Symptom centrality and infrequency of endorsement identify adolescent depression symptoms more strongly associated with life satisfaction

Development and validation of a nomogram for predicting depressive symptoms in dentistry patients: A cross-sectional study

Depressive symptoms are frequently occur among dentistry patients, many of whom struggle with dental anxiety and poor oral conditions. Identifying the factors that influence these symptoms can enable dentists to recognize and address mental health concerns more effectively. This study aimed to investigate the factors associated with depressive symptoms in dentistry patients and develop a clinical tool, a nomogram, to assist dentists in predicting these symptoms. Methods: After exclusion of ineligible participants, a total of 1355 patients from the dentistry department were included. The patients were randomly assigned to training and validation sets at a 2:1 ratio. The LASSO regression method was initially employed to select highly influrtial features. This was followed by the application of a multi-factor logistic regression to determine independent factors and construct a nomogram. And it was evaluated by 4 methods and 2 indicators. The nomograms were formulated based on questionnaire data collected from dentistry patients. Nomogram2 incorporated factors such as medical burden, personality traits (extraversion, conscientiousness, and emotional stability), life purpose, and life satisfaction. In the training set, Nomogram2 exhibited a Concordance index (C-index) of 0.805 and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.805 (95% CI: 0.775-0.835). In the validation set, Nomogram2 demonstrated an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.810 (0.768-0.851) and a Concordance index (C-index) of 0.810. Similarly, Nomogram1 achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.816 (0.788-0.845) and a Concordance index (C-index) of 0.816 in the training set, and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.824 (95% CI: 0.784-0.864) and a Concordance index (C-index) of 0.824 in the validation set. Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) indicated that Nomogram1, which included oral-related factors (oral health and dental anxiety), outperformed Nomogram2. We developed a nomogram to predict depressive symptoms in dentistry patients. Importantly, this nomogram can serve as a valuable psychometric tool for dentists, facilitating the assessment of their patients' mental health and enabling more tailored treatment plans.

Cognitive restraint, uncontrolled eating, and emotional eating. The Italian version of the Three Factor Eating Questionnaire-Revised 18 (TFEQ-R-18): a three-step validation study

BACKGROUND

The Three Factor Eating Questionnaire-Revised 18 (TFEQ-R-18) is an extensively used questionnaire to measure three transdiagnostic features of eating behavior: cognitive restraint, uncontrolled eating, and emotional eating.

OBJECTIVE

This research aims to investigate the psychometric properties of the Italian version of the TFEQ-R-18 in three large community samples.

METHOD

Cross-sectional research designs were employed. In Study 1 (N = 537), an exploratory graph analysis (EGA) was used to examine item clustering within the TFEQ-R-18. In Study 2 (N = 645), a confirmatory factor analysis (CFA) was conducted to test its structural validity. In Study 3 (N = 346), a MANOVA was employed assessing mean differences across eating disorders (e.g., anorexia nervosa, bulimia nervosa, binge eating disorder).

RESULTS

In Study 1, the EGA accurately identified the three original dimensions of the TFEQ-R-18. Study 2 showed that the Italian TFEQ-R-18 has good fit indexes (CFI = 0.989, RMSEA = 0.064; 90% CI [0.058, 0.070], SRMR = 0.062), and possesses robust psychometric properties. Study 3 reveals distinct, statistically significant differences among eating disorders.

CONCLUSION

The TFEQ-R-18 proves to be a concise and precise tool for measuring transdiagnostic eating behaviors. Its applicability in the Italian context, supported by robust psychometric properties, suggests its utility for both research and clinical purposes. The findings affirm its potential to inform interventions aimed at enhancing psychological health.

LEVEL OF EVIDENCE

Level V, descriptive study.

Depressive symptoms and loneliness among early adolescents: a psychometric network analysis approach

BACKGROUND

Previous studies demonstrate a high prevalence of depression and loneliness among adolescents. Although they often co-occur, the relationship between symptoms of depression and loneliness remains poorly understood. This study investigates: (a) the symptoms of depression that are connected to loneliness; (b) the role played by loneliness in the network of depression symptoms; and (c) whether the method used to measure loneliness (single-item direct or multi-item indirect) affects the relationship of loneliness with depressive symptoms.

METHODS

Participants were 496 Polish adolescents (50.8% girls) aged 11 to 13, who completed: (a) the 10-item Major Depressive Disorder subscale of the Revised Child Anxiety and Depression Scale; (b) the 11-item De Jong Gierveld Loneliness Scale (indirect loneliness), and (c) a single direct question evaluating loneliness: 'I'm lonely'. Networks were estimated using a Gaussian Graphical Model.

RESULTS

Loneliness shows a direct relationship with three affective symptoms of depression: sadness, worthlessness, and anhedonia, which mediate relationships with somatic symptoms. In contrast to previous studies, loneliness has the lowest level of centrality among all elements of the network. The method used to assess loneliness did not significantly affect the connections between loneliness and depressive symptoms.

CONCLUSIONS

Loneliness and depression overlap since they are formed by the same cognitive biases and deficits in emotion regulation but differ in the level of generality. In loneliness, they have an interpersonal context, while symptoms of depression can be intrapersonal. This helps us to understand why cognitive interventions, as compared to those which are social, are more effective in reducing loneliness.

Effect of Sleep Quality on Anxiety and Depression Symptoms among College Students in China's Xizang Region: The Mediating Effect of Cognitive Emotion Regulation

BACKGROUND

While the exact mechanisms are not fully understood, there are significant links between sleep quality, anxiety, depressive symptoms, and cognitive emotion regulation. This research examines how sleep quality affects anxiety and depressive symptoms, as well as the potential of cognitive emotion regulation strategies (CERS) to moderate the impact of sleep quality on these symptoms.

METHODS

The Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), the Cognitive Emotion Regulation Questionnaire (CERQ), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder Scale-7 (GAD-7) were all completed online by students from two colleges in China's Xizang region.

RESULTS

The study included 4325 subjects. The prevalence of poor sleep quality, anxiety symptoms, and depression symptoms was 45.69%, 36.81%, and 51.86%, respectively. We observed significant direct effects on poor sleep and severity of anxiety/depression: c'1 = 0.586 (0. 544-0.628), and c'2 = 0.728 (0.683-0.773). Adaptive CERS only had a mediating effect on the relationship between sleep quality and depression symptoms, with a1b3 = -0.005 (-0.011--0.001). The link between poor sleep quality and the intensity of anxiety and depression was significantly affected by the indirect effects of maladaptive CERS: effect a2b2 = 0.126 (0.106-0.147), and effect a2b4 = 0.145 (0.123-0.167).

CONCLUSIONS

Individuals who experience poor sleep quality are more likely to have increased levels of anxiety and depression. However, enhancing sleep quality led to a decrease in anxiety and depression levels. Adaptive CERS did not predict anxiety, but they did predict depression. Multiple maladaptive CERS could increase levels of anxiety and depression. To prevent mental stress, it is crucial to examine sleep problems among college students, understand their cognitive strategies, promote the adoption of adaptive CERS, and reduce the reliance on maladaptive CERS.

Stigma toward internalizing and externalizing disorders: How do adolescents perceive their peers? A network analysis approach

This study's first aim was to explore whether stigma's facets differ between internalizing and externalizing disorders in adolescence. The second aim was to compare the relationships among stigma's facets toward these disorders. Two vignettes depicting a peer with Major Depressive Disorder (MDD) or Attention-Deficit Hyperactivity Disorder (ADHD) were used with 616 adolescents in Italy. A Repeated measure MANOVA showed biogenetic causes, social distancing, and discomfort were more attributed to depression, while dangerousness to ADHD. Furthermore, a Psychometric Network Analysis showed no differences between these disorders in the relations among stigma's components. However, dangerousness seemed to be among the nodes with the highest levels of "strength," confirming previous literature that shows that dangerousness plays a major role in stigma.

Depressive symptom networks in the UK general adolescent population and in those looked after by local authorities

BACKGROUND

Despite the importance of understanding depressive symptom constellations during adolescence and specifically in looked-after children, studies often only apply sum score models to understand depression in these populations, neglecting associations among single symptoms that can be elucidated in network analysis. The few network analyses in adolescents have relied on different measures to assess depressive symptoms, contributing to inconsistent cross-study results.

OBJECTIVE

In three population-based studies using the Short Mood and Feelings Questionnaire, we used network analyses to study depressive symptoms during adolescence and specifically in looked-after children.

METHOD

We computed cross-sectional networks (Gaussian Graphical Model) in three separate datasets: the Mental Health of Children and Young People in Great Britain 1999 survey (n=4235, age 10-15 years), the mental health of young people looked after by local authorities in Great Britain 2002 survey (n=643, age 11-17 years) and the Millennium Cohort Study in the UK 2015 (n=11 176, age 14 years).

FINDINGS

In all three networks, self-hate emerged as a key symptom, which aligns with former network studies. I was no good anymore was also among the most central symptoms. Among looked-after children, I was a bad person constituted a central symptom, while this was among the least central symptom in the other two datasets. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition symptom I did not enjoy anything was not central.

CONCLUSIONS

Findings indicate that looked-after children's depressive symptoms may be more affected by negative self-evaluation compared with the general population.

CLINICAL IMPLICATIONS

Intervention efforts may benefit from being tailored to negative self-evaluations.

Adolescent Life Satisfaction: Association with Psychological, School-Related, Religious and Socially Supportive Factors

Adolescent life satisfaction is crucial to later adult health and well-being; therefore, searching for its correlates should receive priority in research. The aim of this study was to explore the role of psychological (depression, future orientation), school-related (school achievement, satisfaction with school), religious (going to church, importance of religion), socially supportive (family and friend support), other familial, and sociodemographic (age, sex, self-assessed socioeconomic status) factors in adolescent life satisfaction. This cross-sectional survey (entitled Szeged Youth Study 2022) involved a sample of middle and high school students (N = 2239, aged 11-18 years, 51.8% females) from public schools in Szeged, Hungary. Besides descriptive statistics, correlation and multiple regression analysis were applied to the data analyses. Boys scored higher on the life satisfaction scale (Satisfaction with Life Scale, SWLS), while the level of depression (Children's Depression Inventory, CDI) was higher among girls. In the final regression model, family support was the strongest predictor of life satisfaction (β = 0.44, p < 0.001), followed by depression (as a negative contributor), socioeconomic (SES) self-assessment, future orientation, satisfaction with school, going to church, and friend support. School prevention programs should be focused not only on preventing mental health difficulties but also promoting adolescent well-being.

Feeling unloved is the most robust sign of adolescent depression linking to family communication patterns

Using network analysis, this study investigated how family communication patterns (Conversation and Conformity) were related to and predictive of adolescent overall depression severity and specific symptoms. A community sample of adolescents (10-17 years, n = 1327) completed the Children's Depression Inventory and the Revised Family Communication Pattern Instrument. Depressive symptoms were also re-assessed 6 months later. Results showed that Conversation orientation protected against, whereas Conformity orientation increased the risk of adolescent depression. Family communication particularly influenced the child's feeling of being unloved, and feeling unloved was the only symptom prospectively predicted by two communication orientations at baseline. These findings revealed the path linking family factors to adolescent depression and may have implications for future family-based interventions.

Adolescent depression beyond DSM definition: a network analysis

Calls for refining the understanding of depression beyond diagnostic criteria have been growing in recent years. We examined the prevalence and relevance of DSM and non-DSM depressive symptoms in two Brazilian school-based adolescent samples with two commonly used scales, the Patient Health Questionnaire (PHQ-A) and the Mood and Feelings Questionnaire (MFQ). We analyzed cross-sectional data from two similarly recruited samples of adolescents aged 14-16 years, as part of the Identifying Depression Early in Adolescence (IDEA) study in Brazil. We assessed dimensional depressive symptomatology using the PHQ-A in the first sample (n = 7720) and the MFQ in the second sample (n = 1070). We conducted network analyses to study symptom structure and centrality estimates of the two scales. Additionally, we compared centrality of items included (e.g., low mood, anhedonia) and not included in the DSM (e.g., low self-esteem, loneliness) in the MFQ. Sad mood and worthlessness items were the most central items in the network structure of the PHQ-A. In the MFQ sample, self-hatred and loneliness, two non-DSM features, were the most central items and DSM and non-DSM items in this scale formed a highly interconnected network of symptoms. Furthermore, analysis of the MFQ sample revealed DSM items not to be more frequent, severe or interconnected than non-DSM items, but rather part of a larger network of symptoms. A focus on symptoms might advance research on adolescent depression by enhancing our understanding of the disorder.