278 research outputs found

    Pothead or pot smoker? a taxometric investigation of cannabis dependence

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    BACKGROUND: Taxometric methods were used to discern the latent structure of cannabis dependence. Such methods help determine if a construct is categorical or dimensional. Taxometric analyses (MAXEIG and MAMBAC) were conducted on data from 1,474 cannabis-using respondents to the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Respondents answered questions assessing DSM-IV criteria for cannabis dependence. RESULTS: Both taxometric methods provided support for a dimensional structure of cannabis dependence. CONCLUSION: Although the MAMBAC results were not entirely unequivocal, the majority of evidence favored a dimensional structure of cannabis dependence

    Tacit knowledg and the problem of computer modelling cognitive processes in science

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    Once one has said that there is a “tacit dimension” of some sort to communication or to some cognitive activity, it seems like an appropriate step to make it a topic for research. The difficulty with this suggestion is that it assumes that in fact we have some sort of unproblematic mode of access to our implicit understandings, to the “tacit dimension.” To be sure, sometimes portions of this “dimension” are revealed to us, as when we find that others don’t share some procedure we follow “naturally” or habitually, or when we find ourselves in circumstances where these procedures fail, and we are forced to, and can, find replacements for them. But these are perhaps exceptional cases, revealed for us through contingent and possibly rare circumstances. And if this is so, it follows that a project of revealing the tacit dimension would depend on some premises that would give one some assurances that one’s techniques indeed reveal the necessary parts of it. It is one thing to have a method of turning over rocks to see if there are salamanders under them; it is another to form a project of counting all the salamanders in a given area, for one doesn’t know that they are all assessable by the known means

    High impact  =  high statistical standards? Not necessarily so.

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    What are the statistical practices of articles published in journals with a high impact factor? Are there differences compared with articles published in journals with a somewhat lower impact factor that have adopted editorial policies to reduce the impact of limitations of Null Hypothesis Significance Testing? To investigate these questions, the current study analyzed all articles related to psychological, neuropsychological and medical issues, published in 2011 in four journals with high impact factors: Science, Nature, The New England Journal of Medicine and The Lancet, and three journals with relatively lower impact factors: Neuropsychology, Journal of Experimental Psychology-Applied and the American Journal of Public Health. Results show that Null Hypothesis Significance Testing without any use of confidence intervals, effect size, prospective power and model estimation, is the prevalent statistical practice used in articles published in Nature, 89%, followed by articles published in Science, 42%. By contrast, in all other journals, both with high and lower impact factors, most articles report confidence intervals and/or effect size measures. We interpreted these differences as consequences of the editorial policies adopted by the journal editors, which are probably the most effective means to improve the statistical practices in journals with high or low impact factors

    Experience of Pleasure and Emotional Expression in Individuals with Schizotypal Personality Features

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    Difficulties in feeling pleasure and expressing emotions are one of the key features of schizophrenia spectrum conditions, and are significant contributors to constricted interpersonal interactions. The current study examined the experience of pleasure and emotional expression in college students who demonstrated high and low levels of schizotypal personality disorder (SPD) traits on self-report questionnaires. One hundred and seventeen subjects with SPD traits and 116 comparison controls were recruited to participate. Cluster analyses conducted in the SPD group identified negative SPD and positive SPD subgroups. The negative SPD group exhibited deficient emotional expression and anticipatory pleasure, but showed intact consummatory pleasure. The positive SPD group reported significantly greater levels of anticipatory, consummatory and total pleasure compared to the control group. Both SPD groups reported significantly more problems in everyday memory and greater levels of depressive and anxiety-related symptoms

    The Latent Structure of Autistic Traits:A Taxometric, Latent Class and Latent Profile Analysis of the Adult Autism Spectrum Quotient

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    Autistic traits are widely thought to operate along a continuum. A taxometric analysis of Adult Autism Spectrum Quotient data was conducted to test this assumption, finding little support but identifying a high severity taxon. To understand this further, latent class and latent profile models were estimated that indicated the presence of six distinct subtypes: one with little probability of endorsing any autistic traits, one engaging in ‘systemising’ behaviours, three groups endorsing multiple components of Wing and Gould’s autistic triad, and a group similar in size and profile to the taxon previously identified. These analyses suggest the AQ (and potentially by extension autistic traits) have a categorical structure. These findings have important implications for the analysis and interpretation of AQ data

    Worries about being judged versus being harmed: Disentangling the association of social anxiety and paranoia with schizotypy

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    Paranoia is a dimension of clinical and subclinical experiences in which others are believed to have harmful intentions. Mild paranoid concerns are relatively common in the general population, and more clinically severe paranoia shares features with social anxiety and is a key characteristic of schizotypy. Given that subclinical manifestations of schizotypy and paranoia may predict the occurrence of more severe symptoms, disentangling the associations of these related constructs may advance our understanding of their etiology; however no known studies to date have comprehensively evaluated how paranoia relates to social anxiety and schizotypy. The current research sought to examine the association of paranoia, assessed across a broad continuum of severity, with 1) the positive and negative schizotypy dimensions and 2) social anxiety. Specifically, the study tested a series of six competing, a priori models using confirmatory factor analysis in a sample of 862 young adults. As hypothesized, the data supported a four-factor model including positive schizotypy, negative schizotypy, social anxiety, and paranoia factors, suggesting that these are distinct constructs with differing patterns of interrelationships. Paranoia had a strong association with positive schizotypy, a moderate association with social anxiety, and a minimal association with negative schizotypy. The results are consistent with paranoia being part of a multidimensional model of schizotypy and schizophrenia. Prior studies treating schizotypy and schizophrenia as homogenous constructs often produce equivocal or non-replicable results because these dimensions are associated with distinct etiologies, presentations, and treatment responses; thus, the present conceptualization of paranoia within a multidimensional schizotypy framework should advance our understanding of these constructs. © 2014 Horton et al

    Multiple Deprivation, Severity and Latent Sub-Groups:Advantages of Factor Mixture Modelling for Analysing Material Deprivation

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    Material deprivation is represented in different forms and manifestations. Two individuals with the same deprivation score (i.e. number of deprivations), for instance, are likely to be unable to afford or access entirely or partially different sets of goods and services, while one individual may fail to purchase clothes and consumer durables and another one may lack access to healthcare and be deprived of adequate housing . As such, the number of possible patterns or combinations of multiple deprivation become increasingly complex for a higher number of indicators. Given this difficulty, there is interest in poverty research in understanding multiple deprivation, as this analysis might lead to the identification of meaningful population sub-groups that could be the subjects of specific policies. This article applies a factor mixture model (FMM) to a real dataset and discusses its conceptual and empirical advantages and disadvantages with respect to other methods that have been used in poverty research . The exercise suggests that FMM is based on more sensible assumptions (i.e. deprivation covary within each class), provides valuable information with which to understand multiple deprivation and is useful to understand severity of deprivation and the additive properties of deprivation indicators

    Thinking styles and doctors' knowledge and behaviours relating to acute coronary syndromes guidelines

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    Background How humans think and make decisions is important in understanding behaviour. Hence an understanding of cognitive processes among physicians may inform our understanding of behaviour in relation to evidence implementation strategies. A personality theory, Cognitive-Experiential Self Theory (CEST) proposes a relationship between different ways of thinking and behaviour, and articulates pathways for behaviour change. However prior to the empirical testing of interventions based on CEST, it is first necessary to demonstrate its suitability among a sample of healthcare workers. Objectives To investigate the relationship between thinking styles and the knowledge and clinical practices of doctors directly involved in the management of acute coronary syndromes. Methods Self-reported doctors' thinking styles (N = 74) were correlated with results from a survey investigating knowledge, attitudes, and clinical practice, and evaluated against recently published acute coronary syndrome clinical guidelines. Results Guideline-discordant practice was associated with an experiential style of thinking. Conversely, guideline-concordant practice was associated with a higher preference for a rational style of reasoning. Conclusion Findings support that while guidelines might be necessary to communicate evidence, other strategies may be necessary to target discordant behaviours. Further research designed to examine the relationships found in the current study is required

    Selecting Forecasting Methods

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    I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods. Structured judgment, “what experts advise,” which is to rate methods against prespecified criteria, is promising. Statistical criteria, “what should work,” are widely used and valuable, but risky if applied narrowly. Relative track records, “what has worked in this situation,” are expensive because they depend on conducting evaluation studies. Guidelines from prior research, “what works in this type of situation,” relies on published research and offers a low-cost, effective approach to selection. Using a systematic review of prior research, I developed a flow chart to guide forecasters in selecting among ten forecasting methods. Some key findings: Given enough data, quantitative methods are more accurate than judgmental methods. When large changes are expected, causal methods are more accurate than naive methods. Simple methods are preferable to complex methods; they are easier to understand, less expensive, and seldom less accurate. To select a judgmental method, determine whether there are large changes, frequent forecasts, conflicts among decision makers, and policy considerations. To select a quantitative method, consider the level of knowledge about relationships, the amount of change involved, the type of data, the need for policy analysis, and the extent of domain knowledge. When selection is difficult, combine forecasts from different methods
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