Objective: Dentists encounter unique occupational challenges, including stress, depression, and anxiety, that can impact their mental well-being. Therefore, it is essential to identify dentists’ mental health statuses and the factors influencing them. Understanding the heterogeneity in dentists’ mental health is crucial for tailored interventions. To investigate different mental health profiles within the dentist population and understand the characteristics of each type. Methods: In this cross-sectional study, we surveyed 261 Korean dentists from a sample of 1,520. Using latent profile analysis, participants were classified into distinct mental health profiles based on self-reported stress, depressive symptoms, anxiety, and sleep quality. Demographic and occupational variables were analyzed to explore their association with mental health profiles. Results: Three distinct mental health profiles were identified: high, moderate, and low. Factors such as drinking frequency, socioeconomic status, income, and work hours significantly influenced profile classification. Significant differences in job satisfaction were observed among the profiles. Conclusion This study underscores the importance of personalized interventions to address the specific needs of each mental health profile, aiming to improve job satisfaction and overall mental health in the dental profession.

Objective: Dentists encounter unique occupational challenges, including stress, depression, and anxiety, that can impact their mental well-being. Therefore, it is essential to identify dentists’ mental health statuses and the factors influencing them. Understanding the heterogeneity in dentists’ mental health is crucial for tailored interventions. To investigate different mental health profiles within the dentist population and understand the characteristics of each type. Methods: In this cross-sectional study, we surveyed 261 Korean dentists from a sample of 1,520. Using latent profile analysis, participants were classified into distinct mental health profiles based on self-reported stress, depressive symptoms, anxiety, and sleep quality. Demographic and occupational variables were analyzed to explore their association with mental health profiles. Results: Three distinct mental health profiles were identified: high, moderate, and low. Factors such as drinking frequency, socioeconomic status, income, and work hours significantly influenced profile classification. Significant differences in job satisfaction were observed among the profiles. Conclusion This study underscores the importance of personalized interventions to address the specific needs of each mental health profile, aiming to improve job satisfaction and overall mental health in the dental profession.

Objective: Dentists encounter unique occupational challenges, including stress, depression, and anxiety, that can impact their mental well-being. Therefore, it is essential to identify dentists’ mental health statuses and the factors influencing them. Understanding the heterogeneity in dentists’ mental health is crucial for tailored interventions. To investigate different mental health profiles within the dentist population and understand the characteristics of each type. Methods: In this cross-sectional study, we surveyed 261 Korean dentists from a sample of 1,520. Using latent profile analysis, participants were classified into distinct mental health profiles based on self-reported stress, depressive symptoms, anxiety, and sleep quality. Demographic and occupational variables were analyzed to explore their association with mental health profiles. Results: Three distinct mental health profiles were identified: high, moderate, and low. Factors such as drinking frequency, socioeconomic status, income, and work hours significantly influenced profile classification. Significant differences in job satisfaction were observed among the profiles. Conclusion This study underscores the importance of personalized interventions to address the specific needs of each mental health profile, aiming to improve job satisfaction and overall mental health in the dental profession.

Objective: Dentists encounter unique occupational challenges, including stress, depression, and anxiety, that can impact their mental well-being. Therefore, it is essential to identify dentists’ mental health statuses and the factors influencing them. Understanding the heterogeneity in dentists’ mental health is crucial for tailored interventions. To investigate different mental health profiles within the dentist population and understand the characteristics of each type. Methods: In this cross-sectional study, we surveyed 261 Korean dentists from a sample of 1,520. Using latent profile analysis, participants were classified into distinct mental health profiles based on self-reported stress, depressive symptoms, anxiety, and sleep quality. Demographic and occupational variables were analyzed to explore their association with mental health profiles. Results: Three distinct mental health profiles were identified: high, moderate, and low. Factors such as drinking frequency, socioeconomic status, income, and work hours significantly influenced profile classification. Significant differences in job satisfaction were observed among the profiles. Conclusion This study underscores the importance of personalized interventions to address the specific needs of each mental health profile, aiming to improve job satisfaction and overall mental health in the dental profession.

Objective: Dentists encounter unique occupational challenges, including stress, depression, and anxiety, that can impact their mental well-being. Therefore, it is essential to identify dentists’ mental health statuses and the factors influencing them. Understanding the heterogeneity in dentists’ mental health is crucial for tailored interventions. To investigate different mental health profiles within the dentist population and understand the characteristics of each type. Methods: In this cross-sectional study, we surveyed 261 Korean dentists from a sample of 1,520. Using latent profile analysis, participants were classified into distinct mental health profiles based on self-reported stress, depressive symptoms, anxiety, and sleep quality. Demographic and occupational variables were analyzed to explore their association with mental health profiles. Results: Three distinct mental health profiles were identified: high, moderate, and low. Factors such as drinking frequency, socioeconomic status, income, and work hours significantly influenced profile classification. Significant differences in job satisfaction were observed among the profiles. Conclusion This study underscores the importance of personalized interventions to address the specific needs of each mental health profile, aiming to improve job satisfaction and overall mental health in the dental profession.

OBJECTIVE: Bipolar disorder (BD) is characterized by elevated impulsivity, even during periods of remission. Many recovered BD patients have functional impairments, which can lead to poor quality of life (QoL). The aim of this study was to investigate the association between impulsivity and QoL in euthymic BD patients. METHODS: A total of 56 remitted or recovered patients with type I or II BD, diagnosed based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria, were recruited. Psychiatrists administered the Clinical Global Impression (CGI) for BD and the Global Assessment of Functioning (GAF) scales and then interviewed the subjects to assess clinical variables. Patients completed the Barratt Impulsiveness Scale (BIS-11) and the World Health Organization Quality of Life Assessment Instrument-Brief Form (WHOQoL-BREF). Pearson correlations, univariate regression analyses, and multiple linear regression analyses were performed. RESULTS: The BIS-11 total score was significantly correlated with the WHOQoL-BREF total score (r=-0.55, p<0.01) and with the WHOQoL-BREF subscales. After controlling for GAF score and other clinical variables, the BIS-11 total score (beta=-0.43, p=0.001) was independently associated with overall QoL. Additionally, the BIS-11 total score was particularly strongly associated with the physical, psychological, and social domains of the multi-dimensional QoL scale. CONCLUSION: Our results suggest that high impulsivity is related to low QoL in euthymic BD patients. Further studies are needed to examine whether interventions for high impulsivity effectively improve QoL in patients with BD.
Impulsive Behavior ; Bipolar Disorder* ; Diagnostic and Statistical Manual of Mental Disorders ; Humans ; Linear Models ; Psychiatry ; Quality of Life* ; Weights and Measures ; World Health Organization

Acquisition of resistance to anti-cancer drugs is a significant obstacle to effective cancer treatment. Although several efforts have been made to overcome drug resistance in cancer cells, the detailed mechanisms have not been fully elucidated. Here, we investigated whether microRNAs (miRNAs) function as pivotal regulators in the acquisition of anti-cancer drug resistance to 5-fluorouracil (5-FU). A survey using a lentivirus library containing 572 precursor miRNAs revealed that five miRNAs promoted cell survival after 5-FU treatment in human hepatocellular carcinoma Hep3B cells. Among the five different clones, the clone expressing miR-200a-3p (Hep3B-miR-200a-3p) was further characterized as a 5-FU-resistant cell line. The cell viability and growth rate of Hep3B-miR-200a-3p cells were higher than those of control cells after 5-FU treatment. Ectopic expression of a miR-200a-3p mimic increased, while inhibition of miR-200a-3p downregulated, cell viability in response to 5-FU, doxorubicin, and CDDP (cisplatin). We also showed that dual-specificity phosphatase 6 (DUSP6) is a novel target of miR-200a-3p and regulates resistance to 5-FU. Ectopic expression of DUSP6 mitigated the pro-survival effects of miR-200a-3p. Taken together, these results lead us to propose that miR-200a-3p enhances anti-cancer drug resistance by decreasing DUSP6 expression.
Carcinoma, Hepatocellular ; Cell Line ; Cell Survival ; Clone Cells ; Doxorubicin ; Drug Resistance ; Dual Specificity Phosphatase 6* ; Dual-Specificity Phosphatases* ; Ectopic Gene Expression ; Fluorouracil* ; Humans ; Lentivirus ; MicroRNAs