Monitoring the effects of therapeutic interventions in depression through self-assessments

The treatment of major psychiatric disorders is an arduous and thorny path for the patients concerned, characterized by polypharmacy, massive adverse side effects, modest prospects of success, and constantly declining response rates. The more important is the early detection of psychiatric disorders prior to the development of clinically relevant symptoms, so that people can benefit from early interventions. A well-proven approach to monitoring mental health relies on voice analysis. This method has been successfully used with psychiatric patients to ‘objectively’ document the progress of improvement or the onset of relapse. The studies with psychiatric patients over 2-4 weeks demonstrated that daily voice assessments have a notable therapeutic effect in themselves. Therefore, daily voice assessments appear to be a lowthreshold form of therapeutic means that may be realized through self-assessments. To evaluate performance and reliability of this approach, we have carried out a longitudinal study on 82 university students in 3 different countries with daily assessments over 2 weeks. The sample included 41 males (mean age 24.2±3.83 years) and 41 females (mean age 21.6±2.05 years). Unlike other research in the field, this study was not concerned with the classification of individuals in terms of diagnostic categories. The focus lay on the monitoring aspect and the extent to which the effects of therapeutic interventions or of behavioural changes are visible in the results of self-assessment voice analyses. The test persons showed an over-proportionally good adherence to the daily voice analysis scheme. The accumulated data were of generally high quality: sufficiently high signal levels, a very limited number of movement artifacts, and little to no interfering background noise. The method was sufficiently sensitive to detect: i) habituation effects when test persons became used to the daily procedure; and ii) short-term fluctuations that exceeded prespecified thresholds and reached significance. Results are directly interpretable and provide information about what is going well, what is going less well, and where there is a need for action. The proposed self-assessment approach was found to be well-suited to serve as a health-monitoring tool for subjects with an elevated vulnerability to psychiatric disorders or to stress-induced mental health problems. Daily voice assessments are in fact a low-threshold form of therapeutic means that can be realized through selfassessments, that requires only little effort, can be carried out in the test person’s own home, and has the potential to strengthen resilience and to induce positive behavioural changes

Early detection of the risk of developing psychiatric disorders: a study of 461 Chinese university students under chronic stress

Chronic stress, a characteristic of modern time, has a significant impact on general health. In the context of psychiatric disorders, insufficient coping behavior under chronic stress has been linked to higher rates of (1) depressive symptoms among subjects of the general population, (2) relapse among patients under treatment for clinical depression, and (3) negative symptoms among subjects with an elevated vulnerability to psychosis. In this normative study we assessed basic coping behavior among 461 Chinese freshman university students along with their consumption behavior and general health in terms of regular exercises, physical health, psychosomatic disturbances, and mental health. The assessments relied on two instruments that have already demonstrated their capability of (1) reliably detecting insufficient coping behavior under chronic stress and (2) reliably quantifying the interrelation between coping behavior and mental health in the Western world. Thus, we aimed to complement existing data and to develop a generally available, socioculturally independent tool that can be used for the early detection of subjects with an elevated risk of mental health problems. Structural analyses yielded essentially the same scales "activity" and "defeatism" as previous studies on 2,500 students from Switzerland, Italy, Spain, the USA, and Argentina. These scales explained 74.3% of the observed variance in coping behavior among the 461 Chinese students. We found highly significant correlations (p < 0.0001) between the "defeatism" scale on the one hand, and the scales "regular use of medicine," "psychosomatic disturbances," and "impaired mental health" on the other. Particularly intriguing was the finding that a neural net classifier could be constructed to identify students with the highest contributions to the interrelation between "coping behavior" and "mental health," yielding a correlation coefficient as high as r = 0.597 for the respective subgroup. Based on the normative data, an online tool for risk assessments was developed with immediate feedback to users. This study provided another piece of evidence regarding the close link between basic coping behavior and mental health, across cultures and ethnicities. In consequence, our approach to quantifying basic coping behavior, along with other risk factors, can be expected to clear the way for an "early" detection of students with an elevated risk of stress-related mental health problems, nota bene prior to the development of clinically relevant symptoms. The socioeconomic impact of the potential prevention of depressive -disorders, and psychiatric disorders in general, may be enormous

Affective state and voice: cross-cultural assessment of speaking behavior and voice sound characteristics - a normative multicenter study of 577 + 36 healthy subjects

Human speech is greatly influenced by the speakers’ affective state, such as sadness, happiness, grief, guilt, fear, anger, aggression, faintheartedness, shame, sexual arousal, love, amongst others. Attentive listeners discover a lot about the affective state of their dialog partners with no great effort, and without having to talk about it explicitly during a conversation or on the phone. On the other hand, speech dysfunctions, such as slow, delayed or monotonous speech, are prominent features of affective disorders. This project was comprised of 4 studies with healthy volunteers from Bristol (English: n=117), Lausanne (French: n=128), Zurich (German: n=208), and Valencia (Spanish: n=124). All samples were stratified according to gender, age, and education. The specific study design with different types of spoken text along with repeated assessments at 14-day intervals allowed us to estimate the “natural” variation of speech parameters over time, and to analyze the sensitivity of speech parameters with respect to form and content of spoken text. Additionally, our project included a longitudinal self-assessment study with university students from Zurich (n=18) and unemployed adults from Valencia (n=18) in order to test the feasibility of the speech analysis method in home environments. The normative data showed that speaking behavior and voice sound characteristics can be quantified in a reproducible and language-independent way. The high resolution of the method was verified by a computerized assignment of speech parameter patterns to languages at a success rate of 90%, while the correct assignment to texts was 70%. In the longitudinal self-assessment study we calculated individual “baselines” for each test person along with deviations thereof. The significance of such deviations was assessed through the normative reference data. Our data provided gender-, age-, and language-specific thresholds that allow one to reliably distinguish between “natural fluctuations” and “significant changes”. The longitudinal self-assessment study with repeated assessments at 1-day intervals over 14 days demonstrated the feasibility and efficiency of the speech analysis method in home environments, thus clearing the way to a broader range of applications in psychiatry

Assessing Chronic Stress, Coping Skills, and Mood Disorders through Speech Analysis: A Self-Assessment ‘Voice App' for Laptops, Tablets, and Smartphones

Background. Computerized speech analysis (CSA) is a powerful method that allows one to assess stress-induced mood disturbances and affective disorders through repeated measurements of speaking behavior and voice sound characteristics. Over the past decades CSA has been successfully used in the clinical context to monitor the transition from “affectively disturbed” to “normal” among psychiatric patients under treatment. This project, by contrast, aimed to extend the CSA method in such a way that the transition from “normal” to “affected” can be detected among subjects of the general population through 10-20 self-assessments. Methods. Central to the project was a normative speech study of 5 major languages (English, French, German, Italian, Spanish). Each language comprised 120 subjects stratified according to gender, age, and education with repeated assessments at 14-day intervals (total n=697). In a first step, we developed a multivariate model to assess affective state and stress-induced bodily reactions through speaking behavior and voice sound characteristics. Secondly, we determined language-, gender-, and age-specific thresholds that draw a line between “natural fluctuations” and “significant changes”. Thirdly, we implemented the model along with the underlying methods and normative data in a self-assessment “voice app” for laptops, tablets, and smartphones. Finally, a longitudinal self-assessment study of 36 subjects was carried out over 14 days to test the performance of the CSA method in home environments. Results. The data showed that speaking behavior and voice sound characteristics can be quantified in a reproducible and language-independent way. Gender and age explained 15-35% of the observed variance, whereas the educational level had a relatively small effect in the range of 1-3%. The self-assessment “voice app” was realized in modular form so that additional languages can simply be “plugged-in”, once the respective normative data become available. Results of the longitudinal self-assessment study in home environments demonstrated that CSA methods work well under most circumstances. Conclusions. We have successfully developed and tested a self-assessment CSA method that can monitor transitions from “normal” to “affected” in subjects of the general population in the broader context of mood disorders. Our easy-to-use “voice app” evaluates sequences of 10-20 repeated assessments and watches for affect- and stress-induced deviations from baseline that exceed language-, gender-, and age-specific thresholds. Specifically, the “voice app” provides users with stress-related “biofeedback” and can help to identify that 10-15% subgroup of the general population that exhibits insufficient coping skills under chronic stress and may benefit from early detection and intervention prior to developing clinically relevant symptoms

Relationship between eating styles and temperament in an Anorexia Nervosa, Healthy Control, and Morbid Obesity female sample

Contains fulltext : 127209.pdf (Publisher’s version ) (Closed access)Objectives: Eating styles have been studied in both Obesity (OB) and Eating Disorders (ED), but they have not been examined in these two weight conditions together. The present study explores differences in eating styles in an Anorexia Nervosa (AN) and OB sample, compared to Healthy Controls (HC), and it analyses their relationship with Body Mass Index (BMI) and personality traits. Method: The total sample consisted of 291 female participants (66 AN, 79 OB and 146 HC). Evaluation: Assessment measures included the Dutch Eating Behaviour Questionnaire-DEBQ- and the Temperament and Character Inventory-Revised-TCI-R-. Results: The MANCOVA test showed significant differences among the three groups for all eating styles, with emotional eating being more typical in the OB group and restrained eating more typical in the AN group. Partial correlation analyses showed relationships between emotional and external eating and BMI, as well as relationships with different temperament and character traits. The step-wise discriminant function analysis showed that the DEBQ correctly classified 65.6% of the sample into the three weight categories; when combined with the TCI-R, correct classification increased to 72.6%. Conclusions: Weight conditions showed different eating behaviour patterns. Temperament and character traits were related to eating behaviours. DEBQ and TCI-R were able to discriminate between groups. Differences in eating styles in the weight groups can have implications for understanding the development and maintenance of OB and ED.8 p