelaar M, de Man MACP, Schoonhoven L, van de Putte EM, van den Hoogen A. How to support children to develop and express their coping preferences around minor invasive medical procedures: children's and parents' perspectives. Eur J Pediatr. 2023;182:5553-5563. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 8] [Reference Citation Analysis (0)] |
| 24. | Vladislav EO, Marc G, Paica CI, Pop O. Family resilience in a social-ecological context - emotional difficulties and coping strategies. Front Psychol. 2024;15:1421745. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 4] [Reference Citation Analysis (0)] |
| 25. | Grüning Parache L, Vogel M, Meigen C, Kiess W, Poulain T. Family structure, socioeconomic status, and mental health in childhood. Eur Child Adolesc Psychiatry. 2024;33:2377-2386. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 1] [Cited by in RCA: 25] [Article Influence: 12.5] [Reference Citation Analysis (0)] |
| 26. | Essau CA, de la Torre-Luque A. Comorbidity Between Internalising and Externalising Disorders Among Adolescents: Symptom Connectivity Features and Psychosocial Outcome. Child Psychiatry Hum Dev. 2023;54:493-507. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 10] [Cited by in RCA: 13] [Article Influence: 4.3] [Reference Citation Analysis (0)] |
| 27. | Bertollo AG, Santos CF, Bagatini MD, Ignácio ZM. Hypothalamus-pituitary-adrenal and gut-brain axes in biological interaction pathway of the depression. Front Neurosci. 2025;19:1541075. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 78] [Cited by in RCA: 67] [Article Influence: 67.0] [Reference Citation Analysis (0)] |
| 28. | Lin SC, Kehoe C, Pozzi E, Liontos D, Whittle S. Research Review: Child emotion regulation mediates the association between family factors and internalizing symptoms in children and adolescents - a meta-analysis. J Child Psychol Psychiatry. 2024;65:260-274. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 32] [Reference Citation Analysis (0)] |
| 29. | Leeb RT, Danielson ML, Claussen AH, Robinson LR, Lebrun-Harris LA, Ghandour R, Bitsko RH, Katz SM, Kaminski JW, Brown J. Trends in Mental, Behavioral, and Developmental Disorders Among Children and Adolescents in the US, 2016-2021. Prev Chronic Dis. 2024;21:E96. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 45] [Cited by in RCA: 31] [Article Influence: 15.5] [Reference Citation Analysis (1)] |
| 30. | Isaac L, Rosenbloom BN, Tyrrell J, Ruskin DA, Birnie KA. Development and expansion of a pediatric transitional pain service to prevent complex chronic pain. Front Pain Res (Lausanne). 2023;4:1173675. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 11] [Reference Citation Analysis (0)] |