888 resultados para PSYCHIATRIC RATING-SCALE


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Background: Neuropsychiatric symptoms (NPS) affect almost all patients with dementia and are a major focus of study and treatment. Accurate assessment of NPS through valid, sensitive and reliable measures is crucial. Although current NPS measures have many strengths, they also have some limitations (e.g. acquisition of data is limited to informants or caregivers as respondents, limited depth of items specific to moderate dementia). Therefore, we developed a revised version of the NPI, known as the NPI-C. The NPI-C includes expanded domains and items, and a clinician-rating methodology. This study evaluated the reliability and convergent validity of the NPI-C at ten international sites (seven languages). Methods: Face validity for 78 new items was obtained through a Delphi panel. A total of 128 dyads (caregivers/patients) from three severity categories of dementia (mild = 58, moderate = 49, severe = 21) were interviewed separately by two trained raters using two rating methods: the original NPI interview and a clinician-rated method. Rater 1 also administered four additional, established measures: the Apathy Evaluation Scale, the Brief Psychiatric Rating Scale, the Cohen-Mansfield Agitation Index, and the Cornell Scale for Depression in Dementia. Intraclass correlations were used to determine inter-rater reliability. Pearson correlations between the four relevant NPI-C domains and their corresponding outside measures were used for convergent validity. Results: Inter-rater reliability was strong for most items. Convergent validity was moderate (apathy and agitation) to strong (hallucinations and delusions; agitation and aberrant vocalization; and depression) for clinician ratings in NPI-C domains. Conclusion: Overall, the NPI-C shows promise as a versatile tool which can accurately measure NPS and which uses a uniform scale system to facilitate data comparisons across studies. Copyright © 2010 International Psychogeriatric Association.

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ABSTRACT Background: Patients with dementia may be unable to describe their symptoms, and caregivers frequently suffer emotional burden that can interfere with judgment of the patient's behavior. The Neuropsychiatric Inventory-Clinician rating scale (NPI-C) was therefore developed as a comprehensive and versatile instrument to assess and accurately measure neuropsychiatric symptoms (NPS) in dementia, thereby using information from caregiver and patient interviews, and any other relevant available data. The present study is a follow-up to the original, cross-national NPI-C validation, evaluating the reliability and concurrent validity of the NPI-C in quantifying psychopathological symptoms in dementia in a large Brazilian cohort. Methods: Two blinded raters evaluated 312 participants (156 patient-knowledgeable informant dyads) using the NPI-C for a total of 624 observations in five Brazilian centers. Inter-rater reliability was determined through intraclass correlation coefficients for the NPI-C domains and the traditional NPI. Convergent validity included correlations of specific domains of the NPI-C with the Brief Psychiatric Rating Scale (BPRS), the Cohen-Mansfield Agitation Index (CMAI), the Cornell Scale for Depression in Dementia (CSDD), and the Apathy Inventory (AI). Results: Inter-rater reliability was strong for all NPI-C domains. There were high correlations between NPI-C/delusions and BPRS, NPI-C/apathy-indifference with the AI, NPI-C/depression-dysphoria with the CSDD, NPI-C/agitation with the CMAI, and NPI-C/aggression with the CMAI. There was moderate correlation between the NPI-C/aberrant vocalizations and CMAI and the NPI-C/hallucinations with the BPRS. Conclusion: The NPI-C is a comprehensive tool that provides accurate measurement of NPS in dementia with high concurrent validity and inter-rater reliability in the Brazilian setting. In addition to universal assessment, the NPI-C can be completed by individual domains. © International Psychogeriatric Association 2013.

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Smartphone technology provides free or inexpensive access to mental health and wellbeing resources. As a result the use of mobile applications for these purposes has increased significantly in recent years. Yet, there is currently no app quality assessment alternative to the popular ‘star’-ratings, which are often unreliable. This presentation describes the development of the Mobile Application Rating Scale (MARS) a new measure for classifying and rating the quality of mobile applications. A review of existing literature on app and web quality identified 25 published papers, conference proceedings, and online resources (published since 1999), which identified 372 explicit quality criteria. Qualitative analysis identified five broad categories of app quality rating criteria: engagement, functionality, aesthetics, information quality, and overall satisfaction, which were refined into the 23-item MARS. Independent ratings of 50 randomly selected mental health and wellbeing mobile apps indicated the MARS had excellent levels of internal consistency (α = 0.92) and inter-rater reliability (ICC = 0.85). The MARS provides practitioners and researchers with an easy-to-use, simple, objective and reliable tool for assessing mobile app quality. It also provides mHealth professionals with a checklist for the design and development of high quality apps.

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Background: Population-based surveys demonstrate cannabis users are more likely to use both illicit and licit substances, compared with non-cannabis users. Few studies have examined the substance use profiles of cannabis users referred for treatment. Co-existing mental health symptoms and underlying cannabis-related beliefs associated with these profiles remains unexplored. Methods: Comprehensive drug use and dependence severity (Severity of Dependence Scale-Cannabis) data were collected on a sample of 826 cannabis users referred for treatment. Patients completed the General Health Questionnaire, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire, and Positive Symptoms and Manic-Excitement subscales of the Brief Psychiatric Rating Scale. Latent class analysis was performed on last month use of drugs to identify patterns of multiple drug use. Mental health comorbidity and cannabis beliefs were examined by identified drug use pattern. Results: A three-class solution provided the best fit to the data: (1) cannabis and tobacco users (n = 176), (2) cannabis, tobacco, and alcohol users (n = 498), and (3) wide-ranging sub- stance users (n = 132). Wide-ranging substance users (3) reported higher levels of cannabis dependence severity, negative cannabis expectancies, lower opportunistic, and emotional relief self-efficacy, higher levels of depression and anxiety and higher manic-excitement and positive psychotic symptoms. Conclusion: In a sample of cannabis users referred for treatment, wide-ranging substance use was associated with elevated risk on measures of cannabis dependence, co-morbid psychopathology, and dysfunctional cannabis cognitions. These findings have implications for cognitive-behavioral assessment and treatment.

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Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.

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Background Methamphetamine use can produce symptoms almost indistinguishable from schizophrenia. Distinguishing between the two conditions has been hampered by the lack of a validated symptom profile for methamphetamine-induced psychiatric symptoms. We use data from a longitudinal cohort study to examine the profile of psychiatric symptoms that are acutely exacerbated by methamphetamine use. Methods 164 methamphetamine users, who did not meet DSM-IV criteria for a lifetime primary psychotic disorder, were followed monthly for one year to assess the relationship between days of methamphetamine use and symptom severity on the 24-item Brief Psychiatric Rating Scale. Exacerbation of psychiatric symptoms with methamphetamine use was quantified using random coefficient models. The dimensions of symptom exacerbation were examined using principal axis factoring and a latent profile analysis. Results Symptoms exacerbated by methamphetamine loaded on three factors: positive psychotic symptoms (suspiciousness, unusual thought content, hallucinations, bizarre behavior); affective symptoms (depression, suicidality, guilt, hostility, somatic concern, self-neglect); and psychomotor symptoms (tension, excitement, distractibility, motor hyperactivity). Methamphetamine use did not significantly increase negative symptoms. Vulnerability to positive psychotic and affective symptom exacerbation was shared by 28% of participants, and this vulnerability aligned with a past year DSM-IV diagnosis of substance-induced psychosis (38% vs. 22%, _2 (df1) = 3.66, p = 0.056). Conclusion Methamphetamine use produced a symptom profile comprised of positive psychotic and affective symptoms, which aligned with a diagnosis of substance-induced psychosis, with no evidence of a negative syndrome.

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World Conference on Psychology and Sociology 2012

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The Statistics Anxiety Rating Scale (STARS) was adapted into German to examine its psychometric properties (n = 400). Two validation studies (n = 66, n = 96) were conducted to examine its criterion-related validity. The psychometric properties of the questionnaire were very similar to those previously reported for the original English version in various countries and other language versions. Confirmatory factor analysis indicated 2 second-order factors: One was more closely related to anxiety and the other was more closely related to negative attitudes toward statistics. Predictive validity of the STARS was shown both in an experimental exam-like situation in the laboratory and during a real examination situation. Taken together, the findings indicate that statistics anxiety as assessed by the STARS is a useful construct that is more than just an expression of a more general disposition to anxiety.

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This study aimed to examine the structure of the statistics anxiety rating scale. Responses from 650 undergraduate psychology students throughout the UK were collected through an on-line study. Based on previous research three different models were specified and estimated using confirmatory factor analysis. Fit indices were used to determine if the model fitted the data and a likelihood ratio difference test was used to determine the best fitting model. The original six factor model was the best explanation of the data. All six subscales were intercorrelated and internally consistent. It was concluded that the statistics anxiety rating scale was found to measure the six subscales it was designed to assess in a UK population.

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A reliable and valid instrument is needed to screen for depression in palliative patients. The interRAI Depression Rating Scale (DRS) is based on seven items in the interRAI Palliative Care instrument. This study is the first to explore the dimensionality, reliability and validity of the DRS in a palliative population. Palliative home care patients (n = 5,175) residing in Ontario (Canada) were assessed with the interRAI Palliative Care instrument. Exploratory factor analysis and Mokken scale analysis were used to identify candidate conceptual models and evaluate scale homogeneity/performance. Confirmatory factor analysis compared models using standard goodness-of-fit indices. Convergent and divergent validity were investigated by examining polychoric correlations between the DRS and other items. The “known groups” test determined if the DRS meaningfully distinguished among client subgroups. The non-hierarchical two factor model showed acceptable fit with the data, and ordinal alpha coefficients of 0.83 and 0.82 were observed for the two DRS subscales. Omega hierarchical (ωh) was 0.78 for the bifactor model, with the general factor explaining three quarters of the common variance. Despite the multidimensionality evident in the factor analyses, bifactor modelling and the Mokken homogeneity coefficient (0.34) suggest that the DRS is a coherent scale that captures important information on sub-constructs of depression (e.g., somatic symptoms). Higher correlations were seen between the DRS and mood and psychosocial well-being items, and lower correlations with functional status and demographic variables. The DRS distinguished in the expected manner for known risk factors (e.g., social support, pain). The results suggest that the DRS is primarily unidimensional and reliable for use in screening for depression in palliative care patients.

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The aim of this study was to evaluate the performance of the Dimensional Clinical Personality Inventory (DCPI) using Rasch-based person and item analysis. 1281 participants were recruited, between 18 and 90 years of age (M=26.64; SD=8.94), 431 men (33.6%) and 127 (9.9%) patients diagnosed with axis I disorders and/or axis II according to DSM-IV-TR. Results indicated the IDCP scales performed reasonably well, and the usefulness of the analyses presented, demonstrate the Rasch model’s applicability for clinical applications. Among the important tools offered by the Rasch model, we explore the use of the person-item map, which visually presents the intuitively understandable psychological construct along the dimensional scale of the instrument.

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