Psycho‐Oncological Issues in a Pediatric Sample: Two Years Follow‐Up Data of Consultation Liaison Psychiatry
Background Consultation‐Liaison Psychiatry (CLP) is a subspecialty of psychiatry that deals with psychiatric conditions, accompanying non‐psychiatric medical illnesses . Despite the clear benefits and identified needs of CLP, the number of pediatric CLP units remains insufficient . From an academic perspective, studies on pediatric CLP, particularly in psycho‐oncology, are relatively new and limited in number . The incidence of childhood cancer reportedly increases by approximately 1% each year, with recovery rates improving annually by 1.4%. Between the mid‐1970s and 2019, the five‐year relative survival rate for all cancers improved from 58% to 85% in children and from 68% to 87% in adolescents, though these rates vary significantly by cancer type and age at onset . Regardless of substantial therapeutic advances, cancer remains a leading cause of death among children, while its global age‐standardized incidence rates are on the increase . Considering the decreasing mortality due to increased access to health services and treatment options (mortality has tended to remain stable in common subtypes such as leukemia since 2016, but has increased incidence in some subtypes and different age groups), the psychosocial and psychiatric challenges associated with a cancer diagnosis and its chronic impact on children and their families are considerable. Improving survival rates in pediatric oncology has increased awareness of the significant psychosocial and psychiatric challenges faced by children and adolescents with cancer. Cancer treatments are often prolonged, imposing not only physical side effects but also profound emotional and psychological burdens on young patients and their parents . Several factors influence adaptation to the disease process, beyond the cancer's clinical characteristics and time since diagnosis. These factors can be grouped into five categories: individual coping styles, developmental stage, prior medical history, temperament, and familial influences . Understanding these factors across various clinical settings and populations will help identify risk groups and tailor interventions to address psychiatric needs. In response to these challenges, pediatric oncology care increasingly integrates mental health support to address conditions such as depression, anxiety, adjustment disorders, and other psychiatric issues that may emerge or worsen during treatment . This shift aligns with recommendations from global health organizations that underscore the need for holistic approaches, incorporating psychosocial and psychiatric care, as part of comprehensive cancer treatment in children . However, research on the specific psychiatric needs and clinical characteristics of these pediatric patients remains limited, particularly within certain socio‐demographic contexts. This study aims to address these gaps by conducting a retrospective analysis of the psychiatric consultations of pediatric oncology patients treated at the CLP Department of the Child and Adolescent Psychiatry Clinic at Children Hospital, Ankara Etlik City Hospital, University of Health Sciences over a two‐year period. By examining the socio‐demographic characteristics, oncological diagnoses, and psychiatric profiles of these patients, we seek to identify patterns that could inform future mental health support strategies within pediatric oncology. Specifically, we hypothesize that  certain sociodemographic factors, such as gender, lower SES, cessation of education, parental unemployment, and family structure, will be associated with increased rates of psychiatric morbidity and psychotherapeutic requirements ; the primary reasons for psychiatric consultation will vary by oncological diagnosis, with higher instances of internalization problems observed in patients with intensive treatment regimens and longer hospitalization periods. Through these findings, we hope to contribute valuable insights into the psychiatric needs of pediatric oncology patients and underscore the importance of socio‐demographic considerations in developing mental health interventions in oncology care. 

Methods This study was a retrospective, cross‐sectional analysis of a sociodemographic, psychiatric, and medical database comprising 97 pediatric oncology patients. These patients, with various oncological diagnoses, were referred to and followed up by the Consultation‐Liaison Psychiatry (CLP) Department of the Child and Adolescent Psychiatry Clinic at Children Hospital, Ankara Etlik City Hospital, University of Health Sciences between September 2022 and July 2024. The research protocol was approved by the local ethics committee on July 31, 2024 (Protocol Number: AESH‐BADEK‐2024‐512). The study was conducted in compliance with the Declaration of Helsinki, and informed consent was obtained from all participants and their parents prior to inclusion in the study. 2.1 Sample and Inclusion Criteria Pediatric patients with a primary oncological diagnosis, referred to the CLP clinic irrespective of the presence of psychiatric symptoms or diagnosis, were included in the study. Since our study was planned to examine the psychiatric and referral characteristics of patients with primary oncological disease who were referred to pediatric CLP, we focused on the clinical data of the patients with a primary oncological disease and formally consulted to psychiatry. The total patient number (included outpatient and inpatient numbers) between September 2022 and July 2024 for pediatric hematology‐oncology clinic was detected as approximately 40.000 (the real number: 39.191 patients). The total number within these dates in the inpatient services of pediatric hematology‐oncology clinic was 404, whereas only one patient was referred to another hospital upon the patient's and his/her legal custodians' demands. Out of 404 patients with varied hematological and/or oncological conditions followed in the inpatient clinic of pediatric hematology‐oncology clinic within the aforementioned dates, only 103 (25.5%) patients with a primary oncological disorder were referred to Pediatric CLP with varied reasons, whereas 243 (about 60%) patients with a primary oncological disorder were not referred to psychiatry and 58 (about %14.5) patients were treated due to other hematological conditions such as nutritional anemia, hemophilia, thalassemia, etc. Regular data records were obtained for only 97 of the 103 patients referred to the CLP clinic, and 6 patients had to be excluded due to lack of data. Exclusion criteria consisted of incorrect diagnostic entries and incomplete file information. Psychiatric diagnoses were made using structured clinical interviews based on the Schedule for Affective Disorders and Schizophrenia for School‐Age Children–Present and Lifetime Version (K‐SADS‐PL), DSM‐5, Turkish Version (November 2016), as a routine clinical practice . 2.2 Data Collection and Measures Sociodemographic and clinical data were collected, including systematically recorded information on age, gender, educational status, age of oncological and psychiatric diagnoses, psychiatric and oncological history, hospitalization duration, socioeconomic parameters, and parental occupational, educational, and marital status. Additional information, including medical and psychiatric history of parents and details related to the CLP process, was extracted from patient files or obtained by contacting parents. CLP‐specific clinical characteristics recorded included the number of psychiatric consultations, age at first psychiatric referral, consultation symptoms, the person requesting psychiatric evaluation, the main scope of psychiatric consultation, the main consultation rationale defined by psychiatrists, psychiatric diagnoses, requirement of psychopharmacological and psychotherapeutic intervention, types of psychiatric treatment, and psychiatric follow‐up. The socioeconomic status (SES) was determined due to the Hollingshead‐Redlich Index (HRI) , which allows the determination of individual social status by categorizing occupational and educational status. Families were categorized as low SES (HRI < 23), medium SES (HRI 23–44), or high SES (HRI > 44), combining file data with follow‐up calls. The Kiddie‐Schedule for Affective Disorders and Schizophrenia for School‐Age Children‐Present and Lifetime Version DSM‐V, known as K‐SADS‐PL, is a semi‐structured interview designed to detect current and lifetime psychopathologies in pediatric samples based on DSM‐5 diagnostic criteria . The reliability and validity of the Turkish adaptation were established by Ünal et al. . 2.3 Statistical Analysis Data were analyzed using IBM SPSS (version 26.0 for Windows; SPSS Inc., Chicago, IL). Normality was assessed with the Kolmogorov–Smirnov test. Descriptive statistics, including frequencies ( n ), percentages, means, and standard deviations (SD), were used to describe the demographic and clinical characteristics. Subgroup comparisons based on gender, oncological diagnosis types, education continuum status, psychopathology presence, and psychopharmacological treatment requirement were conducted using Pearson's chi‐square ( χ 2 ) or Fisher's exact tests (when expected frequencies were less than five per cell) for categorical variables, and Mann–Whitney U‐tests or Kruskal–Wallis tests for continuous variables. Post hoc tests were applied for multiple group comparisons. p ‐values were derived from two‐tailed tests with an alpha level of 0.05, with Bonferroni correction applied as needed. Multivariate logistic regression analyses (in line with “entered” mode) were employed to identify predictors of psychiatric diagnoses and psychopharmacological intervention requirements. Univariate analyses of variables associated with the dependent variables were performed using chi‐square or Fisher's exact tests. Model fit was evaluated using Hosmer‐Lemeshow goodness‐of‐fit statistics, with explanatory power assessed via Cox & Snell and Nagelkerke R 2 values. 

Sample and Inclusion Criteria Pediatric patients with a primary oncological diagnosis, referred to the CLP clinic irrespective of the presence of psychiatric symptoms or diagnosis, were included in the study. Since our study was planned to examine the psychiatric and referral characteristics of patients with primary oncological disease who were referred to pediatric CLP, we focused on the clinical data of the patients with a primary oncological disease and formally consulted to psychiatry. The total patient number (included outpatient and inpatient numbers) between September 2022 and July 2024 for pediatric hematology‐oncology clinic was detected as approximately 40.000 (the real number: 39.191 patients). The total number within these dates in the inpatient services of pediatric hematology‐oncology clinic was 404, whereas only one patient was referred to another hospital upon the patient's and his/her legal custodians' demands. Out of 404 patients with varied hematological and/or oncological conditions followed in the inpatient clinic of pediatric hematology‐oncology clinic within the aforementioned dates, only 103 (25.5%) patients with a primary oncological disorder were referred to Pediatric CLP with varied reasons, whereas 243 (about 60%) patients with a primary oncological disorder were not referred to psychiatry and 58 (about %14.5) patients were treated due to other hematological conditions such as nutritional anemia, hemophilia, thalassemia, etc. Regular data records were obtained for only 97 of the 103 patients referred to the CLP clinic, and 6 patients had to be excluded due to lack of data. Exclusion criteria consisted of incorrect diagnostic entries and incomplete file information. Psychiatric diagnoses were made using structured clinical interviews based on the Schedule for Affective Disorders and Schizophrenia for School‐Age Children–Present and Lifetime Version (K‐SADS‐PL), DSM‐5, Turkish Version (November 2016), as a routine clinical practice . 

Data Collection and Measures Sociodemographic and clinical data were collected, including systematically recorded information on age, gender, educational status, age of oncological and psychiatric diagnoses, psychiatric and oncological history, hospitalization duration, socioeconomic parameters, and parental occupational, educational, and marital status. Additional information, including medical and psychiatric history of parents and details related to the CLP process, was extracted from patient files or obtained by contacting parents. CLP‐specific clinical characteristics recorded included the number of psychiatric consultations, age at first psychiatric referral, consultation symptoms, the person requesting psychiatric evaluation, the main scope of psychiatric consultation, the main consultation rationale defined by psychiatrists, psychiatric diagnoses, requirement of psychopharmacological and psychotherapeutic intervention, types of psychiatric treatment, and psychiatric follow‐up. The socioeconomic status (SES) was determined due to the Hollingshead‐Redlich Index (HRI) , which allows the determination of individual social status by categorizing occupational and educational status. Families were categorized as low SES (HRI < 23), medium SES (HRI 23–44), or high SES (HRI > 44), combining file data with follow‐up calls. The Kiddie‐Schedule for Affective Disorders and Schizophrenia for School‐Age Children‐Present and Lifetime Version DSM‐V, known as K‐SADS‐PL, is a semi‐structured interview designed to detect current and lifetime psychopathologies in pediatric samples based on DSM‐5 diagnostic criteria . The reliability and validity of the Turkish adaptation were established by Ünal et al. . 

Statistical Analysis Data were analyzed using IBM SPSS (version 26.0 for Windows; SPSS Inc., Chicago, IL). Normality was assessed with the Kolmogorov–Smirnov test. Descriptive statistics, including frequencies ( n ), percentages, means, and standard deviations (SD), were used to describe the demographic and clinical characteristics. Subgroup comparisons based on gender, oncological diagnosis types, education continuum status, psychopathology presence, and psychopharmacological treatment requirement were conducted using Pearson's chi‐square ( χ 2 ) or Fisher's exact tests (when expected frequencies were less than five per cell) for categorical variables, and Mann–Whitney U‐tests or Kruskal–Wallis tests for continuous variables. Post hoc tests were applied for multiple group comparisons. p ‐values were derived from two‐tailed tests with an alpha level of 0.05, with Bonferroni correction applied as needed. Multivariate logistic regression analyses (in line with “entered” mode) were employed to identify predictors of psychiatric diagnoses and psychopharmacological intervention requirements. Univariate analyses of variables associated with the dependent variables were performed using chi‐square or Fisher's exact tests. Model fit was evaluated using Hosmer‐Lemeshow goodness‐of‐fit statistics, with explanatory power assessed via Cox & Snell and Nagelkerke R 2 values. 

Results 3.1 Sociodemographic Characteristics of the Sample Among the 97 pediatric oncology patients referred to CLP, the mean age was 9.71 years (SD = 5.11, range: 1–19 years); 64.9% ( n = 63) were male, and 35.1% ( n = 34) were female. The average age at oncological diagnosis was 8.62 years (SD = 5.04, range: 1–17 years). According to current information obtained from parent calls, 82 (84.5%) patients were alive, 10 (10.3%) patients had passed away, and the status of 5 (5.2%) patients was unknown. Among these, five patients of foreign nationality were unreachable due to having returned to their home countries; their current status was gathered from hospital records. Regarding educational continuity, 31 patients (32%) were still enrolled in formal education, while 37 (38.1%) had discontinued education at various levels, primarily due to their oncological illness. For 29 patients (29.9%), the continuation status was unclear. For those continuing education, the average duration was 6.1 years (SD = 4.07, range: 0–12 years). Notably, patients who were unable to continue education generally did not progress beyond their age‐appropriate level after diagnosis, and those diagnosed during preschool years often experienced delays in school entry. Parental and family demographics are summarized in Table . A significant portion of the sample (72.2%; n = 70) had low SES based on HRI scores, while 25.8% ( n = 25) had medium SES, and 2.1% ( n = 2) had high SES. Family structures varied, with most children living in nuclear families (78.4%; n = 76), followed by extended families (11.3%; n = 11), single‐parent families (7.2%; n = 7), and other arrangements (3.1%; n = 3). The majority of parents (86.6%; n = 84) were married, with 10.3% ( n = 10) divorced, 2.1% ( n = 2) separated, and 1% ( n = 1) had a deceased parent. Approximately 91% of mothers were unemployed, with 20.6% attributing unemployment to the need to care for their ill child, 53.6% citing reasons unrelated to the illness, and 5.2% not specifying a reason. 3.2 Oncological and CLP‐Related Clinical Characteristics The majority of diagnoses fell within the lymphoma‐leukemia group (55.7%; n = 54), with specific breakdowns including B ALL (20.6%), pre‐B ALL (12.4%), T‐ALL (7.2%), NHL (6.2%), AML (6.2%), and HL (4.1%). Other diagnoses included cranial tumors (15.5%), osteosarcoma (10.3%), germ cell tumors, including yolk sac tumor and paratesticular embryonal rhabdomyosarcoma (4.1%), neuroblastoma (2.1%), Wilms tumor (2.1%), neuroendocrine tumors (2.1%), and aplastic anemia (2.1%) (see Figure and Table ). The most common localization of cranial tumors was posterior fossa, whereas the most prevalent one was medulloblastoma, followed by diffuse pontine glioma and other glial tumors, ependymoma, pilocytic astrocytoma, clivus tumor, and craniopharyngioma. Approximately 80% of patients underwent chemotherapy, and 32% required surgical interventions (Table ). The average total hospitalization duration was 126 months (SD = 124.8, range: 2–780 months), with a mean of 5.36 hospitalizations per patient (SD = 4.78, range: 1–21). Intensive care admissions averaged 4.84 months (SD = 22.85, range: 0–220 months). The mean age at first psychiatric referral was 9.06 years (SD = 5.11, range: 1–17 years), and the average number of psychiatric consultations was 2.71 per patient (SD = 2.12, range: 1–10). Table provides additional data on consultation reasons and who initiated the referrals. The majority of cases (75.3%) were referred for psychiatric interventions related to complaints observed by oncologists. Notably, most cases had at least one psychopathology (75.3%) and primary intervention of psychiatrists was to the psychopathological symptoms rather than “counseling/support to diagnosis process” or “refusal to oncological treatments”. Common psychiatric symptoms included depression (36.1%), adjustment disorder (35.1%), sleep disorders (23.7%), anxiety disorders (21.6%), and conduct disorders (21.6%). Psychotropic medications were prescribed to 57.7% of patients, and psychotherapeutic interventions were provided to 28.9%. Psychotropic treatments included SSRIs, antipsychotics, benzodiazepines, and other agents (see Figure and Table ). Multiple psychotropic use (SSRI+AP, SSRI+BNZ, SSRI+hydroxyzine HCl, or AP+BNZ) was preferred in 11 cases (19.6%), while single psychotropic use (monotherapy) was noted in the remaining cases (Figure ). Follow‐up in the CLP unit averaged 2.37 months (SD: 3.18, min–max: 0–14 months), and psychiatric treatment duration was 2.09 months (SD: 2.87, min–max: 0–13 months). Approximately 60% of the patients did not continue their psychiatric follow‐up post‐discharge. The dosage ranges for the preparations were noted as 2.5–20 mg/g for fluoxetine, 12.5–50 mg/g for sertraline, 2.5–10 mg/g for escitalopram, 0.5–1 mg/g for risperidone, 0.5–2 mg/g for haloperidol, 12.5–50 mg/g for quetiapine, and 0.5–5 mg/g for lorazepam. 3.2.1 Comparison of Demographics and Clinical Characteristics by Gender No significant gender differences were found for demographic or clinical features, oncological diagnosis distribution, psychiatric consultation scope, treatment needs, follow‐up, or treatment duration. However, adjustment disorders were more prevalent among females ( p = 0.023, X 2 : 5.138), while depression showed a non‐significant trend toward being more common in males ( p = 0.059, X 2 : 3.577 with 42.9% in males vs. 23.5% in females). 3.3 Comparison by Educational Continuity To explore relationships between educational status and psychiatric conditions, cases with known educational continuity ( n = 68) were divided into two groups for comparison. No statistically significant difference was found in terms of gender ( p = 0.59), age ( p = 0.185), and other demographic characteristics. No difference was found between the groups by attending formal education in terms of clinical characteristics of oncological or psychiatric disorders. However, only depression diagnosis was found to be significantly more frequent in patients who did not attend formal education compared to opponents who attended ( n  = 24 [64.9%] versus 8 [25.8%]) ( p = 0.001, X 2 : 10.33, df:1). 3.4 Comparison by Oncological Diagnoses When grouped by diagnosis type (e.g., lymphoma‐leukemia vs. other cancers), no significant differences were observed in psychopathology rates, psychiatric diagnosis distribution, or treatment options. No difference was found between the groups in terms of the distribution of demographic parameters. However, the lymphoma‐leukemia group had a predominance of low SES, while medium SES was more common in other cancer types ( p = 0.021). Patients with non‐lymphoma‐leukemia diagnoses had more intensive care needs ( p = 0.002), while lymphoma‐leukemia patients had longer hospitalization durations ( p = 0.008). Sleep disorders were more prevalent in patients with non‐lymphoma‐leukemia diagnoses ( p = 0.015) (Table ). 3.5 Comparison by Psychopathology Presence To examine the relationship between the presence of psychopathology and demographic/clinical characteristics, cases with psychopathology ( n = 73) were compared with their counterparts without psychopathology ( n = 24) in terms of study parameters. Psychopathology was not associated with gender, age, educational continuity, parental marital status, or family structure. However, lower SES ( p = 0.022, X 2 : 7.63, df: 2) and older parental age (age of mothers: p = 0.024, t : −2.301, df: 95 and age of fathers: p = 0.028, t : −2.238, df: 95) were associated with higher psychopathology rates. Additionally, steroid use was more common among patients with psychopathology ( p = 0.039, X 2 : 4.253, df: 1), and these patients had longer psychiatric follow‐up ( p = 0.006, t : −2.826, df: 95) and treatment durations ( p = 0.010, t : −2.632, df: 95). The groups differed in terms of “the scope of psychiatric consultation determined by oncologists” ( p = 0.023, likelihood ratio: 11.314, df:4) and “the rationale of psychiatric consultation, being attributed by psychiatrists” ( p > 0.001, likelihood ratio: 34.520, df: 8). However, it was notably observed that 58.3% of the cases in which no psychopathological condition was diagnosed were consulted within the scope of intervention in psychiatric symptoms, while psychiatric diagnoses were detected in 41.7% of the patients who were consulted within the scope of general psychiatric evaluation. The statistical findings related to logistic regression analysis of parameters varied by the presence of psychopathology were pretty pointless. When a potential model was created with the independent variables (such as older mother age, older father age, lower SES , and steroid use ) according to findings of the univariate analysis and their clinical importance in predicting the dependent variable ( presence of psychopathology ), the significance level of the model in enter mode was detected as statistically meaningless ( p = 0.145, X 2 : 8.204, df:5), however with low predictability (Cox & Snell R 2 : 0.081, Nagelkerke R 2 : 0.109) and an appropriate model fit (Hosmer & Lemeshow Test: p = 0.835), as summarized in Table . 3.6 Comparison by Psychopharmacological Intervention Requirement Patients requiring psychopharmacological interventions ( n = 56) were not significantly different in gender, educational continuity, or SES. However, intensive care requirements were associated with a higher need for psychopharmacology ( p = 0.016, X 2 : 5.82, df:1). Among patients needing psychopharmacology, 83.9% were referred for psychiatric complaints, primarily agitation and depressive symptoms ( p = 0.024, likelihood ratio: 11.234, df: 4). The groups by psychopharmacology requirement also differed by the rationale of psychiatric consultation noted by psychiatrists ( p = 0.033, likelihood ratio:16.771, df:8). The patients having psychopharmacology requirement (60.7%) more frequently continued their psychiatric follow‐up than opponents (12.2%) ( p < 0.001, X 2 : 23.178, df:1). Logistic regression analysis (Table ) indicated that ICU requirements and psychiatric consultation rationale were significant predictors for psychopharmacology ( p = 0.012, X 2 : 27.07, df:13), though with modest explanatory power (Cox & Snell R 2 : 0.244, Nagelkerke R 2 : 0.327) and a good model fit (Hosmer & Lemeshow Test: p = 0.981). 

Sociodemographic Characteristics of the Sample Among the 97 pediatric oncology patients referred to CLP, the mean age was 9.71 years (SD = 5.11, range: 1–19 years); 64.9% ( n = 63) were male, and 35.1% ( n = 34) were female. The average age at oncological diagnosis was 8.62 years (SD = 5.04, range: 1–17 years). According to current information obtained from parent calls, 82 (84.5%) patients were alive, 10 (10.3%) patients had passed away, and the status of 5 (5.2%) patients was unknown. Among these, five patients of foreign nationality were unreachable due to having returned to their home countries; their current status was gathered from hospital records. Regarding educational continuity, 31 patients (32%) were still enrolled in formal education, while 37 (38.1%) had discontinued education at various levels, primarily due to their oncological illness. For 29 patients (29.9%), the continuation status was unclear. For those continuing education, the average duration was 6.1 years (SD = 4.07, range: 0–12 years). Notably, patients who were unable to continue education generally did not progress beyond their age‐appropriate level after diagnosis, and those diagnosed during preschool years often experienced delays in school entry. Parental and family demographics are summarized in Table . A significant portion of the sample (72.2%; n = 70) had low SES based on HRI scores, while 25.8% ( n = 25) had medium SES, and 2.1% ( n = 2) had high SES. Family structures varied, with most children living in nuclear families (78.4%; n = 76), followed by extended families (11.3%; n = 11), single‐parent families (7.2%; n = 7), and other arrangements (3.1%; n = 3). The majority of parents (86.6%; n = 84) were married, with 10.3% ( n = 10) divorced, 2.1% ( n = 2) separated, and 1% ( n = 1) had a deceased parent. Approximately 91% of mothers were unemployed, with 20.6% attributing unemployment to the need to care for their ill child, 53.6% citing reasons unrelated to the illness, and 5.2% not specifying a reason. 

Oncological and CLP‐Related Clinical Characteristics The majority of diagnoses fell within the lymphoma‐leukemia group (55.7%; n = 54), with specific breakdowns including B ALL (20.6%), pre‐B ALL (12.4%), T‐ALL (7.2%), NHL (6.2%), AML (6.2%), and HL (4.1%). Other diagnoses included cranial tumors (15.5%), osteosarcoma (10.3%), germ cell tumors, including yolk sac tumor and paratesticular embryonal rhabdomyosarcoma (4.1%), neuroblastoma (2.1%), Wilms tumor (2.1%), neuroendocrine tumors (2.1%), and aplastic anemia (2.1%) (see Figure and Table ). The most common localization of cranial tumors was posterior fossa, whereas the most prevalent one was medulloblastoma, followed by diffuse pontine glioma and other glial tumors, ependymoma, pilocytic astrocytoma, clivus tumor, and craniopharyngioma. Approximately 80% of patients underwent chemotherapy, and 32% required surgical interventions (Table ). The average total hospitalization duration was 126 months (SD = 124.8, range: 2–780 months), with a mean of 5.36 hospitalizations per patient (SD = 4.78, range: 1–21). Intensive care admissions averaged 4.84 months (SD = 22.85, range: 0–220 months). The mean age at first psychiatric referral was 9.06 years (SD = 5.11, range: 1–17 years), and the average number of psychiatric consultations was 2.71 per patient (SD = 2.12, range: 1–10). Table provides additional data on consultation reasons and who initiated the referrals. The majority of cases (75.3%) were referred for psychiatric interventions related to complaints observed by oncologists. Notably, most cases had at least one psychopathology (75.3%) and primary intervention of psychiatrists was to the psychopathological symptoms rather than “counseling/support to diagnosis process” or “refusal to oncological treatments”. Common psychiatric symptoms included depression (36.1%), adjustment disorder (35.1%), sleep disorders (23.7%), anxiety disorders (21.6%), and conduct disorders (21.6%). Psychotropic medications were prescribed to 57.7% of patients, and psychotherapeutic interventions were provided to 28.9%. Psychotropic treatments included SSRIs, antipsychotics, benzodiazepines, and other agents (see Figure and Table ). Multiple psychotropic use (SSRI+AP, SSRI+BNZ, SSRI+hydroxyzine HCl, or AP+BNZ) was preferred in 11 cases (19.6%), while single psychotropic use (monotherapy) was noted in the remaining cases (Figure ). Follow‐up in the CLP unit averaged 2.37 months (SD: 3.18, min–max: 0–14 months), and psychiatric treatment duration was 2.09 months (SD: 2.87, min–max: 0–13 months). Approximately 60% of the patients did not continue their psychiatric follow‐up post‐discharge. The dosage ranges for the preparations were noted as 2.5–20 mg/g for fluoxetine, 12.5–50 mg/g for sertraline, 2.5–10 mg/g for escitalopram, 0.5–1 mg/g for risperidone, 0.5–2 mg/g for haloperidol, 12.5–50 mg/g for quetiapine, and 0.5–5 mg/g for lorazepam. 3.2.1 Comparison of Demographics and Clinical Characteristics by Gender No significant gender differences were found for demographic or clinical features, oncological diagnosis distribution, psychiatric consultation scope, treatment needs, follow‐up, or treatment duration. However, adjustment disorders were more prevalent among females ( p = 0.023, X 2 : 5.138), while depression showed a non‐significant trend toward being more common in males ( p = 0.059, X 2 : 3.577 with 42.9% in males vs. 23.5% in females). 

Comparison of Demographics and Clinical Characteristics by Gender No significant gender differences were found for demographic or clinical features, oncological diagnosis distribution, psychiatric consultation scope, treatment needs, follow‐up, or treatment duration. However, adjustment disorders were more prevalent among females ( p = 0.023, X 2 : 5.138), while depression showed a non‐significant trend toward being more common in males ( p = 0.059, X 2 : 3.577 with 42.9% in males vs. 23.5% in females). 

Comparison by Educational Continuity To explore relationships between educational status and psychiatric conditions, cases with known educational continuity ( n = 68) were divided into two groups for comparison. No statistically significant difference was found in terms of gender ( p = 0.59), age ( p = 0.185), and other demographic characteristics. No difference was found between the groups by attending formal education in terms of clinical characteristics of oncological or psychiatric disorders. However, only depression diagnosis was found to be significantly more frequent in patients who did not attend formal education compared to opponents who attended ( n  = 24 [64.9%] versus 8 [25.8%]) ( p = 0.001, X 2 : 10.33, df:1). 

Comparison by Oncological Diagnoses When grouped by diagnosis type (e.g., lymphoma‐leukemia vs. other cancers), no significant differences were observed in psychopathology rates, psychiatric diagnosis distribution, or treatment options. No difference was found between the groups in terms of the distribution of demographic parameters. However, the lymphoma‐leukemia group had a predominance of low SES, while medium SES was more common in other cancer types ( p = 0.021). Patients with non‐lymphoma‐leukemia diagnoses had more intensive care needs ( p = 0.002), while lymphoma‐leukemia patients had longer hospitalization durations ( p = 0.008). Sleep disorders were more prevalent in patients with non‐lymphoma‐leukemia diagnoses ( p = 0.015) (Table ). 

Comparison by Psychopathology Presence To examine the relationship between the presence of psychopathology and demographic/clinical characteristics, cases with psychopathology ( n = 73) were compared with their counterparts without psychopathology ( n = 24) in terms of study parameters. Psychopathology was not associated with gender, age, educational continuity, parental marital status, or family structure. However, lower SES ( p = 0.022, X 2 : 7.63, df: 2) and older parental age (age of mothers: p = 0.024, t : −2.301, df: 95 and age of fathers: p = 0.028, t : −2.238, df: 95) were associated with higher psychopathology rates. Additionally, steroid use was more common among patients with psychopathology ( p = 0.039, X 2 : 4.253, df: 1), and these patients had longer psychiatric follow‐up ( p = 0.006, t : −2.826, df: 95) and treatment durations ( p = 0.010, t : −2.632, df: 95). The groups differed in terms of “the scope of psychiatric consultation determined by oncologists” ( p = 0.023, likelihood ratio: 11.314, df:4) and “the rationale of psychiatric consultation, being attributed by psychiatrists” ( p > 0.001, likelihood ratio: 34.520, df: 8). However, it was notably observed that 58.3% of the cases in which no psychopathological condition was diagnosed were consulted within the scope of intervention in psychiatric symptoms, while psychiatric diagnoses were detected in 41.7% of the patients who were consulted within the scope of general psychiatric evaluation. The statistical findings related to logistic regression analysis of parameters varied by the presence of psychopathology were pretty pointless. When a potential model was created with the independent variables (such as older mother age, older father age, lower SES , and steroid use ) according to findings of the univariate analysis and their clinical importance in predicting the dependent variable ( presence of psychopathology ), the significance level of the model in enter mode was detected as statistically meaningless ( p = 0.145, X 2 : 8.204, df:5), however with low predictability (Cox & Snell R 2 : 0.081, Nagelkerke R 2 : 0.109) and an appropriate model fit (Hosmer & Lemeshow Test: p = 0.835), as summarized in Table . 

Comparison by Psychopharmacological Intervention Requirement Patients requiring psychopharmacological interventions ( n = 56) were not significantly different in gender, educational continuity, or SES. However, intensive care requirements were associated with a higher need for psychopharmacology ( p = 0.016, X 2 : 5.82, df:1). Among patients needing psychopharmacology, 83.9% were referred for psychiatric complaints, primarily agitation and depressive symptoms ( p = 0.024, likelihood ratio: 11.234, df: 4). The groups by psychopharmacology requirement also differed by the rationale of psychiatric consultation noted by psychiatrists ( p = 0.033, likelihood ratio:16.771, df:8). The patients having psychopharmacology requirement (60.7%) more frequently continued their psychiatric follow‐up than opponents (12.2%) ( p < 0.001, X 2 : 23.178, df:1). Logistic regression analysis (Table ) indicated that ICU requirements and psychiatric consultation rationale were significant predictors for psychopharmacology ( p = 0.012, X 2 : 27.07, df:13), though with modest explanatory power (Cox & Snell R 2 : 0.244, Nagelkerke R 2 : 0.327) and a good model fit (Hosmer & Lemeshow Test: p = 0.981). 

Discussion In this study, we examined the sociodemographic and psychiatric/oncological clinical profiles of pediatric oncology patients in the framework of structured CLP services, emphasizing the intersections of SES, parental employment, opportunities in education continuum, and mental health outcomes, and aligning our findings with established standards and recent advancements in pediatric psycho‐oncology. Emerging literature emphasizes the critical role of psychosocial standards, as pediatric cancer has profound effects not only on patients' mental health but also on family dynamics and educational progress. Studies by Steele et al. (2015), Wiener et al. (2020), Burns et al. (2021), and Friedman et al. (2023) highlight the importance of structured psychosocial and educational interventions, such as the Psychosocial Standards of Care (PSSC) in pediatric oncology, to mitigate long‐term mental health challenges in young cancer patients and survivors . In line with PSSC guidelines, school re‐entry supports for cancer survivors should include liaison personnel to coordinate communication between families, hospitals, and schools, as well as annual evaluations for neurocognitive late effects and academic progress . Our study identified that approximately 40% of the cases discontinued formal education, primarily due to their oncological illness, with depression being notably higher in this group. Additionally, a significant number of mothers reported unemployment, with one in five directly attributing their job loss to the need to care for their child. The majority of cases (over 70%) was of low SES, with around 25% of medium SES. Low socioeconomic status may contribute to both parental job loss and high health care costs. The study by Lau et al. also pointed out that during children's active treatment, parents' professional lives were seriously compromised, as 46% were at risk of loss of employment, 51% had decreased opportunities to work, and 68% had to reduce their work hours . Similarly, a study from Sweden found that mothers' earnings decreased by 21% and fathers' by 10% during the year of their child's cancer diagnosis compared to control groups . Literature on parental psychological health indicates poorer physical and psychosocial quality of life, with elevated levels of anxiety, depression, sleep disturbances, somatic symptoms, and post‐traumatic stress . Our findings also indicate that psychopathology is associated with low SES, older parental age, and steroid use as part of oncological treatment, though the predictive power of these variables in regression analyses was modest. Barrera et al. (2020) argue that effective psychosocial screening in pediatric oncology is critical but often underutilized. The current study's emphasis on routine psychiatric evaluations for all referred cases aligns with their recommendation for systematic screening to ensure early intervention . The current data corroborate the need for early and continuous psychiatric intervention, particularly for low SES groups who exhibit higher psychopathology rates. Zheng et al. (2021) documented disparities in access to psychiatric services in pediatric oncology based on SES and other sociodemographic factors . Addressing these disparities is essential, as untreated psychological distress can exacerbate treatment challenges, including non‐compliance and social isolation . Similarly, Zhang et al. (2021) emphasize the effectiveness of tailored psychosocial interventions, particularly those delivered through digital platforms, to support underserved populations . Integrating these insights into routine care can improve outcomes for patients with high psychological needs, supporting our hypothesis on the link between SES and psychiatric morbidity. The general type and subtype distribution of oncological diseases reported in the cases in this study is consistent with the recent epidemiological data, with the lymphoma‐leukemia group being dominant. According to the latest data, leukemias (28%) and central/peripheral nervous system tumors (25%) are the most prevalent cancers in children, although the distribution shifts in adolescence . The average age at oncological diagnosis (8.62 years) and first psychiatric consultation (around 9 years) indicate that cases have psychiatric needs often arise within the first year after diagnosis. Most referrals were initiated by oncologists for specific psychiatric complaints, which generally matched the psychopathology diagnoses made by psychiatrists. However, it was notable that around 58% of cases with no psychiatric diagnosis were referred with a request to address psychiatric symptoms, while 42% of cases referred for general evaluation were later diagnosed with psychopathology. This supports findings by Peled et al. (2020), who observed discrepancies between oncologists' perceptions and psychiatric diagnoses . Our results highlight the need for early structured psychiatric liaison services following cancer diagnosis to better manage psychiatric and psychosocial challenges in pediatric patients. Early intervention may yield more positive outcomes, as chronic illness and prolonged hospitalization often lead to stress and adaptation difficulties that oncologists may interpret as psychiatric symptoms . Kearney et al. (20016) emphasize structured assessments for early detection of psychiatric needs , aligning with our study's methodology using structured clinical interviews (K‐SADS‐PL‐DSM‐5) for diagnosing and managing psychiatric symptoms. The most frequently identified psychopathologies were depression, adjustment disorder, sleep disorders, anxiety disorders, and behavioral disorders (primarily the opposite defiant disorders), and it was observed that internalization problems were predominantly common, consistent with the rates in similar previous studies . Despite recent medical advances and significant improvements in 5‐year cancer survival rates, most pediatric cancer survivors experience adverse late, long‐term, or persistent medical, behavioral, psychosocial, spiritual, and/or existential outcomes cause by cancer or cancer treatments . Integrating psychosocial, behavioral, and supportive interventions, such as motivational interviewing, psycho‐educational programs, and online peer support groups, into routine care is essential . However, our findings suggest that oncologists typically consult psychiatrists for active symptoms rather than preventive reasons, such as providing psychological support for diagnosis or structuring coping skills. This reactive approach may limit the full potential of psychosocial care, as emphasized in optimal care standards which prioritize structuring psychosocial support through early‐stage consultations before the onset of psychiatric symptoms . 4.1 Clinical and Research Implications Current findings emphasize the significance of early, structured psychiatric interventions for enhancing mental health outcomes and addressing SES‐based disparities in access to mental health resources. In Türkiye, limited data exist on the psychiatric needs of this population and how socio‐demographic factors intersect with these needs. This gap hampers the development of evidence‐based interventions tailored to the region's unique sociocultural and healthcare contexts. Previous studies have often focused on adult cancer patients or have limited their scope to general psychosocial outcomes without delving into specific psychiatric diagnoses. Furthermore, few studies have utilized structured psychiatric assessments, such as the K‐SADS‐PL‐DSM‐5, in routine evaluations, leaving a substantial gap in standardized psychiatric data for pediatric oncology patients in this context. 4.2 Study Limitations There are potential methodological limitations of this study, such as sample size, generalizability to other clinical settings, and retrospective evaluation of clinical data which limits the correct interpretation of the causality of the relationships detected between clinical and demographic findings. Therefore, further research with larger sample size and a follow‐up longitudinal study design is essential for a more understanding of psychiatric needs over time and for clarification of causal association between psychosocial risk factors, clinical setting, and psychiatric progress, as well as understanding the underlying factors of treatment adherence and outcomes. 

Clinical and Research Implications Current findings emphasize the significance of early, structured psychiatric interventions for enhancing mental health outcomes and addressing SES‐based disparities in access to mental health resources. In Türkiye, limited data exist on the psychiatric needs of this population and how socio‐demographic factors intersect with these needs. This gap hampers the development of evidence‐based interventions tailored to the region's unique sociocultural and healthcare contexts. Previous studies have often focused on adult cancer patients or have limited their scope to general psychosocial outcomes without delving into specific psychiatric diagnoses. Furthermore, few studies have utilized structured psychiatric assessments, such as the K‐SADS‐PL‐DSM‐5, in routine evaluations, leaving a substantial gap in standardized psychiatric data for pediatric oncology patients in this context. 

Study Limitations There are potential methodological limitations of this study, such as sample size, generalizability to other clinical settings, and retrospective evaluation of clinical data which limits the correct interpretation of the causality of the relationships detected between clinical and demographic findings. Therefore, further research with larger sample size and a follow‐up longitudinal study design is essential for a more understanding of psychiatric needs over time and for clarification of causal association between psychosocial risk factors, clinical setting, and psychiatric progress, as well as understanding the underlying factors of treatment adherence and outcomes. 

Conclusions Our study highlights the critical role of sociodemographic disparities‐sensitive psychiatric and educational support in pediatric oncology and suggests that psychosocial standards, coupled with clinician support mechanisms, are essential for comprehensive care. Future research should explore the impact of digital interventions and interdisciplinary care models on improving access and efficacy of psychosocial support in pediatric oncology. 

Conceptualization: A.E. Methodology: A.E., Y.S.Ç. Software: A.E., Y.S.Ç., M.K., Ş.S.M., Z.B.Ö., S.N.K., E.N.Ş., G.S., S.M., A.F.K., V.S.Y.K., Ü.B.G., D.C., R.N., M.C., B.Ş. Validation: A.E., Y.S.Ç., M.K. Investigation: A.E., Y.S.Ç., M.K., Ş.S.M., Z.B.Ö., S.N.K., E.N.Ş., G.S., S.M., A.F.K., V.S.Y.K., Ü.B.G., D.C., R.N., M.C., B.Ş., Y.Ö. Formal analysis: A.E., Y.Ö. Resources: A.E., Y.S.Ç., M.K., Ş.S.M., Z.B.Ö., S.N.K., E.N.Ş., G.S., S.M., A.F.K., V.S.Y.K., Ü.B.G., D.C., R.N., M.C., B.Ş., Y.Ö. Data Curation: A.E., M.K., Y.Ö. Writing–Original Draft: A.E. Writing–review and editing: A.E., Y.Ö. Visualization: A.E., M.K., Y.Ö. Supervision: A.E., Y.Ö. 

The research protocol was approved by the local ethical committee on July 31, 2024 (ethics committee protocol number: AESH‐BADEK‐2024‐512). The study was conducted in accordance with the Declaration of Helsinki, and the written informed consent was obtained from all participants and their parents before the onset of the study. 

The authors declare no conflicts of interest. 

