Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): A systematic review

Association between hikikomori (social withdrawal) and depression in Korean young adults

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental illness, particularly affecting women. The World Health Organization projects that by 2030, MDD will be the leading cause of disease burden. The phenomenon of hikikomori-initially observed in Japan-is increasingly associated with depression, a key risk factor for which is social isolation. This study analyzed the impact of social withdrawal on depression among South Korean young adults, focusing on (1) the relation between withdrawal duration and causes, and (2) its effect on depression severity.

METHODS

Data from the 2022 Korean Youth Survey, including 14,966 participants aged 19-34, were used. Depression levels were assessed using the Patient Health Questionnaire-9 (PHQ-9), and multiple logistic regression was conducted to examine the association between hikikomori behavior and depression.

RESULTS

The reference group for all analyses was youth who were not socially withdrawn. The association between hikikomori and depression was statistically significant for the two sexes (males: OR: 2.25, 95 % CI: 1.60-3.19; females: OR: 2.34, 95 % CI: 1.63-3.36). Household size influenced depression risk among hikikomori, and sex differences were observed in social withdrawal's effect on suicide risk.

CONCLUSION

This study highlights the link between hikikomori and depression in South Korean youth, with sex-specific differences in depression and suicide risk, suggesting the need for tailored mental health programs. Future research should explore the long-term effects of prolonged social withdrawal through longitudinal studies and conduct cross-cultural comparisons of hikikomori.

Acid reflux medication use among adults with depressive symptoms

Emotional stress, including depression, may contribute to increased gastroesophageal reflux disease symptoms. In this paper, we aim to evaluate the associations between depressive symptoms, depressive symptom severity, and symptom clusters with acid reflux medication use, considering the potential interaction effect of sex. Data from the 2007-2018 National Health and Nutrition Examination Survey were used. Participants aged 18 years or older were included if they responded to the depressive symptoms and prescription medication questionnaires. This study included 31,444 participants, of whom 2871 had depressive symptoms. Participants with depressive symptoms had significantly higher odds of using antacids (aOR = 1.735; p < 0.001), histamine-2 receptor antagonists (H2RAs) (aOR = 1.653; p < 0.001), and proton pump inhibitors (PPIs) (aOR = 1.723; p < 0.001). A positive association was also found between depressive symptom severity and the use of antacids (aOR = 1.054; p < 0.001), H2RAs (aOR = 1.048; p < 0.001), and PPIs (aOR = 1.053; p < 0.001). Moreover, increases in cognitive-affective and somatic scores were associated with higher odds of using antacids (aOR = 1.080 for cognitive, 1.102 for somatic; p < 0.001), H2RAs (aOR = 1.078 for cognitive, 1.083 for somatic; p < 0.001), and PPIs (aOR = 1.075 for cognitive, 1.105 for somatic; p < 0.001). No significant sex interaction effects were observed. Adjusted models demonstrated no significant associations between depressive symptoms and the duration of medication use. This study provides evidence of an association between depressive symptoms and acid reflux medication use, highlighting the need to screen for related symptoms in patients with depressive symptoms.

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning

BACKGROUND

Early diagnosis of depression is crucial, and speech-based early diagnosis of depression is promising, but insufficient data and lack of theoretical support make it difficult to be applied. Therefore, it is valuable to combine psychiatric theories, collect speech recognition data for depression, and develop a practicable recognition method for depression.

METHODS

In this study, 24 patients with major depressive disorders (MDDs) and 36 healthy controls (HCs) were recruited to participate in a multi-task speech experiment. Descriptive statistics and tests of variance were used to analyze subjects' personality and speech changes. Subsequently, the speech task with the most depressive cues was explored using the Bidirectional Long - Short Term Memory (Bi-LSTM) algorithm, on which a personality-assisted multitasking deep model, i.e., multi-task attentional temporal convolutional network model (TCN-MTA).

RESULTS

Statistical analyses of speech duration showed that the fable reading, neutral stimulus, and negative stimulus tasks had significant differences on subjects' speech duration, and the negative stimulus task had significant differences between the depressed and control groups (p < 0.001, 0.03, 0.04). Notably, the Big Five personality emotional stability scores were significantly different between the depressed and control groups (0.03). Depression was best identified using Bi-LSTM in negative (Youden index = 0.44) and positive stimulus speech (Youden index = 0.42). Further, the specificity of 0.72 and sensitivity of 0.87 for recognizing depression in negative stimulus speech using our proposed TCN-MTA outperforms existing methods.

LIMITATIONS

The sample size enrolled in this study is higher than the minimum sample size calculated through G-Power 3.1, but the sample size in this study is still small.

CONCLUSION

The proposed deep learning-based personality-assisted multitasking method could accurately recognize major depression, which demonstrated the potential of the method based on the fusion of specialized theories and artificial intelligence.

Longitudinal Effects of Residential Treatment for Eating Disorders: Symptom Trajectories and Predictors of Functional Outcomes

OBJECTIVE

Residential treatment for eating disorders addresses the gap between inpatient and outpatient care, but evidence for longer-term and functional outcomes remains limited. The current study examined both clinical and functional outcomes from admission to a 6-month follow-up from Australia's first residential service for eating disorders.

METHOD

Measures of eating disorder symptoms, body mass index (BMI), anxiety, depression, general and eating disorder-specific health-related quality of life (HRQoL), and functional disability were completed at pretreatment, posttreatment, and 3- and 6-month follow-ups by 81 individuals with eating disorders (Mage = 25.78 years).

RESULTS

Linear mixed effects modeling found that change in outcomes over time was best modeled by a cubic growth curve, such that participants showed a steep improvement from pretreatment to posttreatment followed by a worsening of symptoms by 3 months post-discharge, which tapered off by 6 months post-discharge. Pairwise comparisons indicated significant improvement between pretreatment and posttreatment for all outcomes, and between pretreatment and 6 months post-discharge for all outcomes except mental HRQoL. Treatment gains were maintained after discharge for shape and weight concerns, anxiety, general and eating disorder-specific HRQoL, and functional disability. Greater in-treatment improvement in eating disorder symptoms predicted steeper in-treatment improvement and posttreatment deterioration in eating disorder-specific HRQoL, mental HRQoL, and functional disability. Greater post-discharge mental health support predicted steeper improvement in functional disability.

DISCUSSION

Results support the longitudinal effectiveness of residential treatment for clinical and functional outcomes. However, not all outcomes may maintain the degree of improvement seen at discharge, highlighting the importance of appropriate step-down care.

TRIAL REGISTRATION

Registration number: ACTRN12621001651875.

Association between ketogenic diets and depression: A cross-sectional analysis of the NHANES 2005-2023 August

BACKGROUND

The ketogenic diet (KD) is widely used for epilepsy and neurodegenerative diseases. Glutamate, the excitatory neurotransmitter in the body, has been found to be significantly elevated in the brains of some patients with depression. Ketone bodies, the main products of KD, may negatively regulate the metabolic activity of glutamate, which suggests a potential role in the onset and progression of depression. However, the relationship between KD and depression risk remains uncertain.

METHODS

This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and August 2023 to investigate the association between the ketogenic diet ratio (KDR) and depression risk. Multiple logistic regression analysis was employed to examine this association, whereas nonlinear relationships were assessed using restricted cubic splines. Stratification analysis was employed to examine the association between KDR and depression severity. Subgroup analyses were also performed.

RESULTS

In a fully adjusted model accounting for confounding variables, KDR was significantly associated with depression risk. Two-piecewise linear regression analysis better fitted the association (KDR < 0.35, OR: 0.11; 95%CI: 0.03-0.35; P < 0.001). Subgroup analyses indicated that this association between KDR and depression was particularly pronounced in certain specific populations. We further observed a significant correlation between KDR and depression severity (P < 0.001).

CONCLUSION

Higher KDR was associated with a reduced risk of depression, with potentially greater efficacy observed in specific populations. Additionally, KDR has been found to be significantly associated with the severity of depression. Further study could investigate their potential mechanism.

Association of tobacco use with depressive symptoms in adults: Considerations of symptom severity, symptom clusters, and sex

OBJECTIVE

We aim to assess the association between depressive symptoms, depressive symptom severity and symptom clusters with tobacco use. We will also evaluate sex differences in these associations.

METHOD

This cross-sectional study used data from the National Health and Nutrition Examination Survey (2005-2018). Depressive symptoms were assessed using the Patient Health Questionnaire-9. Tobacco use was categorized into four groups: cigarette use, smoked tobacco products (pipes and cigars), smokeless tobacco products (chewing tobacco and snuff), and non-tobacco use (reference group).

RESULTS

This study included 33,509 participants. Cigarette use was associated with a 0.83-unit increase in total PHQ-9 scores (95% CI =  [0.63, 1.04]), and 1.73 times higher odds of reporting depressive symptoms (95% CI =  [1.48, 2.02]) compared to non-tobacco use. However, the use of smoked and smokeless tobacco was not associated with depressive symptoms. In females, cigarette use showed a stronger association with total PHQ-9 scores (aCoef =  1.23, 95% CI =  [0.92, 1.55]) than in males (aCoef =  0.45, 95% CI =  [0.21, 0.69]). Additionally, female smoked tobacco users showed positive associations with both PHQ-9 scores and the presence of depressive symptoms, but this relationship was not observed in males. Furthermore, subgroup analysis revealed associations between cigarette use and cognitive-affective and somatic symptom clusters, as well as a relationship between the logarithm of total cigarette consumption and depressive symptoms.

CONCLUSION

Cigarette use was associated with higher odds of depressive symptoms with females having a stronger association. Further studies are needed to replicate these findings and examine the underlying mechanisms.

Associations between clustering of hypoglycemic symptoms, psychological traits, and problem-solving abilities in adults with type 1 diabetes: baseline data analysis of the PR-IAH study

Background

Precision medicine in diabetes care requires a dedicated focus on hypoglycemic symptoms. This study explored the associations between clustering of hypoglycemic symptoms, psychological characteristics, and problem-solving capabilities in adults with type 1 diabetes (T1D).

Methods

A total of 251 adults with T1D participated in this survey. Hierarchical clustering was used to analyze 11 hypoglycemic symptoms (Edinburgh scale). The data included diabetic complications, fear of hypoglycemia, depressive symptoms, hypoglycemia problem-solving scale (HPSS), and treatment details. For predicting clusters and identifying feature importance, we utilized a machine learning approach.

Results

Three distinct clusters were observed; individuals not sensitive to autonomic or neuroglycopenic symptoms (cluster 1, n = 138), those sensitive to both autonomic and neuroglycopenic symptoms (cluster 2, n = 19), and those sensitive to autonomic but not neuroglycopenic symptoms (cluster 3, n = 94). Compared to cluster 1, individuals from clusters 2 and 3 were of younger age, had higher fear of hypoglycemia, increased depressive symptoms, and greater use of continuous subcutaneous insulin infusion. Cluster 2 displayed enhanced HPSS scores, indicating better detection control and a more proactive approach to seeking preventive strategies than cluster 1. The accuracy for classifying into 3 clusters using machine learning was 88.2%. The feature importance of random forest model indicated that hunger, shaking, palpitation, sweating, and confusion were the top five important factors for predicting clusters.

Conclusion

This study identified three distinct clusters of adults with T1D. These findings may provide valuable insights for diabetes professionals seeking to educate these individuals on how to manage hypoglycemia effectively.

Trial registration

University Hospital Medical Information Network (UMIN) Center: UMIN000039475); approval date: February 13, 2020.

Depression and Psychological Distress in Patients with Lower Extremity Lymphedema: A Mixed-Method Study

Background: Lower extremity lymphedema is a chronic and incurable condition. Treatment options for lymphedema have continued to advance and prognosis has improved; however, the condition still poses a substantial negative impact on patients' mental health. Therefore, the key questions raised in this study are "How many patients with lower limb lymph have depression symptoms?" and "Are there any differences in the symptoms and distress factors of patients with lower extremity lymphedema, and how do they experience distress?" Methods and Results: A total of 112 lower extremity lymphedema patients from June 2021 to December 2023 were enrolled in the study. Quantitative and qualitative data of patients were collected and analyzed. Participants completed the Patient Health Questionnaire (PHQ-9), and we interviewed participants with moderate/severe depressive symptoms with score ≥10. A total of 83 participants completed this study. Overall, 39.76% of the participants had a PHQ-9 score ≥5, indicating that they had mild depressive symptoms; 13.25% of the participants had a PHQ-9 score ≥10, indicating that they had moderate or severe depressive symptoms. Compared with participants who had received treatment before the study, participants who did not receive any treatment before the study had a higher risk of depression (χ2 = 6.705, p = 0.031). There was no significant difference in the degree of depression in patients with different stages of lymphedema (χ2 = 8.430, p = 0.077). From the qualitative interview data, we extracted five common themes: "loss of self," "isolation from surroundings," "discomfort caused by symptoms and complications," "concern about the progression or deterioration of the original malignant tumor," and "fear that surgical treatment may be ineffective." Conclusions: This study found that patients with lower extremity lymphedema are prone to psychological symptoms of depression. To clarify the reason that affect psychological distress is important information to improve the psychological health support for patients with lower extremity lymphedema.

Frailty Markers and Falls Among US Clergy

Studies examining frailty, physical performance, and falls among the clergy are limited. The objective of the study was to analyze sociodemographic profiles, gait, strength, and falls between diocesan and religious clergy. Participants included eighty-eight male Catholic clergy primarily in the northeast United States. Participants completed a demographic profile and gait velocity and strength measures. Results noted that more diocesan priests were retired (p = .02). Participants with a fall history demonstrated slower gait (p = .001) and weaker grip strength (p = .017) and were more likely to have a fear of falling (p = .009). Findings underscore the importance of fall screening among clergy.

Beyond Cumulative Scores: Distinct Patterns of Adverse Childhood Experiences and Their Differential Impact on Emotion, Borderline Personality Traits, and Executive Function

Adverse childhood experiences (ACEs) are associated with long-lasting and multifaceted consequences for mental health. Despite established dose-response effects of ACEs on mental health, the specificity of ACE pattern effects remains understudied, especially on executive function. This study aims to explore how specific patterns of ACEs, beyond just cumulative scores, differentially impact emotional symptoms, personality and cognitive function. This study recruited 2515 college students from several universities in northern China. Demographic characteristics, depression, anxiety, borderline personality traits, and executive function (Wisconsin Card Sort Test) were assessed. Latent class analysis was used to identify patterns of ACEs. Data were analysed using χ2-test, ANCOVA, and multivariate linear regression methods. Pattern-oriented and cumulative-oriented approaches were compared to predict the effects of ACEs. Three distinct patterns of ACEs were identified: low adversity (LA), multiple adversity (MA), and family environment adversity (FA). FA with the highest number of ACEs was uniquely linked to executive function impairments, while both MA and cumulative ACEs significantly predicted higher anxiety, depression, and borderline personality traits. The pattern-oriented method was more sensitive to capturing the diverse outcomes of executive function impairment than cumulative scores. Our findings highlight the importance of moving beyond cumulative scores and considering specific ACEs patterns to understand their differential impact on mental health. Identifying FA as a distinct pattern with specific consequences for executive function offers valuable insights into developing targeted prevention strategies tailored to specific risk profiles.

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records

BACKGROUND

Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogeneous electronic health record (EHR) data. Integrating this data can provide a more comprehensive understanding of depression and anxiety in T2DM patients, leading to more personalized treatment strategies.

OBJECTIVE

This study aims to develop and validate a deep learning model, the Regional EHR for Depression and Anxiety Prediction Model (REDAPM), using regional EHR data to predict depression and anxiety in patients with T2DM.

METHODS

A case-control development and validation study was conducted using regional EHR data from the Nanjing Health Information Center (NHIC). Two retrospective, matched (1:3) datasets were constructed from the full cohort for the model's internal and external validation. These two datasets were selected from the NHIC data of 2020 and 2022, respectively. The REDAPM incorporates both structured and unstructured EHR data, capturing the temporal dependency of clinical events. The performance of REDAPM was compared to a set of baseline models, evaluated using the area under the receiver operating characteristic curve (ROC-AUC) and the area under the precision-recall curve (PR-AUC). Subgroup, ablation, and interpretation analyses were conducted to identify relevant clinical features available from EHRs.

RESULTS

The internal and external validation datasets comprised 24,724 and 34,340 patients, respectively. The REDAPM outperformed baseline models in both datasets, achieving ROC-AUC scores of 0.9029±0.008 and 0.7360±0.005, and PR-AUC scores of 0.8124±0.011 and 0.5504±0.009. Ablation and subgroup experiments confirmed the significant contribution of patients' medical history text to the model's performance. Integrated gradient score analysis identified the predictive importance of other mental disorders.

CONCLUSION

The REDAPM effectively leverages the heterogeneous characteristics of regional EHR data, demonstrating strong predictive performance for depression onset in diabetic patients. It also shows potential for discovering significant clinical features, indicating considerable promise for clinical utility.

Are endurance runners at higher risk of depression? Screening for depression and risk factors

Depression is an important public health issue. In the general adult population, about 6.7% are affected. Little data are available about endurance runners. We conducted a prospective survey study screening for depression using the Patient Health Questionnaire and investigating potential associated risk factors in endurance runners (≥ 21.1-42.2 km) and ultraendurance runners (≥ 42.2 km). Statistical analysis included descriptive statistics, predictive techniques, and regression analysis. A total of n = 601 runners participated (female n=222 and male n=379; mean age [SD]: 42.8 years [± 10.1]). Overall, 11.3% screened positive for major depression, particularly female runners compared to male runners (p=0.002) and endurance runners compared to ultraendurance runners (p=0.023). No significant differences were observed among performance levels (elite vs. nonelite). Mild depression was observed in 21.6% of runners. Factors associated with a higher risk for screening for major depression included age (p<0.001), particularly runners under the age of 28 years, previous self-reported history of depression (p<0.001), more frequent weekly workouts (4-5/wk; p=0.021), weeks lost to injury (p=0.022), and female sex (p=0.025). A third of endurance and ultraendurance runners screened positive for depression, highlighting the importance of creating awareness for mental health issues and potential screening for athletes and providing access to appropriate support services and education.

The association between constipation and anxiety: a cross-sectional study and Mendelian randomization analysis

Objective

The relationship between constipation and anxiety remains underexplored. This study investigates the association between constipation and anxiety in a representative sample of adults in the United States.

Methods

A cross-sectional analysis was conducted using data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2010, including 9,126 adults aged ≥20 years. Constipation and anxiety were assessed using standardized survey instruments. Multivariable logistic regression models were employed to calculate adjusted odds ratios (ORs), and subgroup and sensitivity analyses were performed to validate the findings. Additionally, Mendelian randomization (MR) was employed to assess the potential causal relationship between constipation and anxiety using genetic data from large GWAS datasets.

Results

Of the 9,126 participants, 324 reported constipation (prevalence: 3.6%), and 2,424 reported anxiety (prevalence: 26.6%). Anxiety prevalence was significantly higher in individuals with constipation compared to those without (41.4% vs. 26.0%; P < 0.001). After adjusting for demographic, socioeconomic, lifestyle, and comorbid factors, constipation remained independently associated with anxiety (adjusted OR: 1.33, 95% CI: 1.02-1.73; P = 0.038). Subgroup analyses revealed no significant interactions. Sensitivity analyses, including multiple imputations, weighted analysis, and propensity score matching, corroborated the robustness of the results. MR analysis, however, revealed no significant causal association between constipation and anxiety.

Conclusion

This study identifies a significant association between constipation and anxiety in a large, nationally representative cohort. While the association remains robust after adjusting for various factors, MR did not provide evidence for a causal relationship. Clinicians should consider evaluating and addressing anxiety symptoms as part of a comprehensive management strategy for patients presenting with constipation.

Identifying and treating pectoralis minor syndrome in women with breast hypertrophy, poor posture and diffuse shoulder symptoms

Pectoralis minor syndrome (PMS) has been identified as a cause of chronic shoulder pain, involving compression of the brachial plexus at the thoracic outlet associated with scapulothoracic abnormal motion (STAM). This condition is poorly recognised and frequently overlooked in clinical practice.We present three patients with breast hypertrophy who experienced shoulder girdle pain and intermittent paraesthesia. Ultrasound-guided pectoralis minor (PM) muscle blocks provided effective but transient relief. Definitive treatment with arthroscopic PM release (APMR) resulted in durable symptom resolution.PMS is often overlooked due to its diffuse symptoms. Although women have been reported to suffer from PMS more frequently, this is the first report to describe the association between female gender, breast hypertrophy, postural overload and PMS, as well as the outcomes in these patients after APMR. Based on the current literature and our clinical experience, we propose an assessment and treatment algorithm for this challenging syndrome.

Cardiometabolic index and major depressive disorder: Stroke and diabetes as mediators

BACKGROUND

Major depressive disorder (MDD) is a severe affective disorder that is clearly linked to stroke and diabetes. This study aimed to investigate the mediating role of stroke and diabetes in the association between the cardiometabolic index (CMI) and MDD.

METHODS

This cross-sectional study analyzed data from 8312 participants in the National Health and Nutrition Examination Survey (NHANES, 2005-2018). MDD was diagnosed using the Patient Health Questionnaire-9 (PHQ-9; score > 10). Associations were evaluated using multivariate logistic/linear regression, stratified interaction analyses, restricted cubic spline (RCS) models for nonlinearity, and bootstrap mediation testing.

RESULTS

There was a robust positive correlation between the incidence of MDD [OR = 1.36 (95 % CI: 1.21-1.51)] and the PHQ-9 score [β = 0.55 (95 % CI: 0.37-0.73)], with a one-unit increase in CMI. The participants in CMIQ4 had a 64 % greater risk of stroke than did the participants in CMIQ1 [OR = 1.64 (95 % CI: 1.17-2.29)]. The forest plot shows that the results remained stable under the grouping of stroke, diabetes, race, gender, and age. Moreover, stroke and diabetes both exhibited partial mediating roles, with indirect effects accounting for 4.03 % and 5.37 % of the total effect, respectively. Through RCS analysis, a nonlinear correlation was observed between CMI and MDD and between CMI and diabetes. There is a linear relationship between stroke and MDD, and maintaining CMI levels below 0.518 may mitigate the risk of MDD.

CONCLUSION

Stroke and diabetes partially mediated the associations between CMI and MDD. However, additional prospective studies are warranted to scrutinize the impact of CMI on MDD.

Depression and anxiety in patients with atopic dermatitis: Recognizing and addressing mental health burden

The psychosocial burden of atopic dermatitis (AD) is extensive, stemming from intense itch, sleep disturbance, unpredictable flares, lifestyle restrictions and missed activities, social stigma, and treatment burden. Overall, adults with AD are at a 2- to 3-fold greater risk for depression and anxiety compared with individuals without AD and children at a 1.5-fold greater risk, with greatest risk for those with more severe disease. A number of mechanisms seem to affect the relationship between AD and mental health, including poorly controlled disease, sleep disturbance, stress-induced itch, inflammation, and coping patterns. In some cases, the mental health burden of AD may also negatively affect AD management and course, creating a reinforcing cycle of psychosocial burden. Although depression and anxiety are known comorbidities of AD, the mental health burden of AD often goes unaddressed, which may further a sense of isolation for patients and families. Given the strong association between symptom severity and increased mental health burden, optimizing AD treatment and reducing itch are critical. Health care professionals can support patients with AD and their caregivers by encouraging open conversations about mental health, addressing common areas of condition-related stress, screening for depression and anxiety, and facilitating referrals to mental health professionals for further assessment and evidence-based care. Existing research supports use of cognitive-behavioral interventions to help manage the physical and mental health burden of AD. Further research is needed to evaluate psychological interventions for pediatric patients with AD and for patients with clinical diagnoses of depression and anxiety to better guide shared decision-making around support for these patients.

Measurement properties of the Polish version of the Cystic Fibrosis Questionnaire Revised 14+ in the adult population

Measuring the quality of life in patients with cystic fibrosis is an important element of the patient care process. Many tools have been created for this measurement among adults. One of them is the Cystic Fibrosis Questionnaire-Revised 14+ (CFQ-R 14+). Its measurement properties have not been comprehensively assessed in the population of Polish adults. The aim of the study is to verify the construct validity, including structural and criterion validity, as well as internal consistency, of the Polish version of the CFQ-R 14+ in the population of adults with cystic fibrosis. We conducted a cross-sectional survey among adults with cystic fibrosis. After preparing the database, we performed a confirmatory factor analysis (CFA) followed by exploratory factor analysis (EFA) using the parallel analysis method principal axis factoring with Oblimin rotation. Intercorrelations of questionnaire factors and the occurrence of relationships among items for the general scale results was checked. We also presented basic descriptive statistics (mean, median, standard deviation, skewness, kurtosis, minimum and maximum values). The analyses included responses from 220 adult patients. CFA results did not show adequate goodness of fit (χ2(1025) = 2112.35, p < 0.001; CFI = 0.831; TLI = 0.814; RMSEA = 0.069; SRMR = 0.074). After EFA, 6 factors were extracted, considering 40 out of 50 questions of the CFQ-R 14+. CFQ-R 14+ may be useful in assessing the quality of life of Polish adult patients with cystic fibrosis. Our analysis demonstrates that the optimal factor structure of the tool in this population includes 6 scales.

Use of patient-reported outcome measures (PROMs) in primary care-based mental health programming: an environmental scan of Alberta, Canada

Background

Many Primary Care Networks (PCNs) in Alberta collect Patient Reported Outcome Measures (PROMs) to support patient-centered care. However, there is limited knowledge on what tools are currently being administered across PCNs and how the data is used. For this study, we focused on PROMs for mental health programming (MHP). Our objectives are to identify what PROMs are currently being administered in PCNs and what domains they measure for MHP; understand PCNs’ capacity to implement and use PROMs data effectively for their PCN MHP; describe how PROMs are currently being reported in PCNs for MHP; and understand the feasibility of having standardized and consistent measurement of PROMs in general across PCNs.

Methods

This environmental scan employs a survey for PCN evaluators (those responsible for managing PROMs data for their PCN), tailored to examine PROMs in PCN MHP across all populations. Evaluators from all 39 Alberta PCNs were invited to complete the survey on behalf of their PCN. It included closed and open-ended questions. Survey results were aggregated and reported by objective.

Results

Evaluators from 20 PCNs (51%) completed the survey, with a mix of rural/urban and across all five health zones. Nine out of 20 reported 11 tools currently being collected and seven out of nine reported using more than one tool for MHP. The most used tools were the EQ-5D-5 L (7/9) and PHQ-9 (6/9). Seven respondents indicated the EQ-5D-5Lwas useful or sometimes useful; five reported the PHQ-9 was useful or sometimes useful. While the use of each PROM varied, most PROMs are used for clinical care decisions and internal reporting. Most respondents indicated standardizing PROMs across PCNs would be challenging, however having alignment of PROMs and sharing best practices for PCNs would be beneficial.

Conclusions

These results provide a better understanding of the current use of PROMs in PCNs, specific to MHP, which will be further examined through future narrative conversations. Overall, this study informs primary care leadership on the current use of PROMs and supports the advancement of PROMs use in Alberta.

Effects of Tai Chi Versus General Aerobic Exercise on Depressive Symptoms and Serum Lipid Levels Among Older Persons With Depressive Symptoms: A Randomized Controlled Study

Tai Chi, a mindfulness-based aerobic exercise, may alleviate depressive symptoms and improve physiological markers in older adults. However, its distinct effects compared with general aerobic exercise remain unclear. To compare the effects of Tai Chi and general aerobic exercise on depressive symptoms and serum lipid levels in community-dwelling older adults with mild to moderate depression, a randomized controlled trial was conducted. Participants were randomly assigned to Tai Chi (n = 120) or general aerobic exercise (n = 120) for 3 months. Depressive symptoms and serum lipid levels were measured at baseline and postintervention. A generalized estimating equation was used to assess group differences over time. The Tai Chi group exhibited significantly greater reductions in depressive symptoms and improvements in serum lipid profiles compared with the general aerobic exercise group. Tai Chi's mind-body synergy may enhance its antidepressant effects, offering a promising approach to mental health and healthy aging.

Using network analysis to identify central symptoms of depression and anxiety in different profiles of infertility patients

BACKGROUND

Depression and anxiety were not only common but also with serious consequence in infertility patients. The current study endeavors to define distinct depression and anxiety profiles of infertility patients and identify central symptoms within different profiles to facilitate targeted interventions.

METHOD

The research employed K-means Clustering to delineate the depression and anxiety profiles, followed by a repetition of the analysis using Latent Class Analysis (LCA). Furthermore, network analysis was utilized to identify central symptoms within the various profiles.

RESULT

K‑means Clustering identified Cluster 1 (16.15%), Cluster 2 (37.08%) and Cluster 3 (46.77%), while LCA yielded the low-risk group (47.23%), the mild-risk group (34.46%) and the high-risk group (18.31%). A majority of patients in the three clusters were predominantly in a single LCA-derived patient class (88.38-100%). Network analysis revealed that connections within each symptom in PHQ-9 and GAD-7 were stronger than those between symptoms. Furthermore, PHQ 2 ("sad mood"), GAD 1 ("nervousness") and GAD 2 ("uncontrollable worry") were identified as the central symptoms in Cluster 1 GAD 3 ("excessive worry"), GAD 2 ("uncontrollable worry") and GAD 5 ("restlessness") emerged as the central symptoms in Cluster 2) Additionally, PHQ 4 ("fatigue"), GAD 6 ("irritability") and GAD 3 ("excessive worry") were identified as the central symptoms in Cluster 3.

CONCLUSIONS

We defined three distinct depression and anxiety profiles among infertility patients and pinpointed central symptoms within each profile. These findings underscore the importance of directing research towards those central symptoms within each profile in order to develop targeted intervention strategies.

The impact of extended reality cognitive behavioral therapy on mental disorders among children and youth: A systematic review and meta-analysis protocol

BACKGROUND

The prevalence of mental disorders among children and youth has significantly increased, with rising rates of anxiety, depression, and other psychological disorders globally. Despite the widespread adoption of cognitive behavioral therapy (CBT) as a standardized treatment for various mental disorders, its efficacy can be constrained due to limited patient engagement, lack of commitment, and stigma, all challenges pronounced among children and youth. In this context, extended reality (XR) technologies (including virtual, augmented, and mixed reality) have emerged as innovative therapeutic tools offering immersive and engaging environments to overcome the limitations of traditional CBT.

OBJECTIVES

This protocol aims to outline the methodology for conducting a systematic review and meta-analysis to evaluate the impact of XR-CBT on symptoms of mental disorders among children and youth.

METHODS

This systematic review and meta-analysis will follow PRISMA-P 2015 guidelines. A comprehensive search will be conducted in PsycINFO, PubMed, EMBASE, Scopus, and Web of Science to identify relevant studies published between January 2014 and June 2024. Eligible studies must involve children and youth (ages 24 years or younger) diagnosed with a mental disorder (e.g., anxiety, depression, ADHD, PTSD) and compare XR-CBT interventions (virtual, augmented, or mixed reality) with traditional therapy or control groups (e.g., no treatment). The primary outcome will be the change in symptoms of mental disorders, measured using standardized instruments (e.g., PHQ-9, GAD-7, PSS). Data will be extracted on post-intervention means, standard deviations, and 95% confidence intervals. Effect sizes, calculated using Hedges' g, will be pooled with a random-effects model. Moreover, an a priori meta-regression within a random-effects framework will be conducted to examine how study-level characteristics influence effect sizes and address heterogeneity across studies. Heterogeneity will be assessed using the I2 statistic and the Cochran's Q test. Risk of bias in individual studies will be evaluated using the Cochrane risk-of-bias tool.

CONCLUSIONS

This protocol establishes a structured approach for assessing the efficacy of XR-CBT interventions on mental disorders among children and youth. The results of the systematic review and meta-analysis will fill a gap in current research and inform future therapeutic applications for mental health interventions among children and youth.

Understanding the complex network of anxiety, depression, sleep problems, and smartphone addiction among college art students using network analysis

Background

This study employs a network analysis approach to explore the interconnections between anxiety, depression, and sleep problems and smartphone addiction among college students using network analysis, offering a new perspective on these prevalent mental health issues.

Methods

A cross-sectional study was conducted among art students at a public university in the province of Fujian, China. Data were collected using the Generalized Anxiety Disorder Scale-7, Patient Health Questionnaire-9, Pittsburgh Sleep Quality Index, and Mobile Phone Addiction Index. The R package was used in the analysis for statistical analysis, and information was collected using multi-stage sampling as well as stratified sampling. Network analysis was utilized to identify bivariate associations between symptoms, core components, co-occurring patterns, and key nodes within the network. Network stability and accuracy were assessed using the bootstrap method, and network comparisons were conducted across subgroups based on gender, residential condition, and sibling status.

Results

The study included 2,057 participants. The network analysis revealed uncontrollable worry as the most central symptom, with low energy and excessive worry also identified as key symptoms within the network. Bridge symptoms such as daytime dysfunction, self-harm or suicidal ideation, abnormal behavior and speech, and sensory fear were found to be critical in linking anxiety, depression, and sleep problems. The network of comorbid symptoms and smartphone addiction highlighted inefficiency and loss of control as central factors influencing mental health. No significant differences in network characteristics were found across the subgroups, suggesting the universality of the identified network structure.

Conclusion

This study delineates the intricate network of anxiety, depression, sleep problems, and smartphone addiction among college students, identifying key symptomatic intersections and their implications for mental health.

Risk of Attempted and Completed Suicide in Persons Diagnosed With Headache

Importance

Although past research suggests an association between migraine and attempted suicide, there is limited research regarding risk of attempted and completed suicide across headache disorders.

Objective

To examine the risk of attempted and completed suicide associated with diagnosis of migraine, tension-type headache, posttraumatic headache, and trigeminal autonomic cephalalgia (TAC).

Design, Setting, and Participants

This was a population-based cohort study of Danish citizens from 1995 to 2020. The setting was in Denmark, with a population of 5.6 million people. Persons 15 years and older who were diagnosed with headache were matched by sex and birth year to persons without headache diagnosis with a ratio of 5:1. Data analysis was conducted from May 2023 to May 2024.

Exposures

First-time headache diagnoses identified from inpatient hospitalizations, emergency department visits, and outpatient specialty clinic visits using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes.

Main Outcomes and Measures

Diagnostic codes from the ICD-10 were used to identify attempted suicide from the Danish National Patient Registry and the Danish Psychiatric Central Research Register and completed suicides from the Danish Register of Causes of Death. Absolute risks (ARs) and risk differences (RDs) for attempted and completed suicide were calculated using the cumulative incidence function. Hazard ratios (HRs) for attempted and completed suicide associated with headache diagnosis were computed adjusting for age, sex, year, education, income, baseline comorbidities, and accounting for competing risk of death.

Results

In total, 119 486 persons (83 046 female [69.5%]) diagnosed with headache were identified and matched with 597 430 persons (415 230 female [69.5%]) drawn from the general population. Participants' median (IQR) age was 40.1 (29.1-51.6) years. The 15-year AR of attempted suicide among persons diagnosed with headache was 0.78% (95% CI, 0.72%-0.85%) vs 0.33% (95% CI, 0.31%-0.35%) in the comparison cohort (RD, 0.45%; 95% CI, 0.39%-0.53%). The 15-year AR of completed suicide among persons diagnosed with headache was 0.21% (95% CI, 0.17%-0.24%) vs 0.15% (95% CI, 0.13%-0.16%) in the comparison cohort (RD, 0.06%; 95% CI, 0.02%-0.10%). The hazards of attempted suicide (HR, 2.04; 95% CI, 1.84-2.27) and completed suicide (HR, 1.40; 95% CI, 1.17-1.68) were elevated among persons with headache vs comparison cohort members. Findings were consistent across headache types, with stronger associations for TACs and posttraumatic headache.

Conclusions and Relevance

Results of this cohort study revealing the robust and persistent association of headache diagnoses with attempted and completed suicide suggest that behavioral health evaluation and treatment may be important for these patients.

Screening for Depression in Caregivers of Children with Developmental Disabilities: A Quality Improvement Initiative

INTRODUCTION

Screening for depression in caregivers of children with developmental disabilities is not routine, representing missed opportunities for support.

METHOD

A quality improvement project was initiated in our pediatric clinic. Root causes of limited screening included unclear guidelines for support, caregiver perception that help is unavailable, and lack of a quick screening tool. A clinical pathway was constructed and integrated into existing practice using quality improvement methodology.

RESULTS

Baseline screening rate was 5%-10%. During the 12-week pilot, weekly rates ranged from 46.0% to 91.0% (mean 70.2%). Monthly rates subsequently averaged 55.0%. Approximately 20% had a positive screen; over half were caregivers of children with autism. About 5% had moderate depression, of whom 40% required referral to social workers.

DISCUSSION

Structured depression screening of caregivers of children with developmental disabilities is feasible and sustainable in a busy clinic. Further research is needed to measure the impact on child and family outcomes.

Increased Odds of Cognitive Impairment in Adults with Depressive Symptoms and Antidepressant Use

INTRODUCTION

The relationship between antidepressant use and class with cognition in depression is unclear. This study aimed to evaluate the association of cognition with depressive symptoms and antidepressant use (class, duration, number).

METHODS

Data from the National Health and Nutrition Examination Survey were examined for cognitive function through various tests and memory issues through the Medical Conditions questionnaire. Depressive symptoms were assessed using the Patient Health Questionnaire-9.

RESULTS

A total of 2867 participants were included. Participants with depressive symptoms had significantly higher odds of cognitive impairment (CI) on the animal fluency test (aOR=1.89, 95% CI=1.30, 2.73, P=0.002) and Digit Symbol Substitution test (aOR=2.58, 95% CI=1.34, 4.9, P=0.007), as well as subjective memory issues (aOR=7.25, 95% CI=4.26, 12.32, P<0.001) than those without depression. There were no statistically significant associations between any of the CI categories and depressive symptoms treated with an antidepressant and antidepressant use duration. Participants who were using more than one antidepressant had significantly higher odds of subjective memory issues than those who were using one antidepressant. Specifically, users of atypical antidepressants, selective serotonin reuptake inhibitors, or tricyclic antidepressants (TCAs) had significantly higher odds of subjective memory issues in comparison to no antidepressants, with TCAs showing the largest odds (aOR=4.21, 95% CI=1.19, 14.86, P=0.028).

DISCUSSION

This study highlights the relationship between depressive symptoms, antidepressant use, and CI. Future studies should further evaluate the mechanism underlying this phenomenon.

Impact of Early Depressive Burden on Patient-Reported Outcomes Following Minimally Invasive Transforaminal Lumbar Interbody Fusion

STUDY DESIGN

Retrospective review.

OBJECTIVE

To evaluate mental health influence on minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) patients.

SUMMARY OF BACKGROUND DATA

Poor mental health has been postulated to indicate inferior patient perceptions of surgical outcomes in spine literature. Few studies have assessed mental health as a dynamic metric throughout the perioperative period.

METHODS

A single-surgeon database was retrospectively searched for patients who underwent primary, elective MIS-TLIF for degenerative or isthmic spondylolisthesis. Summative depressive burden (SDB) was defined by the sum of preoperative and 6-week postoperative 9-item Patient Health Questionnaire (PHQ-9), with Lesser Burden (LB, SDB<10) and Greater Burden (GB, SDB≥10) cohorts. Patient-reported outcomes measures (PROMs) were compared preoperatively, at 6 weeks, and at final postoperative follow-up (11.4±10.9 mo), using Patient-Reported Outcomes Measurement Information System-Physical Function (PROMIS-PF), Oswestry disability index (ODI), visual analog scale-back (VAS-B), VAS-leg (VAS-L), and PHQ-9. Improvements at 6-week (∆PROM-6W), final follow-up (∆PROM-FF), and minimum clinically important difference (MCID) achievement were compared.

RESULTS

The GB cohort consisted of 44 of 105 patients. Demographic variations included older age, higher Charlson comorbidity index, increased hypertension prevalence, and private insurance in the LB cohort ( P ≤0.018). The LB cohort demonstrated better baseline and 6-week PROMIS-PF/ODI/VAS-L ( P ≤0.032) and better final PROMIS-PF/ODI/VAS-L/PHQ-9 ( P ≤0.031). Both cohorts improved in all PROMs at 6 weeks and final follow-up ( P ≤0.029), except for PROMIS-PF at 6 weeks in the GB cohort. ∆PROM-6W, ∆PROM-FF, and MCID achievement rate for PHQ-9 were greater in the GB cohort ( P ≤0.001).

CONCLUSION

On average, patients undergoing MIS-TLIF for degenerative or isthmic spondylolisthesis improved in all PROMs by final follow-up. Patients with GB suffered inferior perceptions of physical function, disability, and leg pain. MCID rates in mental health were higher for GB cohort. Surgeons are encouraged to adopt a compassionate understanding of depressive burden and educate the patient on possible consequential postoperative outcomes.

One-shot intervention reduces online engagement with distorted content

Depression is one of the leading causes of disability worldwide. Individuals with depression often experience unrealistic and overly negative thoughts, i.e. cognitive distortions, that cause maladaptive behaviors and feelings. Now that a majority of the US population uses social media platforms, concerns have been raised that they may serve as a vector for the spread of distorted ideas and thinking amid a global mental health epidemic. Here, we study how individuals ( n = 838 ) interact with distorted content on social media platforms using a simulated environment similar to Twitter (now X). We find that individuals with higher depression symptoms tend to prefer distorted content more than those with fewer symptoms. However, a simple one-shot intervention can teach individuals to recognize and drastically reduce interactions with distorted content across the entire depression scale. This suggests that distorted thinking on social media may disproportionally affect individuals with depression, but simple awareness training can mitigate this effect. Our findings have important implicasstions for understanding the role of social media in propagating distorted thinking and potential paths to reduce the societal cost of mental health disorders.

Central Sensitivity Symptoms and Autistic Traits in Autistic and Non-Autistic Adults

Central sensitivity syndromes (CSSs) are a group of health conditions thought to include an underlying sensitisation of the central nervous system. Evidence suggests autistic adults experience poorer physical health than the general population and are more likely to have a CSS. This study examined CSS diagnoses and symptoms in autistic and non-autistic adults, to determine whether CSS symptoms were related to autistic traits, mental health, sensory sensitivity, age or gender. Participants included 534 adults with clinical diagnoses of autism, CSS, both diagnoses or neither (i.e., comparison group), who were recruited through social media, support groups and institutional affiliations. Participants completed online self-report validated questionnaires, including the Autism Spectrum Quotient (AQ), Central Sensitization Inventory (CSI), Sensory Perception Quotient (SPQ), and the PHQ-9 and GAD-7. Autistic people without a diagnosed CSS reported significantly more CSS symptoms than the comparison group, with a mean score above the clinical cut-off. Non-autistic participants with a CSS had significantly more autistic traits than the comparison group. Autistic people with a CSS reported the most sensory sensitivity, with autism only and CSS only groups reporting similar levels of sensory sensitivity and all diagnostic groups reporting more sensory sensitivity than the comparison group. Sensory sensitivity, anxiety, autistic traits, age and gender were all significant predictors of CSS symptoms. The overlap in symptoms between autistic individuals and those with CSS suggests diagnostic overshadowing and possible under-diagnosis or misdiagnosis. Furthermore, these symptoms may exacerbate or mask one another. Notwithstanding potential limitations of representativeness and selection bias, increased awareness of the association between autistic traits and CSS symptoms is important for clinicians to improve diagnostic accuracy and treatment.

Effectiveness of mental health chatbots in depression and anxiety for adolescents and young adults: a meta-analysis of randomized controlled trials

BACKGROUND

The mental health chatbot is dedicated to providing assistance to individuals grappling with the complexities of depression and anxiety.

OBJECTIVE

The study aimed to evaluate the effectiveness of the mental health chatbot in alleviating symptoms of depression and anxiety among adolescents and young adults.

METHODS

A systematic review framework was employed with a protocol pre-registered on Prospero (CRD42023418877). Databases were systematically searched, including PubMed, ACM Digital Library, Embase, Cochrane and IEEE. Data synthesis was conducted narratively, and meta-analysis was performed by pooling data from the original studies.

RESULTS

Ten randomized controlled trials focused on an acute population, mainly females and university students. Chatbots designed for daily conversations and mood monitoring, using cognitive behavioral therapy techniques, showed efficacy in treating depression (95% CI = -1.09 to -0.23; p = .003). However, it is essential to highlight that these interventions utilizing chatbots for mental health were not found to be efficacious in managing symptoms of anxiety (95% CI = -0.56 to 0.4; p = .74).

CONCLUSIONS

Evidence supports the effectiveness of mental health chatbots in treating depression, but further exploration and refinement are needed to optimize their efficacy in managing anxiety.

The joint and interactive effects of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and body mass index on the risk of depression, as well as the mediating role of NHHR: results from NHANES 2005-2023

BACKGROUND

Various research in the past has indicated that the NHHR, which represents the ratio of non-high-density lipoprotein cholesterol (non-HDL-C) to high-density lipoprotein cholesterol (HDL-C), and body mass index (BMI) each act independently as contributors to depression risk. Nonetheless, studies exploring the combination of NHHR with BMI in relation to depression are limited. Consequently, the central aim of this study is investigating the joint and interactive effects of NHHR and BMI on depression risk, as well as the mediating role of NHHR.

METHODS

Encompassing participants aged 20 years or over, this research incorporated a total of 39,704 individuals from the National Health and Nutrition Examination Survey (NHANES), which covered the period of 2005 to 2023. To analyze the impact of NHHR and its combination with BMI on depression, our analytical approach included multivariate logistic regression, restricted cubic spline modeling, interaction testing and subgroup analyses. Additionally, we studied the joint effects of NHHR and BMI. Finally, we applied a four-way decomposition analysis method to examine the interactions and mediating effects within the aforementioned relationships.

RESULTS

Among all participants in this study, the prevalence of depressive disorder (Patient Health Questionnaire-9 score ≥ 10) was 9.2%. Both the NHHR and BMI were associated with depression, which remained significant even after full adjustment for covariates [NHHR, OR (95% CI): 1.07 (1.04-1.09); BMI, OR (95% CI): 1.02 (1.02-1.03)]. Compared with the reference group, the OR (95% CI) for the highest groups of NHHR, BMI, and their product term NHHR-BMI were 1.41 (1.24-1.61), 1.35 (1.18-1.54), and 1.59 (1.37-1.84), respectively. Participants with NHHR in the fourth quartile and BMI exceeding 30 kg/m², had higher depression risk compared to other participants with NHHR in the first quartile and BMI below 25 kg/m² [OR (95% CI): 1.64 (1.34-2.00)]. Results of the four-way decomposition analyses indicated that NHHR played a mediating role in the association between BMI and depression, with the mediating effect accounting for 17.6%. Similarly, NHHR also mediated 11.0% of the mediating effect between BMI and PHQ-9 score. However, no interaction between NHHR and BMI related to depression was found in the general population. After stratifying by gender, it was found that the mediated interaction between NHHR and BMI had a statistically significant effect on depression and PHQ-9 score in males.

CONCLUSIONS

Depression risk is linked to both NHHR and BMI, and NHHR has a significant mediating impact on the association between BMI and depression. Notably, there is a non-negligible mediated interaction effect between BMI and NHHR in male participants. Compared to considering NHHR or BMI individually, participants had a higher risk of depression when the combined terms of the two were in the higher quartiles. These findings suggest that the combined assessment of these two indicators may help deepen the understanding and evaluation of depression, enhance the accuracy of risk stratification, and is worthy of further research.

Increased odds of metabolic syndrome among adults with depressive symptoms or antidepressant use

Metabolic syndrome (MetS) is a condition that includes a cluster of risk factors for cardiovascular disease. In this paper, we aimed to evaluate the association between depressive symptoms, antidepressant use, duration of antidepressant use, antidepressant type and MetS. Data from the 2005-2018 National Health and Nutrition Examination Surveys were used in this study. Adults were included if they responded to the depressive symptoms and prescription medications questionnaires and had measures of blood pressure, waist circumference, triglycerides, high-density lipoprotein, and fasting plasma glucose. Participants were categorized by their antidepressant use (yes/no), type, and duration. This study included 14,875 participants (50.45% females), with 3616 (23.45%) meeting the criteria for MetS. Participants with higher depressive symptom scores (aOR = 1.04, 95% CI: 1.02, 1.05, p < 0.001) or those with depressive symptoms (aOR = 1.42, 95% CI: 1.17, 1.73, p = 0.001) had higher odds of MetS. A similar associations was seen among those who were on antidepressants compared to those who were not on antidepressants (aOR = 1.24, 95% CI: 1.03, 1.50, p = 0.025). Duration of antidepressant use was not significantly associated with MetS. Participants on tricyclic antidepressants had greater odds of MetS compared to those not taking any antidepressants (aOR = 2.27, 95% CI: 1.31, 3.93, p = 0.004). Our study provides evidence of the association between depressive symptoms, antidepressant use, and MetS, highlighting the importance of monitoring metabolic and cardiovascular alterations in individuals of depression.

Depression diagnosis: EEG-based cognitive biomarkers and machine learning

Depression is a complex mental illness that has significant effects on people as well as society. The traditional techniques for the diagnosis of depression, along with the potential of nascent biomarkers especially EEG-based biomarkers, are studied. This review explores the significance of cognitive biomarkers, offering a comprehensive understanding of their role in the overall assessment of depression. It also investigates the effects of depression on various brain regions, outlines promising areas for future research, and emphasizes the importance of understanding the neurophysiological roots of depression. Furthermore, it elucidates how machine learning and deep learning models are integrated into EEG-based depression diagnosis, emphasizing their importance in optimizing personalized therapeutic protocols and improving diagnostic accuracy with EEG data analysis.

Fast, smart, and adaptive: using machine learning to optimize mental health assessment and monitor change over time

In mental health, accurate symptom assessment and precise measurement of patient conditions are crucial for clinical decision-making and effective treatment planning. Traditional assessment methods can be burdensome, especially for vulnerable populations, leading to decreased motivation and potentially unreliable results. Computerized Adaptive Testing (CAT) has emerged as a solution, offering efficient and personalized assessments. In particular, Machine Learning-based CAT (MT-based CATs) enables adaptive, rapid, and accurate evaluations that are more easily implementable than traditional methods. This approach bypasses typical item selection processes and the associated computational costs while avoiding the rigid assumptions of traditional CAT approaches. This study investigates the effectiveness of Machine Learning-Model Tree-based CAT (ML-MT-based CAT) in detecting changes in mental health measures collected at four time points (6-month intervals between February 2018 and December 2019). Three CATs measuring generalized anxiety, depression, and social anxiety were developed and tested on a dataset with responses from 564 participants. A cross-validation approach based on real data simulations was used. Results showed that ML-MT-based CATs produced estimates of trait levels comparable to full-length tests while reducing the number of items administered by 50% or more. In addition, ML-MT-based CATs captured changes in trait levels consistent with full-length tests, outperforming short static measures.

Internet gaming disorder and depression mediated by impaired resilience and sleep distress: a three-wave longitudinal study among Chinese adolescents

AIMS

While the cross-sectional relationship between internet gaming disorder (IGD) and depression is well-established, whether IGD predicts future depression remains debated, and the underlying mechanisms are not fully understood. This large-scale, three-wave longitudinal study aimed to clarify the predictive role of IGD in depression and explore the mediating effects of resilience and sleep distress.

METHODS

A cohort of 41,215 middle school students from Zigong City was assessed at three time points: November 2021 (T1), November 2022 (T2) and November 2023 (T3). IGD, depression, sleep distress and resilience were measured using standardized questionnaires. Multiple logistic regression was used to examine the associations between baseline IGD and both concurrent and subsequent depression. Mediation analyses were conducted with T1 IGD as the predictor, T2 sleep distress and resilience as serial mediators and T3 depression as the outcome. To test the robustness of the findings, a series of sensitivity analyses were performed. Additionally, sex differences in the mediation pathways were explored.

RESULTS

(1) IGD was independently associated with depression at baseline (T1: adjusted odds ratio [AOR] = 4.76, 95% confidence interval [CI]: 3.79-5.98, p < 0.001), 1 year later (T2: AOR = 1.42, 95% CI: 1.16-1.74, p < 0.001) and 2 years later (T3: AOR = 1.24, 95% CI: 1.01-1.53, p = 0.042); (2) A serial multiple mediation effect of sleep distress and resilience was identified in the relationship between IGD and depression. The mediation ratio was 60.7% in the unadjusted model and 33.3% in the fully adjusted model, accounting for baseline depression, sleep distress, resilience and other covariates. The robustness of our findings was supported by various sensitivity analyses; and (3) Sex differences were observed in the mediating roles of sleep distress and resilience, with the mediation ratio being higher in boys compared to girls.

CONCLUSIONS

IGD is a significant predictor of depression in adolescents, with resilience and sleep distress serving as key mediators. Early identification and targeted interventions for IGD may help prevent depression. Intervention strategies should prioritize enhancing resilience and improving sleep quality, particularly among boys at risk.

Residential versus day program treatment for eating disorders: A comparison of post-treatment outcomes and predictors

Both residential and day programs for eating disorders provide options for a step-up from standard outpatient care. However, there have not been any direct comparisons of their effectiveness and limited research on predictors of better outcomes from either setting. This study aimed to compare clinical outcomes and predictors from a transdiagnostic residential and day program for eating disorders. Measures of eating disorder symptoms, body mass index (BMI), anxiety, and depression were completed by 106 participants (n = 82 residential, n = 24 day program) at pre-treatment, after four weeks, and at discharge. Greater improvement from pre- to post-treatment was evident from residential, compared to day program, treatment (all ps ≤ .005, medium effect sizes). After accounting for age, baseline BMI, and treatment duration, lower baseline eating disorder symptoms (β = 0.84, p < .001) and greater early change in eating disorder symptoms (β = -0.88, p < .001) each predicted less severe eating psychopathology at discharge. Longer treatment duration predicted better post-treatment outcomes for the day program, but was less predictive of residential outcomes (β = 0.64, p < .001). Post-treatment outcomes were not predicted by age or baseline BMI, anxiety, or depression. As symptom severity did not differ at baseline, results support residential treatment over day programs for individuals with more severe eating disorder presentations. Future research should examine whether day programs are equally effective as residential treatment at lower baseline symptom severity and compare residential care with more intensive settings such as inpatient services.

Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes

Depression is a common mental health disorder and a leading contributor to mortality and morbidity. Despite several advancements, the current screening methods have limitations in enabling the robust and automated detection of depression, thereby hindering early diagnosis and timely intervention. This study aimed to develop explainable artificial intelligence (AI) models to predict depression using polysomnographic phenotype data, ensuring high predictive performance while providing clear insights into the importance of features influencing the risk of depression. Advanced machine learning algorithms such as random forest, extreme gradient boosting, categorical boosting, and light gradient boosting machines were employed to train and validate the predictive AI models. Phenotype data from subjective health questionnaires, clinical assessments, and demographic factors were analyzed. The explainable AI models identified the important features, and their performance was evaluated using cross-validation. The study population, comprising 114 control participants and 39 individuals with depression, was stratified based on validated depression-scoring methods. The proposed explainable AI models achieved an F1-score of 85%, verifying their high reliability in predicting depression. Key features influencing the risk of depression, such as anxiety disorders, sleep efficiency, and demographic factors, offer actionable insights for clinical practice, highlighting the transparency of these models. This study proposed and developed explainable AI models based on polysomnographic phenotype data for the automated detection of depression and verified that these models help improve mental health diagnostics, enabling timely interventions.

An Analysis of Primary Hyperparathyroidism in Association with Depression or Anxiety

BACKGROUND

Non-classical manifestations such as neuropsychiatric manifestations in primary hyperparathyroidism (PHPT) have long been documented as symptoms of PHPT and are commonly reported by these patients, despite this connection still being a matter of debate, and they (per se) do not represent an indication of parathyroidectomy.

OBJECTIVE

We aimed to overview the most recent findings regarding the link between depression and/or anxiety (D/A) in subjects confirmed with PHPT, including the impact of the surgery in improving their outcome.

METHODS

This was a comprehensive review of English-based original studies published between January 2020 and October 2024.

RESULTS

The studies (n = 16) included a total of 10,325 patients and an additional 152,525 patients with hypercalcemia (out of whom 13,136 had a PHPT diagnosis and 45,081 were at risk of PHPT diagnosis). Out of these subjects with PHPT, 10,068 underwent parathyroidectomy. Female prevalence was between 62.5 and 92%. Most individuals were over 50, with the youngest studied population having a mean age of 52.7 ± 13.8 years, and the oldest had a median of 71. Depression was documented based on ICD-10 codes (n = 3) and patients' records (n = 2), Depression Anxiety Stress Scales (DASS) (n = 2), Beck Depression Inventory (BDI) (n = 3), BDI-II (n = 3), Symptom Check List 90-revised (SCL) (n = 1), Hamilton Depression Rating Scale (HAM-D) (n = 2), HADS (n = 2), Patient Health Questionnaire-9 (n = 1), and European Quality of Life 5 Dimensions 3-Level Version (EuroQOL-5D-3L) (n = 1). Patient records' (n = 1) and ICD-10 codes (n = 2) were also used for anxiety. Most studies used questionnaires to identify anxiety in PHPT: DASS (n = 2), SCL90R (n = 1), Generalized Anxiety Disorder-7 (n = 1), HADS (n = 2), EuroQOL-5D-3L (n = 1), and State-Trait Anxiety Inventory (n = 1). Depression prevalence varied from 20-36.6% to 65.7% (scale-based assessment) and to 10.5% upon ICD-10. A rate of newly onset depression was reported of 10.7% and of 0.2% with concern to the prevalent suicidal ideation (an incidental rate of 0.4% after a median follow-up of 4.2 years). Most studies identified a moderate depression (when assessing its severity), affecting approximately one third of the surgery candidates. The prevalence of anxiety in PHPT varied between 10.4% and 38.6% (n = 8). Discordant results were generated when applying distinct questionnaires for the same population, and this might come as a potential bias. Other confounding factors are generated by the sub-population referred for surgery that typically displays a more severe parathyroid condition or non-endocrine overlapping conditions (e.g., related to the social or familial status).

CONCLUSION

The modern approach of the patient with PHPT should be complex and go beyond the traditional frame. D/A had a high prevalence in the mentioned studies, associated with increased medication use. Yet, the underlying pathogenic mechanisms remain incompletely elucidated. No correlations between D/A and serum calcium levels were confirmed, while PTH had a slight positive correlation with depression. Parathyroid surgery appears to be beneficial for D/A as it improves the scores, prevalence, and severity. Cinacalcet might reduce depression scores, although more evidence is needed. Women are prone to both PHPT and D/A. The optimal method of D/A screening in PHPT remains to be determined, and the current scales need validation and perhaps adjustment for this specific population sub-group, while PHPT management should be refined upon D/A identification.

Sleep dysfunction in stroke survivors impacts caregiver burden and functional recovery-an observational study

PURPOSE

Sleep dysfunction is often reported post-stroke, but its impact on short-term outcomes and caregiver burden remains less studied. Here, we studied the prevalence of sleep dysfunction and its relationship with self-reported depression, caregiver burden, and functional outcome after stroke.

METHODS

Prospective observational study where consecutive patients with acute ischemic stroke were recruited at 3 months follow-up visit from stroke outpatient clinic from January 2022-March 2023. After informed consent, all the recruited patients were administered 5 questionnaires[Epworth Sleepiness Scale, Insomnia Severity Index, and Pittsburgh Sleep Quality Index for sleep, Patient Health Quality 9 for depression, and Zarit's Caregiver Burden Scale]. 20% of patients underwent overnight ambulatory level 3 polysomnography. Clinical and sleep characteristics were correlated with functional outcome and caregiver burden scores at 3 and 6 months follow-up.

RESULTS

Of 100 patients, with a mean age of 62.2 ± 11.2 years, 67% had moderate to severe strokes at admission with mean National Institute of Health Stroke Scale [NIHSS] 8.3 ± 6.24.63% reporting one or more sleep disturbances post-stroke. 20% had hypersomnolence,35% had insomnia and 40% had poor sleep quality at 3 months after stroke.45% reported depression and 22% caregivers reported significant burden. Caregiver burden had a strong correlation with patient-reported hypersomnolence and poor sleep quality. Sleep dysfunction showed a significant association with poor functional outcomes at 6 months after stroke.

CONCLUSION

Sleep dysfunction is present in a significant number of ischemic stroke survivors 3 months after stroke and can contribute to poor functional outcomes and caregiver stress. The impact of early recognition and timely treatment of sleep dysfunction post-stroke needs to be studied in larger populations.

Prevalence and Burden of Chronic Spontaneous Urticaria in Japan: A Cross-Sectional Study

Background: Real-world data on the prevalence and burden of patients with chronic spontaneous urticaria (CSU) are limited in Japan. This study aimed to estimate CSU prevalence and assess its humanistic and economic burden. Methods: This analysis utilized data from Japanese adult respondents self-reporting physician-diagnosed CSU collected through the 2019 National Health and Wellness Survey. The weighted 12-month prevalence was estimated using 2018 international census projections. Outcomes included the SF-12v2 (physical and mental component summary [PCS and MCS] scores), health utility index (SF-6D and EQ-5D), Dermatology Life Quality Index (DLQI), Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Work Productivity and Activity Impairment scores at data collection, and healthcare resource utilization over the past 6 months. Results: Among 30,006 respondents, 334 reported having CSU, of whom 62.3% were female. The mean (SD) age at data collection and CSU diagnosis was 50.8 (15.3) and 39.2 (14.9) years, respectively. The weighted prevalence of CSU was 1.1%. The mean (SD) PCS and MCS scores were 50.3 (7.0) and 45.1 (10.0), respectively. The mean (SD) health utility measures (SF-6D and EQ-5D) were 0.71 (0.13) and 0.79 (0.18), respectively. The mean (SD) DLQI score was 3.8 (6.0). More than 40% of patients reported mild/moderate/severe anxiety and depression. The mean % (SD) scores for absenteeism, presenteeism, overall work impairment, and activity impairment were 7.6 (17.6), 27.2 (27.2), 30.3 (29.6), and 28.5 (27.8), respectively. Approximately 90.0% of patients visited healthcare providers, including emergency room visits (6.9%) and hospitalizations (9.9%). Conclusions: This study provides insights into the diagnosed prevalence and burden of CSU in Japan, highlighting its impact on patients' lives.

Evaluating the association of depressive symptoms on serum folate and erythrocyte folate levels based on the 2017-2020 NHANES database

Objective

To improve further the management of the nutritional status and dietary habits of depressed patients.

Methods

This study investigated the effect of different severity states of depressive symptoms on serum and erythrocyte folate levels using the Nutrition Examination Survey (NHANES) database from 2017 to 2020. We comprised a sample of 4,872 cases from NHANES database. We developed 3 linear regression models to assess the effect of depressive symptoms on erythrocyte folate and serum folate by collating and analyzing the data. The relationship between depression severity and erythrocyte folate as well as serum folate was also mutually validated by the results of multiple logistic regression. Finally, we made restricted cubic spline plots using the glm function of R.

Results

Depression remained negatively correlated with serum folate levels with a OR value of -0.02, 95% CI of -0.05 ~ -0.00. Moderate depression was negatively correlated with folate, with a OR value of -0.03, 95% CI of -0.05 ~ -0.00. When exploring the association between different degrees of depressive symptoms and erythrocyte folate, it was unexpectedly found that major depression was negatively associated with erythrocyte folate with a OR value of -0.18, 95% CI of -0.31 ~ -0.04 after adjusting for all covariates.

Conclusion

Depression is associated with folate levels. The risk of serum folate insufficiency or erythrocyte folate insufficiency is higher after a positive depression. For different degrees of depressive symptoms, serum folate levels were significantly lower than normal in patients with moderate depression, while erythrocyte folate levels were lower than normal in patients with major depression. Therefore, attention should be paid to the dietary habits and nutritional status of patients with depression or depressive symptoms when they are undergoing long-term antidepressant treatment. Folic acid supplementation is recommended for patients with moderate or severe depression or for depressed patients who have developed unhealthy eating habits.

The Impact of Depression on Bedtime Procrastination in High School Students in Pandemic era: The Mediating Roles of Conscientiousness and Emotional Stability

BACKGROUND

Bedtime procrastination is a common sleep problem that adolescents encounter. This study aimed to investigate the association between bedtime procrastination and depression in Korean high schoolers, while accounting for possible mediators including viral anxiety, resilience, and personality traits.

METHOD

A total of 300 high school students participated in the study. An online survey was conducted from October 18 to 24, 2021. The survey included the Bedtime Procrastination Scale, Patient Health Questionnaire-9 items, Stress and Anxiety to Viral Epidemics-6 items, Connor Davidson Resilience Scale 2-items, and Ten-Item Personality Inventory.

RESULTS

Bedtime procrastination was positively associated with depression (r = 0.31, p < 0.001) and negatively associated with resilience (r = -0.14, p = 0.020), extraversion (r = -0.14, p = 0.015), conscientiousness (r = -0.33, p < 0.001), and emotional stability (r = -0.30, p < 0.001). Linear regression revealed that higher levels of bedtime procrastination were significantly associated with increased depression (β = 0.21, p < 0.001) and personality traits such as lower conscientiousness (β = -0.22, p < 0.001) and lower emotional stability (β = -0.14, p = 0.022). Mediation analysis showed that depression had a direct effect on bedtime procrastination, and depression had an indirect effect on bedtime procrastination that was partially mediated by conscientiousness or emotional stability.

CONCLUSION

In Korean high school students, more bedtime procrastination shows a significant association with higher levels of depression, which is in part mediated by personality traits.

Depressive symptomatology in Brazil: perspectives of statistical and psychometrics analyses of the PHQ-9 at four time-points (2020-2023) in the COVID-19 pandemic

The present research assessed the psychometric properties of the Patient Health Questionnaire-9 (PHQ-9) through an examination of its internal structure, invariance analysis, and standardization. Social distribution analyses of the measure were conducted using linear and binomial logistic regression. The sample consisted of 10,069 adults from all 27 states in Brazil. The data were obtained through four collections across different years of the COVID-19 pandemic (2020, 2021, 2022, and 2023), using independent samples. Confirmatory Factor Analysis (CFA) indicated that the measure is unidimensional with satisfactory fit indices. The model was invariant in relation to the variables investigated at four different levels (configural, metric, scalar, and strict). The standardization supported hypothetical cut scores indicating the severity of depressive symptoms, categorized as very low (0 to 6), low (7 to 13), moderate (14 to 19), high (20 to 23), and very high (≥ 24). We found that sex/gender, skin color/ethnicity, age, education level, and year of the pandemic were predictors of depressive symptoms in the adjusted linear regression analysis. The logistic regression showed variables with higher chances for a positive screening diagnosis of depression, with adjusted Odds Ratio as follows: years 2021 (ORadj = 1.275) and 2023 (ORadj = 1.409), women (ORadj = 1.900), Pardos individuals (ORadj = 1.252), education up to high school (ORadj = 1.272), being a northeast region resident (ORadj = 2.127), and younger people (ORadj = 1.716). The findings of this study indicate the suitability of the PHQ-9 for assessing depression in the population and recommend its use for monitoring depressive symptoms in the coming years in Brazil. Clinical implications include developing interventions to address the psychological impact of this and any future health crises.

Association of disease activity with depression and anxiety in systemic lupus erythematosus: a comparison of SLEDAI-2K and SLE-DAS

OBJECTIVE

To explore the association of disease activity, as evaluated by both the Systemic Lupus Erythematosus Disease Activity Score (SLE-DAS) and the SLEDAI-2000 (SLEDAI-2K), with depression and anxiety in patients with SLE.

METHODS

A cross-sectional study was conducted among 85 Chinese patients with SLE. Disease activity was measured using SLEDAI-2K and SLE-DAS scoring systems. Depression and anxiety were assessed using Patient Health Questionnaire-9 and Generalized Anxiety Disorder Scale-7, respectively. Multivariate logistic regression analysis was performed to evaluate the association of disease activity scores, as well as specific clinical and laboratory items, with depression and anxiety.

RESULTS

There was a robust correlation between SLEDAI-2K and SLE-DAS scores in overall patient population (Spearman's r = 0.764, 95% CI 0.655-0.842; P < 0.001) and in those with moderate-to-high disease activity (Spearman's r = 0.792, 95% CI 0.616-0.892; P < 0.0001). However, the correlation weakened for patients with mild disease activity or remission (Spearman's r = 0.450, 95%CI 0.188-0.652; P = 0.001). Multivariate logistic regression analysis did not show a significant correlation between SLEDAI-2K and SLE-DAS scores and depression/anxiety. The presence of mucosal ulcer/serositis significantly increased the risk of depression (odds ratio = 4.472, 95% CI 1.035-19.328; P = 0.045) and anxiety (odds ratio = 3.978, 95% CI 1.051-15.049; P = 0.042).

CONCLUSION

The SLE-DAS scoring system demonstrated a comparable ability to assess disease activity in SLE compared with SLEDAI-2K. Though neither scoring system showed significant associations with depression and anxiety, the presence of mucosal ulcer/serositis markedly heightened the risk of both among SLE patients.

Internal Structure of the Patient Health Questionnaire-9: A Systematic Review and Meta-analysis

PURPOSE

This review aimed to evaluate the internal structure (structural validity, internal consistency, and measurement invariance) of the Patient Health Questionnaire-9 (PHQ-9), which is one of the most widely used self-administered instruments for assessing and screening depression.

METHODS

The updated COnsensus-based Standards for the selection of health Measurement Instruments methodology for a systematic review of self-reported instruments was used. PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library databases were searched from their inception up to February 28, 2023.

RESULTS

This study reviewed 98 psychometric studies reported on in 90 reports conducted in 40 countries. Various versions of the PHQ-9 were identified: one-factor structures (8 types), two-factor structures (10 types), bifactor structures (4 types), three-factor structure (1 type), and second-order three-factor structure (1 type). There was sufficient high-quality evidence for structural validity of the one-factor structure with nine items scored using a four-point Likert scale based on confirmatory factor analysis, for internal consistency with a quantitatively pooled Cronbach α of .85, and for measurement invariance across sex, age, education level, marital status, and income groups. There was sufficient high-quality evidence for structural validity, internal consistency (Cronbach's α = .76- .92, ω = 0.83- .92), and measurement invariance across sex for the PHQ-8 (which excluded item 9: "suicidality or self-harm thoughts").

CONCLUSION

The one-factor PHQ-9 and PHQ-8 (excluding item 9) scored using a four-point Likert scale have the best internal structure based on the current evidence. The one-factor PHQ-9 and PHQ-8 justify the use of aggregated total scores in both practice and research. The total score of the PHQ-9 using a four-point Likert scale can be used to compare depression levels across sex, age, education level, marital status, and income groups due to the availability of sufficient evidence for measurement invariance across these demographic groups.

Effectiveness of a task-sharing collaborative care model for the detection and management of depression among adults receiving antiretroviral therapy in primary care facilities in South Africa: A pragmatic cluster randomised controlled trial

BACKGROUND

HIV is characterised by high rates of comorbidity with mental health conditions including depression, as such, the detection and treatment of comorbid depression is critical to achieve viral load suppression. This study evaluated the effectiveness of a collaborative care intervention for depression among adults with comorbid depression symptoms receiving ART in primary health care (PHC) facilities.

METHODS

We conducted a pragmatic cluster-randomised trial in 40 clinics in the North West province of South Africa. PHC clinics were stratified by sub-district and randomised in a 1:1 ratio. Participants were ≥ 18 years, receiving ART, and had depression symptoms indicated by Patient Health Questionnaire-9 (PHQ-9) score ≥ 9. Intervention clinics received: i) supplementary mental health training and clinical communication skills for PHC nurses; ii) workshops for PHC doctors on treating depression; and iii) lay counselling services. Using mixed effects regression models, we assessed co-primary outcomes of PHQ-9 response at 6 months (≥50 % reduction in baseline PHQ-9 score) and viral load suppression at 12 months (viral load<1000 copies/mL).

RESULTS

The intervention had no effect in PHQ-9 response (49 % vs 57 %, risk difference (RD) = -0.08, 95 % CI = -0.19; 0.03, p = 0.184) or viral load suppression (85 % vs 84 %, RD = 0.02, 95 % CI = -0.01; 0.04, p = 0.125). Nurses referred 4298 clinic patients to counsellors, however, only 66/1008 (7 %) of intervention arm participants were referred to counsellors at any point during the study.

LIMITATIONS

The highly pragmatic approach of this trial limited exposure to the counselling component of the intervention and referral to doctors for initiation of antidepressant treatment was extremely low.

CONCLUSION

The trial showed no effect of a district-based intervention to strengthen collaborative care for depression. The trial revealed the extent of the treatment gap in the context of scaling up mental health services.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT02407691); Pan African Clinical Trials Registry (201504001078347).

Prevalence and Correlates of Depressive Symptoms and Cognitive Impairment in Elderly People over 65 Years Old in the Community and Nursing Homes

Objective

Cognitive impairment and depression significantly reduce quality of life in the aging population. This study aimed to investigate the prevalence of depressive symptoms and cognitive impairment and explore its relationship in the elderly.

Methods

A total of 1645 elderly people in nursing homes and 4703 elderly people in the community were enrolled in the survey. The Patient Health Questionnaire-9 and Ascertain Dementia-8 were employed to evaluate depressive symptoms and cognitive impairment.

Results

The overall prevalence of cognitive impairment was 12.5% in the community-dwelling group and 52.2% in the nursing home group. The prevalence of cognitive impairment in nursing homes was significantly higher than that in community-dwelling groups for the same age group (p < 0.001). The overall prevalence of depressive symptoms was 3.9% in the community-dwelling group and 2.0% in the nursing home group. The prevalence of depressive symptoms increased with age in the community-dwelling group (p < 0.001). The binary logistic regression results showed that the type of care mode affected the prevalence of cognitive impairment, and the elderly in nursing homes had a high risk of cognitive impairment (odds ratio [OR] = 3.528, 95% confidence interval [CI]: 2.209-5.635, p < 0.001); depressive symptoms had a significant positive correlation with the odds of cognitive impairment (OR = 1.854, 95% CI: 1.052-3.266, p < 0.05); and the cognitive impairment rate increased with age (OR = 1.412, 95% CI: 1.044-1.910, p < 0.05).

Conclusions

There was an increased prevalence in cognitive impairment as well as depressive symptoms in the aging population in Zhongshan city. Population-based mental health strategies need to be urgently implemented for the aging.

Methodological challenges in using screening tools for depression in migraine: A systematic review

BACKGROUND

Depression is frequently described to occur in migraine, and depression screening questionnaires are commonly used to evaluate depressive symptoms in patients with migraine. The present study aimed to investigate how the most common depression screening tools are used in migraine studies to determine whether they are applied and interpreted correctly.

METHODS

PubMed was systematically searched, and we included any study using the Beck Depression Inventory (BDI), Patient Health Questionnaire-9 (PHQ-9), Hospital Anxiety Depression Scale (HADS) or Hamilton Depression Rating Scale (HAM-D). The study included adults diagnosed with migraine based on the International Classification of Headache Disorders (ICHD-2 or ICHD-3).

RESULTS

The literature search generated 78 studies. Thirty-five (45%) of the included studies used a depression screening tool as evidence of depression. This applied to 53, 46, 47 and 13% of studies using PHQ, BDI, HADS and HAM-D, respectively. Only one study out of 35 confirmed the diagnosis with a diagnostic interview. The data presentation and interpretation across the studies was highly heterogeneous.

CONCLUSIONS

Screening tools as evidence of depression in patients with migraine may lead to inaccurate estimates of depression among migraine patients. There is a need for guidelines on and validation of depression screening tools in patients with migraine.

Satisfaction in surgically treated patients with degenerative cervical myelopathy: an observational study from the Canadian Spine Outcomes and Research Network

BACKGROUND CONTEXT

Healthcare reimbursement is evolving towards a value-based model, entwined and emphasizing patient satisfaction. Factors associated with satisfaction after degenerative cervical myelopathy (DCM) surgery have not been previously established.

PURPOSE

Our primary objective was to ascertain satisfaction rates and satisfaction predictors at 3 and 12 months following surgical treatment for DCM.

DESIGN

This is a prospective cohort study within Canadian Spine Outcomes and Research Network (CSORN).

PATIENT SAMPLE

Patients in the study were surgically treated for DCM patients who completed 3-month and 12-month follow-ups within CSORN between 2015 and 2021.

OUTCOME MEASURES

Data analyzed included patient demographic, surgical variables, patient-reported outcomes (NDI, NRS-NP, NRS-AP, SF-12-MCS, SF-12-PCS, ED-5Q, PHQ-8), MJOA and self-reported satisfaction on a Likert scale.

METHODS

Multivariable regression analysis was conducted to identify significant factors associated with satisfaction, address multicollinearity and ensure predictive accuracy. This process was conducted separately for the 3-month and 12-month follow-ups.

RESULTS

Six hundred and sixty-three patients were included, with an average age of 60, and an even distribution across MJOA scores (mild, moderate, severe). At 3-month and 12-month follow-up, satisfaction rates were 86% and 82%, respectively. At 12 months, logistic regression showed the odds of being satisfied varied by +24%, -3%, -10%, -14%, +3%, and +12% for each 1-point change between baseline and 12 months in MJOA, NDI, NRS-NP, NRS-AP, SF-12-MCS, SF-12-PCS. Satisfaction increased 11-fold for each 0.1-point increased in ED-5Q from baseline to 12 months. At baseline, for every 1-point increase in SF-12-MCS, the odds of being satisfied increased by 7%. At 3 months, all PROs (except for NRS-AP change and baseline SF-12-MCS) predicted satisfaction. All logistic regression analyses demonstrated excellent predictive accuracy, with the highest 12-month AUC of 0.86 (95%CI=0.81-0.90). No patient demographic or surgical factors influenced satisfaction.

CONCLUSIONS

Improvement in Patient Reported Outcomes and MJOA are strongly associated with patient satisfaction after surgery for DCM. The only baseline PRO associated with 12-months satisfaction was SF-12-MCS. No modifiable patient baseline characteristic or surgical variables were associated with satisfaction.