The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform
Erin Koffel - One of the best experts on this subject based on the ideXlab platform.
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Further validation of the Iowa Sleep Disturbances Inventory.
Psychological assessment, 2011Co-Authors: Erin KoffelAbstract:This study examined the reliability and validity of an expanded version of the Iowa Sleep Disturbances Inventory (ISDI; Koffel & Watson, 2010) in 2 samples (219 college students and 200 psychiatric patients). The expanded ISDI includes the scales Sleep Paralysis and Sleep Hallucinations. These scales, along with the Nightmares scale, help define a higher order factor entitled Unusual Sleep Experiences. This factor was distinct from the Insomnia and Lassitude factors that were reported previously. The expanded ISDI showed strong evidence of convergent and discriminant validity with the corresponding interview ratings on a clinician rating version of the ISDI. Mean convergent correlations were .68 in students and .70 in patients. Convergent correlations were significantly higher than discriminant correlations in 99.8% of the 624 comparisons. This study also reports the associations of higher order sleep factors with questionnaire and interview measures of pathological symptoms (e.g., depression, anxiety, dissociation, and schizotypy). The Lassitude factor was specific to dysphoria, whereas the Unusual Sleep Experiences factor was specific to posttraumatic stress disorder (PTSD) and dissociation. Finally, several ISDI scales showed strong evidence of specificity in relation to pathological symptoms; in particular, there were strong associations between (a) ISDI Fatigue and measures of dysphoria, (b) ISDI Nightmares and measures of PTSD, and (c) ISDI Sleep Hallucinations and measures of dissociation.
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The two-factor structure of sleep complaints and its relation to depression and anxiety.
Journal of abnormal psychology, 2009Co-Authors: Erin Koffel, David WatsonAbstract:Although sleep complaints are common in depression and anxiety, there is little agreement as to how they should be organized and assessed. It is also unclear whether sleep complaints show specificity with certain disorders or whether they are nonspecific symptoms. The authors examined the structure of sleep complaints and the relations of these complaints to depression and anxiety in 3 samples: college students, older adults, and psychiatric patients. Exploratory and confirmatory factor analyses indicated that sleep complaints consistently defined 2 distinct dimensions: Insomnia and Lassitude. The Insomnia factor included indicators of early, middle, and late insomnia, as well as poor sleep quality. The Lassitude factor included measures of hypersomnia, fatigue, and sleepiness. Both factors were significantly related to symptoms and diagnoses of depression and anxiety. However, Lassitude was more strongly related to symptoms of depression and anxiety than was Insomnia. In addition, Lassitude showed specificity to measures and diagnoses of depression compared with anxiety disorders. This specificity can be explained by Lassitude's relation with negative and positive emotionality, both of which are components of depression.
David Watson - One of the best experts on this subject based on the ideXlab platform.
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The Structure, Specificity, and Validity of Depression Symptoms
Understanding the Emotional Disorders, 2017Co-Authors: David Watson, Michael W. O’haraAbstract:This chapter examines key symptom criteria of major depression. It begins by developing a comprehensive measurement model based on six symptom dimensions: dysphoria, Lassitude, insomnia, suicidality, appetite loss, and appetite gain. It then demonstrates that these symptom dimensions are robust and show impressive convergent and discriminant validity across multiple methods (self-reports, clinicians’ ratings, interview assessments). Three types of symptoms—dysphoria, Lassitude, and suicidality—exhibit strong criterion validity and significant specificity in relation to diagnoses of major depression. In contrast, symptoms of insomnia and appetite disturbance display unimpressive criterion validity and poor specificity. Moreover, these nonspecific symptoms provided little or no incremental information in logistic regression analyses. Taken together, these results suggest that the diagnosis of depression can be improved by focusing primarily on strong and specific symptoms (such as dysphoria and Lassitude) and deemphasizing weak and nonspecific symptoms (i.e., insomnia and appetite disturbance).
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The two-factor structure of sleep complaints and its relation to depression and anxiety.
Journal of abnormal psychology, 2009Co-Authors: Erin Koffel, David WatsonAbstract:Although sleep complaints are common in depression and anxiety, there is little agreement as to how they should be organized and assessed. It is also unclear whether sleep complaints show specificity with certain disorders or whether they are nonspecific symptoms. The authors examined the structure of sleep complaints and the relations of these complaints to depression and anxiety in 3 samples: college students, older adults, and psychiatric patients. Exploratory and confirmatory factor analyses indicated that sleep complaints consistently defined 2 distinct dimensions: Insomnia and Lassitude. The Insomnia factor included indicators of early, middle, and late insomnia, as well as poor sleep quality. The Lassitude factor included measures of hypersomnia, fatigue, and sleepiness. Both factors were significantly related to symptoms and diagnoses of depression and anxiety. However, Lassitude was more strongly related to symptoms of depression and anxiety than was Insomnia. In addition, Lassitude showed specificity to measures and diagnoses of depression compared with anxiety disorders. This specificity can be explained by Lassitude's relation with negative and positive emotionality, both of which are components of depression.
Sakura Kadowaki - One of the best experts on this subject based on the ideXlab platform.
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Analysis of psychological stress factors by using bayesian network
2013 IEEE International Conference on Mechatronics and Automation, 2013Co-Authors: Kazuhito Sato, Hiroaki Otsu, Hirokazu Madokoro, Sakura KadowakiAbstract:This paper presents a gender-specific stress model to analyze the psychological stress factors on intentional facial expressions. We have focused on the relationship between facial expression intensity and Stress Response Scale (SRS-18). In this paper, we extract three facial expressions (i.e., happiness, anger, and sadness) from the basic six facial expressions defined by Ekman, and then represent a graphical model of the relationship between these three facial expressions and the psychological stress factors (“i.e., depression and anxiety”, “displeasure and anger”, and “Lassitude”). In the experiment, we created an original facial expression dataset consisting of three facial expressions and a psychological stress dataset by SRS-18 obtained from 10 subjects during 7-20 weeks at one week interval. As the results of probabilistic reasoning based on the observed values of each facial expression, such trends are obtained as follows. BNs shows trends of different stress factor between men and women in relations of expression levels and psychological stress. Stress models appeared on happiness faces of “Lassitude” factor in men, the anger faces of “displeasure and anger” were affected with stress factors in women.
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Analysis of psychological stress factors and facial parts effect on intentional facial expressions
2012Co-Authors: Hiroaki Otsu, Kazuhito Sato, Hirokazu Madokoro, Sakura KadowakiAbstract:This paper presents a method to create an individual model to describe relations between facial expressions and stress patterns using Bayesisan networks. We extracted relations between three facial expressions (happiness, anger, and sadness) for the basic six facial expressions defined by Ekman and psychological stress factors (dysphoria and anxiety, displeasure and anger, and Lassitude).
M.t. Abou-saleh - One of the best experts on this subject based on the ideXlab platform.
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Predictors of response to amine-specific antidepressants
Journal of affective disorders, 1995Co-Authors: R.a. Burns, T. Lock, D.r.l. Edwards, Cornelius Katona, D.a. Harrison, Mary M. Robertson, B.l. Nairac, M.t. Abou-salehAbstract:Discriminant function analysis of data from a double-blind comparative trial of lofepramine (a noradrenaline-specific reuptake inhibitor) and fluoxetine (a serotonin-specific reuptake inhibitor), involving 183 patients was used to identify predictors of response. Psychic anxiety significantly predicted a positive response to antidepressant medication, whereas psychomotor retardation, observed sadness, subjective Lassitude and somatic complaints were significant predictors of nonresponse. Age, gender, endogenicity, duration of illness and number of previous episodes were not predictive of response. Significant differences were found between predictors of response to fluoxetine and lofepramine (P < 0.001 all groups). Predictors of response to lofepramine were similar to overall predictors, i.e., psychic anxiety predicted responders whilst observed sadness, psychomotor retardation, Lassitude, inability to feel and somatic complaints predicted nonresponders. In contrast, baseline weight loss predicted response to fluoxetine, whereas anxiety, reduced insight and a tendency to blame others significantly predicted nonresponse. Such findings have practical implications for the management of depressive illness.
B.l. Nairac - One of the best experts on this subject based on the ideXlab platform.
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Predictors of response to amine-specific antidepressants
Journal of affective disorders, 1995Co-Authors: R.a. Burns, T. Lock, D.r.l. Edwards, Cornelius Katona, D.a. Harrison, Mary M. Robertson, B.l. Nairac, M.t. Abou-salehAbstract:Discriminant function analysis of data from a double-blind comparative trial of lofepramine (a noradrenaline-specific reuptake inhibitor) and fluoxetine (a serotonin-specific reuptake inhibitor), involving 183 patients was used to identify predictors of response. Psychic anxiety significantly predicted a positive response to antidepressant medication, whereas psychomotor retardation, observed sadness, subjective Lassitude and somatic complaints were significant predictors of nonresponse. Age, gender, endogenicity, duration of illness and number of previous episodes were not predictive of response. Significant differences were found between predictors of response to fluoxetine and lofepramine (P < 0.001 all groups). Predictors of response to lofepramine were similar to overall predictors, i.e., psychic anxiety predicted responders whilst observed sadness, psychomotor retardation, Lassitude, inability to feel and somatic complaints predicted nonresponders. In contrast, baseline weight loss predicted response to fluoxetine, whereas anxiety, reduced insight and a tendency to blame others significantly predicted nonresponse. Such findings have practical implications for the management of depressive illness.
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Predictors of response to amine-specific antidepressants Research report
1995Co-Authors: T. Lock, B.l. NairacAbstract:Discriminant function analysis of data from a double-blind comparative trial of lofepramine (a noradrenaline-specific reuptake inhibitor) and fluoxetine (a serotonin-specific reuptake inhibitor), involving 183 patients was used to identify predictors of response. Psychic anxiety significantly predicted a positive response to antidepressant medication, whereas psychomotor retardation, observed sadness, subjective Lassitude and somatic complaints were significant predictors of nonresponse. Age, gender, endogenicity, duration of illness and number of previous episodes were not predictive of response. Significant differences were found between predictors of response to fluoxetine and lofepramine (P < 0.001 all groups). Predictors of response to lofepramine were similar to overall predictors, i.e., psychic anxiety predicted responders whilst observed sadness, psychomotor retardation, Lassitude, inability to feel and somatic complaints predicted nonresponders. In contrast, baseline weight loss predicted response to fluoxetine, whereas anxiety, reduced insight and a tendency to blame others significantly predicted nonresponse. Such findings have practical implications for the management of depressive illness.
