Depressive Mood States Research Articles

Ambient Air Pollution and Depressed Mood in the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave IV.

Depression is a major contributor to the global burden of disease. There is limited understanding of how environmental exposures may contribute to depression etiology. We used Wave IV of the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine associations between low-level ambient air pollution exposure and depressed mood in a generally healthy population of over 10,000 24-32 year olds. Annual mean PM2.5 levels in the 2008-2009 study were close to the current U.S. standard. In fully adjusted quasi-binomial logistic regression models, there were no meaningful associations between IQR increases in air pollutant and change in depressed mood status regardless of specific pollutant or moving average lags. In interaction effects models, an IQR increase in lag day 0-30 PM2.5 resulted in 1.20 (95% CI, 1.02-1.41) times higher likelihood of having depressed mood, but only for persons with chronic lung disease (interaction P=0.04); the association was null for participants without chronic lung disease (OR 0.98, 95% CI, 0.91, 1.05). Our findings suggest that among persons with a lifetime history of chronic lung disease, greater exposure to even low-level PM2.5, PM10, and sulfate may be associated with modest increases in the likelihood of having depressed mood.

Subclinical hypomanic experiences in young adults after sleep deprivation are independent of depressive disorders, chronotype or 5-HTTLPR polymorphism

Introduction The acute antidepressant effect of sleep deprivation (SD) in patients with depressive disorders has been studied for more than 60 years. However, hypomanic mood swings after partial or total SD have also been described in people without diagnosed mental disorders. Studying this phenomenon in the general population may yield insights about the mechanisms of therapeutic SD, mania and bipolar disorders. Methods A cross-sectional sample of young adults was recruited and classified into those who described having regularly occurring subclinical hypomanic experiences (ROHE) after SD and those who did not. History of psychiatric and physical illness, with screening for depression and mania, as well as alcohol or drug consumption, family history of depressive disorders or suicide, 5-HTTLPR polymorphism, and MEQ-SA chronotype were collected. Results A total of 251 participants were included; 39.0% indicated regularly having subclinical hypomanic experiences after SD. These experiences were not associated with depressive or mania screening, history of psychiatric illness, family history, 5-HTTLPR polymorphism, or MEQ-SA chronotype. Conclusions ROHE after non-therapeutic SD seem to be a relatively common phenomenon in young adults, independent of depressive mood state. Our results suggest that therapeutic SD may depend on a physiological phenomenon of subclinical affective disturbance after SD that affects a part of the general population, independent of psychiatric diagnosis. Further studies could elucidate associated factors and contribute to our understanding of (hypo-)manic mood states.

Depressive and mania mood state detection through voice as a biomarker using machine learning.

Depressive and manic states contribute significantly to the global social burden, but objective detection tools are still lacking. This study investigates the feasibility of utilizing voice as a biomarker to detect these mood states. Methods:From real-world emotional journal voice recordings, 22 features were retrieved in this study, 21 of which showed significant differences among mood states. Additionally, we applied leave-one-subject-out strategy to train and validate four classification models: Chinese-speech-pretrain-GRU, Gate Recurrent Unit (GRU), Bi-directional Long Short-Term Memory (BiLSTM), and Linear Discriminant Analysis (LDA). Our results indicated that the Chinese-speech-pretrain-GRU model performed the best, achieving sensitivities of 77.5% and 54.8% and specificities of 86.1% and 90.3% for detecting depressive and manic states, respectively, with an overall accuracy of 80.2%. These findings show that machine learning can reliably differentiate between depressive and manic mood states via voice analysis, allowing for a more objective and precise approach to mood disorder assessment.

9 The Relationship Between Depressive Mood and Mini Mental Status Examination Scores in Individuals with Heart Failure

Objective:Heart failure occurs when the heart is unable to support a flow of blood that meets the body’s needs, ultimately resulting in decreased oxygenation throughout the body— including the brain. Results of previous research suggest that individuals with heart failure exhibit both localized and diffuse neuropsychological deficits. The aims of this study are to meta-analytically examine a) the performance of participants with heart-failure and healthy controls on the Mini Mental State Examination (MMSE), a neuropsychological test of general cognition, and b) the role of depressive mood as a potential moderator of performance on the MMSE in these participants.Participants and Methods:Two researchers independently searched eight databases for articles that examined the neuropsychological functioning of patients with heart failure.Inclusion criteria identified studies that had a heart failure group with a comparable control group and reported on neuropsychological assessment for both groups. Studies were excluded if a heart failure group had any other type of major organ failure or if the comparison was between different classes of heart failure rather than between a heart failure group and healthy controls.Results:A meta-analysis using a random-effects model revealed a statistically significant and large effect size estimate (g= 0.727, p <.001) CI [.331, 1.123]. The heterogeneity was found to be statistically significant and in the large range, I2 = 83.027%, tau2 = .155, p < .001. A meta-regression analyzing the relationship between depressive mood and MMSE effect size estimates was statistically significant, Q residual = 8.715, df = 3, p = .03.Conclusions:This study is the first to examine the relationship between depressive mood and general cognitive status (as measured by the MMSE) in participants with heart failure. The strong relationship between cognitive status and heart failure, and the role of depression in explaining a statistically significant portion of the heterogeneity in the relationship seen in primary studies, highlights the importance of accurately assessing depression when studying the effect of heart failure on cognition. Further research needs to examine the impact of depression on quality of life in patients with heart failure as potentially mediated by difficulties in cognition.

Are dysfunctional attitudes elevated and linked to mood in bipolar disorder? A systematic review and meta-analysis.

Dysfunctional attitudes (DA) are higher in depression; however, less is understood about their role in bipolar disorder (BD). This paper aimed to explore the presence of DA in BD in comparison to clinical and non-clinical groups. Also explored were the associations between DA and mood states of depression, mania or euthymia in BD. A systematic review and meta-analysis were conducted. A total of 47 articles were included in the systematic review of which 23 were included in the meta-analysis. The quality of each study was rated. The meta-analysis showed significantly higher DA in BD than healthy controls (d = .70). However, no difference was observed between BD and unipolar participants (d = -.16). When reviewing mood state within BD, a significant mean difference was found between DA scores for euthymic and depressed participants (d = -.71), with those who were depressed scoring higher. Three studies found that psychological therapies significantly reduce DA in BD (d = -.38). These findings imply not only that DA are both a characteristic of BD that is not as prevalent in healthy populations but also that a depressed mood state is associated with increased severity. This implies that DA could possibly go 'offline' when mood symptoms are not present. Psychological therapies appear to reduce DA in BD. Implications for future research as well as practice-based implications are expanded on in the discussion.

Supra-second interval timing in bipolar disorder: examining the role of disorder sub-type, mood, and medication status

BackgroundWidely reported by bipolar disorder (BD) patients, cognitive symptoms, including deficits in executive function, memory, attention, and timing are under-studied. Work suggests that individuals with BD show impairments in interval timing tasks, including supra-second, sub-second, and implicit motor timing compared to the neuronormative population. However, how time perception differs within individuals with BD based on disorder sub-type (BDI vs II), depressed mood, or antipsychotic medication-use has not been thoroughly investigated. The present work administered a supra-second interval timing task concurrent with electroencephalography (EEG) to patients with BD and a neuronormative comparison group. As this task is known to elicit frontal theta oscillations, signal from the frontal (Fz) lead was analyzed at rest and during the task.ResultsResults suggest that individuals with BD show impairments in supra-second interval timing and reduced frontal theta power during the task compared to neuronormative controls. However, within BD sub-groups, neither time perception nor frontal theta differed in accordance with BD sub-type, depressed mood, or antipsychotic medication use.ConclusionsThis work suggests that BD sub-type, depressed mood status or antipsychotic medication use does not alter timing profile or frontal theta activity. Together with previous work, these findings point to timing impairments in BD patients across a wide range of modalities and durations indicating that an altered ability to assess the passage of time may be a fundamental cognitive abnormality in BD.

Serum Protein Profiling Reveals a Decrease in Apolipoprotein A-IV During a Clinical Depressive Mood State.

Depressive mood is a major psychiatric symptom that causes serious disturbances in daily life. Unlike physical symptoms, psychiatric symptoms are more difficult to evaluate objectively. Therefore, we aimed to discover biomarkers that reflect changes in serum protein metabolism during a clinical depressive mood. Serum protein profiling was conducted in participants who were not experiencing a current depressive episode (healthy individuals and patients in remission). Serum proteins were identified and quantified using liquid chromatography-tandem mass spectrometry. Differentially expressed proteins with a p-value <0.05 were selected, and candidate biomarkers were verified using multiple reaction monitoring analysis for absolute quantification. Apolipoprotein A-IV levels were lower in the group with a current episode of depression than in the remission and healthy control groups. Further, fibronectin levels were also lower in the group with a current episode of depression than in the healthy control group but not in the remission group. We found that apolipoprotein A-IV-mediated inflammation is involved in clinical depressive moods, possibly by inducing neurological changes in the brain. Therefore, apolipoprotein A-IV and fibronectin levels may be explored as potentially novel biomarkers for detecting a current episode of depression.

Nutrient Intake and Depressive Mood Status among College Students: A Case Study of Hunan Normal University

In order to understand the relationship between nutrient intake and depressive mood status among college students at Hunan Normal University, this study conducted a questionnaire survey to investigate the relevant issues. The results showed that the more imbalanced the types and insufficient the amounts of nutrient intake were, the stronger the degree of depression experienced by the students, and there was a significant correlation between nutrient intake and depressive mood status. These findings have important implications for improving the daily dietary habits of college students and changing the high prevalence of depressive mood problems at Hunan Normal University.

Identifying Current Feelings of Mild and Moderate to High Depression in Young, Healthy Individuals Using Gait and Balance: An Exploratory Study.

Depressive mood states in healthy populations are prevalent but often under-reported. Biases exist in self-reporting of depression in otherwise healthy individuals. Gait and balance control can serve as objective markers for identifying those individuals, particularly in real-world settings. We utilized inertial measurement units (IMU) to measure gait and balance control. An exploratory, cross-sectional design was used to compare individuals who reported feeling depressed at the moment (n = 49) with those who did not (n = 84). The Quality Assessment Tool for Observational Cohort and Cross-sectional Studies was employed to ensure internal validity. We recruited 133 participants aged between 18-36 years from the university community. Various instruments were used to evaluate participants' present depressive symptoms, sleep, gait, and balance. Gait and balance variables were used to detect depression, and participants were categorized into three groups: not depressed, mild depression, and moderate-high depression. Participant characteristics were analyzed using ANOVA and Kruskal-Wallis tests, and no significant differences were found in age, height, weight, BMI, and prior night's sleep between the three groups. Classification models were utilized for depression detection. The most accurate model incorporated both gait and balance variables, yielding an accuracy rate of 84.91% for identifying individuals with moderate-high depression compared to non-depressed individuals.

양육 어려움이 여성 한부모 임금근로자의 우울감에 미치는 영향

As the proportion of female single-parent families has increased in Korea, recent research results show that single mothers with unstable jobs experience additional psychological problems due to their employment instability. Thus, this study examined the effects of parenting difficulties and employment status of employed single mothers with school-age children on their depressive mood and the moderating effect of employment status. Data from the Study on the Status of Single-Parent Families in 2018 (N=988) was analyzed by SPSS PROCESS macro V.4 model 1. The results show that higher levels of parenting difficulties and temporary employment resulted in higher levels of depressive mood, and there was a moderating effect of employment status. That is, the depression level of employed single mothers who experience parenting difficulties was found to be more serious depending on unstable employment status. Based on the results, the relationship among parenting difficulties, depressive mood and unstable employment status of employed single mothers was discussed. Also, social welfare policies and programs to improve the mental health of employed single mothers were suggested.

Dynamic time warp analysis of individual symptom trajectories in individuals with bipolar disorder.

Manic and depressive mood states in bipolar disorder (BD) may emerge from the non-linear relations between constantly changing mood symptoms exhibited as a complex dynamic system. Dynamic Time Warp (DTW) is an algorithm that may capture symptom interactions from panel data with sparse observations over time. The Young Mania Rating Scale and Quick Inventory of Depressive Symptomatology were repeatedly assessed in 141 individuals with BD, with on average 5.5 assessments per subject every 3-6 months. Dynamic Time Warp calculated the distance between each of the 27 × 27 pairs of standardized symptom scores. The changing profile of standardized symptom scores of BD participants was analyzed in individual subjects, yielding symptom dimensions in aggregated group-level analyses. Using an asymmetric time-window, symptom changes that preceded other symptom changes (i.e., Granger causality) yielded a directed network. The mean age of the BD participants was 40.1 (SD 13.5) years old, and 60% were female participants. Idiographic symptom networks were highly variable between subjects. Yet, nomothetic analyses showed five symptom dimensions: core (hypo)mania (6 items), dysphoric mania (5 items), lethargy (7 items), somatic/suicidality (6 items), and sleep (3 items). Symptoms of the "Lethargy" dimension showed the highest out-strength, and its changes preceded those of "somatic/suicidality," while changes in "core (hypo)mania" preceded those of "dysphoric mania." Dynamic Time Warp may help to capture meaningful BD symptom interactions from panel data with sparse observations. It may increase insight into the temporal dynamics of symptoms, as those with high out-strength (rather than high in-strength) could be promising targets for intervention.

Spatial and Temporal Gait Characteristics in Patients Admitted to a Neuro-Rehabilitation Department with Age-Related White Matter Changes: A Gait Analysis and Clinical Study.

Patients with age-related white matter changes (ARWMC) frequently present a gait disorder, depression and cognitive impairment. Our aims are to define which alterations in the gait parameters are associated with motor or neuro-psychological impairment and to assess the role of motor, mood or cognitive dysfunction in explaining the variance of the gait parameters. Patients with gait disorders admitted to a Neuro-rehabilitation Department, affected by vascular leukoencephalopathy who had ARWMC confirmed by a brain MRI, were consecutively enrolled, classified by a neuroradiological scale (Fazekas 1987) and compared to healthy controls. We excluded subjects unable to walk independently, subjects with hydrocephalus or severe aphasia, with orthopaedic and other neurological pathologies conditioning the walking pattern. Patients and controls were assessed by clinical and functional scales (Mini Mental State Examination, Geriatric Depression Scale, Nevitt Motor Performance Scale, Berg Balance Scale, Functional Independence Measure), and computerised gait analysis was performed to assess the spatial and temporal gait parameters in a cross-sectional study. We recruited 76 patients (48 males, aged 78.3 ± 6.2 years) and 14 controls (6 males, aged 75.8 ± 5 years). In the multiple regression analysis, the gait parameter with overall best model summary values, associated with the ARWMC severity, was the stride length even after correction for age, sex, weight and height (R2 = 0.327). The motor performances justified at least in part of the gait disorder (R2 change = 0.220), but the mood state accounted independently for gait alterations (R2 change = 0.039). The increase in ARWMC severity, the reduction of motor performance and a depressed mood state were associated with a reduction of stride length (R = 0.766, R2 = 0.587), reduction of gait speed (R2 = 0.573) and an increase in double support time (R2 = 0.421). The gait disorders in patients with ARWMC are related to motor impairment, but the presence of depression is an independent factor for determining gait alterations and functional status. These data pave the way for longitudinal studies, including gait parameters, to quantitatively assess gait changes after treatment or to monitor the natural progression of the gait disorders.

Improving mental health and daytime function in adult insomnia patients predict cognitive behavioral therapy for insomnia effectiveness: A case-control study

ObjectiveThis study investigated demographic, sleep related symptoms and mental health status as predictors of clinically significant treatment responses to cognitive behavioral therapy in adults who have good adherence for the cognitive behavioral therapy for insomnia (CBT-I) program in primary insomnia. MethodsA total of 42 adults with primary insomnia disorder were treated with CBT-I at a university hospital from June 2020 to January 2021. Demographic variables were surveyed and sleep-related symptoms were measured using self-reported questionnaires before and after the intervention, comprising a 6-week interval. The treatment responder group was defined as patients with an Insomnia Severity Index change score >7 compared to baseline. Logistic regression and paired t-test examined whether these factors predicted treatment outcomes for CBT-I. ResultsDemographic variables did not predict treatment outcomes. Higher levels of anxiety were associated with a higher likelihood of treatment response (odds ratio [OR] = 1.234; confidence interval [CI]: 1.008–1.511). More severe insomnia at baseline was associated with a greater likelihood of treatment response (OR = 1.450; CI: 1.121–1.875). The lesser the dysfunctional beliefs and attitudes about sleep, the more effective the treatment response (OR = 0.943; CI: 0.904–0.984). Unlike the group of treatment responders, daytime function, depressive mood, and anxiety status did not improve in the group of treatment non-responders after CBT-I intervention. ConclusionsPatients with severe insomnia and anxiety at baseline should be treated more aggressively with CBT-I. During treatment, patients’ mental health problems and daytime activities should be continuously monitored, in order to help improve these problems which might strengthen the effectiveness of CBT-I.

The influence of childhood maltreatment on trait depression in patients with major depressive disorder: A moderated mediation model of rumination and mindful attention awareness

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders. Individuals who were exposed to childhood maltreatment might be an especially vulnerable group and were more likely to meet the diagnostic criteria for depression than those who were not. Trait depression refers to a personality trait predisposition to depression, expressed as the frequency of symptoms rather than a transient depressive mood state. Clarifying the relationship between childhood maltreatment and trait depression in patients with MDD has therefore become an important field of research. Childhood Trauma Questionnaire-Short Form (CTQ-SF), Ruminative Responses Scale (RRS), State-Trait Depression Scale (ST-DEP), and Mindful Attention Awareness Scale (MAAS) were used as research instruments. SPSS 23.0 statistical software was used for statistical analysis and examined the moderated mediation models. A total of 288 patients with MDD were included in this study. After standardization of the variables, the model revealed childhood maltreatment was positively associated with trait depression (β = 0.215, p < 0.001) and that rumination partially mediated the effect between childhood trauma and trait depression. Mindfulness moderated the association between rumination and trait depression in depressed patients (β = 0.171, p < 0.001). Simple slope tests showed that rumination significantly predicted trait depression in patients with high levels of mindfulness (bsimple = 0.460, p < 0.001, 95%CI = [0.339, 0.581]), while this predictive effect was not significant in patients with low levels (bsimple = 0.119, p = 0.097, 95%CI = [−0.022, 0.261]). After adding mediating variables, we found that the negative impact of childhood maltreatment on trait depression was both directly and indirectly through the patients' own ruminative levels. However, mindfulness performed a critical moderating role in the overall mediating model, aggravating the negative impact of childhood maltreatment on trait depression. There are several limitations in this study: the history of childhood maltreatment was reviewed and reported; the MAAS was a single-dimensional questionnaire that fails to measure the content of other mindfulness factors; cross-sectional data could not be used to infer the causal relationship between variables.

Association between depressive mood and chronic periodontitis among senior residents using the National Health Insurance Service-Senior Cohort Database.

Bacteria involved in chronic periodontal disease induce inflammatory cytokines. These cytokines can enter the brain through systemic circulation and cause depression. In this study, we investigated the association between depressed mood and chronic periodontitis in older adults in Korea. This study used data from the Life-changing Period Health Checkup (2007-2008), performed only at 66 years of age, which is available from the National Health Insurance Service-Senior Cohort Database. The depressed mood status was evaluated by three questions in the mental health examination. The definition of chronic periodontitis was determined based on the diagnosis and treatment codes for chronic periodontitis. Based on the three questions, we investigated the association between depressive mood and chronic periodontal disease by dividing the study population into 9622 depressed mood subjects (DMS) and 9091 non-depressed mood subjects (NDMS). Multivariable-adjusted logistic regression analysis was performed, and odds ratios (ORs) with 95% confidence intervals (95% CIs) were presented. Among the NDMS, 5390 patients with chronic periodontitis were identified, and among the DMS, 5964 patients with chronic periodontitis were identified. The crude OR (95% CI) for chronic periodontitis in DMS compared to NDMS was 1.12 (1.06-1.19). The adjusted OR (95% CI) for chronic periodontitis was 1.12 (1.06-1.19). As a result of confirming the effect of sex and comorbidity on the association between depressed mood and chronic periodontitis, a significant association was observed for women at 1.15 (1.07-1.25). In addition, the adjusted OR (95% CI) for depressive mood and chronic periodontitis was 1.15 (1.07-1.25) for patients with hypertension, 1.13 (1.03-1.25) for patients with diabetes, 1.12 (1.02-1.22) for patients with dyslipidemia, and 1.18 (1.04-1.34) for patients with heart disease. This study confirmed the relationship between depressed mood and chronic periodontitis in older adults. Therefore, education to strengthen the emotional management of older adults, especially with respect to depression, would play an auxiliary role in preventing and treating periodontitis.

A paper-based colorimetric method for monitoring of lithium therapeutic levels.

Lithium remains the "gold standard" for both acute and maintenance treatment of bipolar disorder (BD), a serious life-long condition characterised by recurrent episodes of depressed and manic mood states. However, lithium has a very narrow therapeutic range (0.4-1.2 mmol L-1) and despite its effectiveness in preventing and reducing mood swings and suicidality, it is a potentially hazardous drug. While it is crucial to carefully monitor lithium plasma levels, the current techniques of lithium monitoring are cumbersome and require frequent blood tests with the consequent discomfort which results in patients evading treatment. Therefore, development of low-cost and facile lithium detection techniques that can be translated into point-of-care devices for personal monitoring will be a major advance in the management of BD. In the current study, we present colorimetric determination of lithium therapeutic levels utilizing test paper strips, based on its reaction with the chromogenic agent Quinizarin. Exposure of Quinizarin-dipped test papers to samples of interstitial fluid (ISF) or dH2O spiked with therapeutic concentrations of lithium resulted in colour changes that were monitored using optical spectroscopy. The acquired spectra from the test papers show spectral variations which are related to lithium concentrations in spiked samples of dh2O and artificial ISF with a coefficient of determination (R2) of 0.9 and 0.8, respectively. Altogether, the spectrophotometric and colorimetric analyses demonstrated strong correlations between the observed colour changes and the concentrations of lithium present in the sample. Therefore, this study has demonstrated that Quinizarin-treated cellulose-based papers are suitable for the precise detection of changes in lithium therapeutic levels. This method is simple and very convenient and serves as a foundation for the future development of a paper-based colorimetric sensor for monitoring of lithium therapeutic levels in ISF and other non-invasive biological fluids.

Adiponectin, leptin, cortisol, neuropeptide Y and profile of mood states in athletes participating in an ultramarathon during winter: An observational study.

Background: The Montane® Yukon Arctic Ultra (YAU) is one of the longest (690km) and coldest (+10.6°C-43.9°C) ultramarathons worldwide. Taking part in an ultramarathon is associated with great physiological and psychological stress, which can affect one's mood, level of hormones, and peptides. The current study aimed to identify relationships between peptides, hormones, and mood states in participants during this ultramarathon. Methods: The study cohort consisted of 36 participants (19 men, 17 women, 38.64 ± 9.12years) split into a finisher (n = 10), non-finisher (n = 19), and control group (n = 7). Data were collected at four time points: baseline (PRE), during (D1 after 277km, D2 after 383km), and after the race (POST). Questionnaires were used to assess ratings of perceived exertion (RPE), total quality of recovery (TQR), and profile of mood states (POMS-SF). Serum NPY, leptin, adiponectin, and cortisol were measured. Results: Among non-finishers, scores for confusion, anger, depression, and tension-anxiety (PRE vs. D2, p < 0.05) increased, while vigor decreased (PRE vs. D1, p < 0.05). In contrast, finishers' tension-anxiety scores decreased (PRE vs. D1, p < 0.05). Fatigue increased in finishers (PRE vs. POST, p < 0.05) and non-finishers (PRE vs. D1, p < 0.05). In non-finishers, depressive mood correlated positively with leptin, anger, and confusion at several time points (p < 0.001). In finishers, NPY correlated with TQR at PRE (p < 0.05), while leptin correlated negatively with TQR at POST (p < 0.05). Tension-anxiety correlated highly with perceived exertion in non-finishers (p < 0.001) and with cortisol in finishers (p < 0.05) and non-finishers (p < 0.001). In finishers, confusion correlated negatively with NPY (p < 0.01). Conclusion: The study reveals an essential interplay between hormones and mood states affecting performance: Leptin was associated with anger and a depressive mood state in non-finishers and worse recovery in finishers. In contrast, NPY appeared linked to a lower confusion score and heightened recovery in finishers. A simultaneous increase in depressed mood, anger, tension-anxiety, and confusion might harm performance and lead to race failure.

Language Use in Mother-Adolescent Dyadic Interaction: Preliminary Results.

This preliminary study applied a computer-assisted quantitative linguistic analysis to examine the effectiveness of language-based classification models to discriminate between mothers (n = 140) with and without history of treatment for depression (51% and 49%, respectively). Mothers were recorded during a problem-solving interaction with their adolescent child. Transcripts were manually annotated and analyzed using a dictionary-based, natural-language program approach (Linguistic Inquiry and Word Count). To assess the importance of linguistic features to correctly classify history of depression, we used Support Vector Machines (SVM) with interpretable features. Using linguistic features identified in the empirical literature, an initial SVM achieved nearly 63% accuracy. A second SVM using only the top 5 highest ranked SHAP features improved accuracy to 67.15%. The findings extend the existing literature base on understanding language behavior of depressed mood states, with a focus on the linguistic style of mothers with and without a history of treatment for depression and its potential impact on child development and trans-generational transmission of depression.

Presleep Heart-Rate Variability Biofeedback Improves Mood and Sleep Quality in Chinese Winter Olympic Bobsleigh Athletes.

To evaluate the effectiveness of heart-rate variability (HRV) biofeedback in improving autonomic function, mood, and sleep in elite bobsleigh athletes. Eight Chinese Winter Olympic bobsleigh athletes (age: 24 [2]y, body mass: 89 [15]kg, and height: 184 [5]cm) completed a randomized crossover study with and without HRV biofeedback before a single night's sleep. HRV biofeedback was provided 35minutes prior to bedtime in the experimental condition. The assessment of HRV took place 45 and 10minutes before bedtime. The Profile of Mood States questionnaire was completed 50 and 15minutes prior to bedtime. Sleep duration and quality were measured through an air-mattress sleep-monitoring system. Sleep efficiency (P = .020; F = 7.831; CI, 0.008 to 0.072) and the percentage of deep sleep duration increased (P = .013; F = 10.875; CI, 0.006 to 0.035), while the percentage of light sleep decreased (P = .034; F = 6.893; CI, -0.038 to -0.002). Presleep HRV biofeedback increased parasympathetic and decreased sympathetic activity. Mood states of anger (P = .006, F = 7.573), panic (P = .031, F = 4.288), tension (P = .011, F = 6.284), depression (P = .010, F = 6.016), fatigue (P = .000, F = 16.901), and total mood disturbance (P = .001, F = 11.225) were reduced before sleep. Presleep HRV biofeedback improved some measures of autonomic function, mood, and sleep quality in Chinese Olympic bobsleigh athletes. Presleep HRV biofeedback provides a practical strategy that may help reduce sleep disturbances during periods of training and competition.

To what extent is circadian phase predictive of subjective jet lag in long-haul cabin crew pre- and post-trip?

Long-haul cabin crew regularly report misalignment between their circadian phase and the external world (i.e. jet lag). The extent to which changes in circadian phase relate to reported levels of jet lag remains unclear. The main aim of the present study was first to evaluate the relationship between objective (circadian phase) and subjective jet lag and second to explore the relative role of both subjective and objective psycho-behavioural factors in predicting the subjective experience of jet lag. Twenty-eight long-haul cabin crew completed questionnaires measuring diurnal preference, trip characteristics and subjective jet lag as a single and as a multidimensional measure. Sleep was monitored using actigraphy and urinary melatonin peak time was measured, at baseline (T1), e.g. before a long-haul trip and post-trip on the crew's first recovery day (T2). Subjective jet lag was also measured at both time points. At T1, later circadian phase related to increased unidimensional jet lag, however, a post-trip discrepancy was found between objective and subjective uni- and multidimensional jet lag measured at T2 and change from T1 to T2. After controlling for direction and size of circadian phase, increased uni- and multidimensional subjective jet lag was predicted by depressed mood states. The regression models including phase, diurnal preference, departure time on the outbound sector and arousal levels accounted for 28% of the variance in unidimensional jet lag and 53% of the variance in multidimensional jet lag. It was concluded that there is a discordance between objective and subjective jet lag post-trip. Further, subjective jet lag in long-haul cabin crew is better explained by mood impairment than circadian phase. The results are discussed with reference to the gap between subjective and objective jet lag and the role of psychology rather than just biology in the jet lag experience. The implications for improving health and safety in the workplace, through a better understanding of the role of human factors in the management of jet lag, are discussed.