Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: Suicide poses a significant public health concern with increasing prevalence in the general population, emphasizing the need for effective gatekeeper suicide prevention education. This study assesses the longitudinal effectiveness of the “Suicide CARE” gatekeeper training program within a general community sample. Suicide CARE is representative gatekeeper program in Korea. A total of 5 million individuals completed the training program of Suicide CARE in Korea to date. Methods: Participants were recruited through the Korea Suicide Prevention Association website, randomly assigned to the experimental (n=49) or control group (n=53). Pre- and post-training surveys, along with a 3-month follow-up, measured perceived knowledge, gatekeeper efficacy, preparedness, and attitudes toward suicide. Longitudinal effects were analyzed using repeated measures analysis of variance. Results: The experimental group showed significant improvement in perceived knowledge, gatekeeper efficacy, perceived preparedness, and some aspects of attitude towards suicide compared to the control group, with effects declining over time but remaining statistically significant at the 3-month follow-up test. Conclusion This study is the first to evaluate the longitudinal effectiveness of Suicide CARE in a community population. Strategic integration of evidence-based gatekeeper training programs like Suicide CARE can contribute to community suicide prevention initiatives.