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Clinical Psychopharmacology of Amphetamine and Related Compounds
Published in John Caldwell, S. Joseph Mulé, Amphetamines and Related Stimulants: Chemical, Biological, Clinical, and Sociological Aspects, 2019
As has already been stated, amphetamine was noted to possess a euphoriant action in early clinical studies.4–6 In one of the first controlled studies designed to evaluate this euphoriant effect 29 mg of amphetamine per 70 kg was administered subcutaneously to 20 normal volunteer subjects and was compared with pentobarbitone, morphine, heroin, and placebo.33 Thirteen of the twenty subjects rated amphetamines as the most pleasant of the drugs they had received, several remarking that they felt particularly “happy” or “enthusiastic”. A similar result was obtained in a study involving 239 subjects completing an adjective check-list; here too such words as “happy” and “friendly” were checked more often after amphetamine than after plecebo.34 A comparison of dextroamphetamine and levoamphetamine revealed that the dextrorotatory isomer was the more potent in elevating mood in normal subjects, being at least twice as potent as the levo form.35 Furthermore, a greater euphoriant action was observed after 20 mg dextroamphetamine than after 10 mg. However, in another study,36 no euphoriant activity was seen during a 5 min recording period that followed a slow (over 1 hr) intravenous infusion of 20 mg methamphetamine. This unexpected absence of observed euphoriant effect may have been attributable to the very limited period of observation and the length of time taken over the infusion.
Mode of Action of Selected Botanicals That Lower Blood Glucose
Published in Robert Fried, Richard M. Carlton, Type 2 Diabetes, 2018
Robert Fried, Richard M. Carlton
Overweight or obese men, aged 40 to 65 years, were randomly assigned to take 400-mg capsules of EGCG, or the placebo lactose, twice daily for 8 weeks. Oral glucose tolerance testing and measurement of metabolic risk factors (BMI, waist circumference, percentage body fat, blood pressure, total cholesterol, low-density lipoprotein (LDL) cholesterol, HDL cholesterol, skin tags) were conducted pre- and postintervention. Mood was also evaluated weekly using the University of Wales Institute of Science and Technology mood adjective checklist.
Anxiolytics: Predicting Response/Maximizing Efficacy
Published in Mark S. Gold, R. Bruce Lydiard, John S. Carman, Advances in Psychopharmacology: Predicting and Improving Treatment Response, 2018
Assessment of response to anxiolytic medications in general requires that specific anxiety symptoms are measured as targets of drug action. Where and when does the patient experience anticipatory anxiety and how much of it is experienced? In the measurement of anxiety in various mental disorders, we recommend the use of mood adjective checklists, or some other validated anxiety scale. Izard’s mood adjective checklist, the Differential Emotive Scale-State Anxiety Inventory is particularly useful because it measures all seven fundamental motions simultaneously and only requires about 5 min for the patient to fill out.4 These are filled out when or shortly after anxiety is experienced, and they enable good quantification of target anxiety. Even with mood adjective checklist results, it is important to question the patient carefully about changes in target symptoms, the presence of new symptoms, or possible side effects. At the time the lorazepam script is given, the patient is instructed about anxiety record keeping and when and how to fill out the mood adjective checklist. A fairly accurate quantification of the patient’s anxiety can often be estimated from clinical history, and this provides part of the baseline. If laboratory tests are pending, it is possible to have patients delay starting the medications until a small baseline anxiety record can be obtained.
Exploring the effects of road type on drivers’ eye behavior and workload
Published in International Journal of Occupational Safety and Ergonomics, 2023
Kai Yao, Shengyuan Yan, Fengjiao Li, Yingying Wei, Cong Chi Tran
At present, the research on safe driving mainly focuses on the evaluation of drivers’ mental workload. The research hopes to prevent traffic accidents by reducing the driver’s mental workload. Mental workload is the degree of mental effort required to complete a particular task [6]. The driver’s mental workload can be considered as the interaction result of task requirement and attention [7,8]. The widely used assessment methods include the positive affect and negative affect schedule (PANAS) [9], activation–deactivation adjective check list (AD-ACL) [10], subjective workload assessment technology (SWAT) [11], NASA task load index (NASA-TLX) [12], overall workload scale (OW) [13] and modified Cooper–Harper scale (MCH) [14]. Di Stasi et al. [15] applied the mental workload test method to establish a risk behavior model for motorcycle riding simulation, and used the subjective workload assessment technique to evaluate the workload during driving and calling progress. Compared with subjective evaluation methods, physiological measurement methods are relatively less affected by personal bias and hobbies, and thus reflect the reliable mental workload level. To accurately evaluate the driver’s mental workload, Yan et al. [16] proposed a driver’s mental workload prediction and evaluation model based on physical indexes. Savage et al. [17] believed that blinking behavior can accurately reflect the change of driver’s mental workload.
Correlates of the personality change judgments of individuals who have MS
Published in Brain Injury, 2021
Rodger Weddell, Samantha Fisher-Hicks
Participants rated their behavior on semantic differential items (see Figure 1). This questionnaire was based on the adjectives used in the HISD (7) and Brooks and McKinlay personality adjective checklist (10). Items from the original scale that seemed potentially pejorative (e.g., mature-childish) were excluded. Ten and 4 items were unique to the HISD and the personality adjective checklist, respectively. A further 4 adjectival dimensions were similar, and the personality checklist version was selected. For example, the talkative-quiet option was used in preference to the HISD talkative-withdrawn version as it more closely represented amount of speech produced. The talkative-withdrawn option was potentially more conceptually complex: some respondents might rate themselves as talkative despite being withdrawn at the point of rating because they were depressed, while organic cognitive symptoms might reduce the speech of other participants. Five of the original items were transformed by pairing one pole with a clearer opposite. For example, the HSID emotional-stable item potentially conflates lack of emotion due to neural damage to emotional mechanisms and emotional reactivity to stress. Accordingly, the emotional-unemotional and stable-changeable items were added to the specific characteristics questionnaire. Since the original scales were devised, there has been increasing appreciation of the impact of brain injury on empathy and social bonding processes. Given the evidence of empathy impairments following various causes of brain damage including MS (28–31), we included items such as concerned about others versus not concerned about others to see if perceived PC might be linked with perceived empathy changes and with social context measures.
Development of a Short Form of the Abridged Big Five-Dimensional Circumplex Model to Aid with the Organization of Personality Traits
Published in Journal of Personality Assessment, 2019
Meredith A. Bucher, Douglas B. Samuel
Thus, findings from both articles suggest that the AB5C model is a promising and broadly inclusive faceted model that could be useful for integrating other faceted measures. Interestingly, however, Woods and Anderson (2016) did not use the IPIP–AB5C itself to support their argument for the AB5C model. Instead, they extracted five orthogonal components from a 100-item adjective checklist to specify high and low poles of each domain within their sample. Although such a strategy has some appeal, the local specification of factors creates the possibility of idiosyncratic findings and limits the integration of findings across studies.