The influence of ‘cognitive busyness’ on causal attributions of challenging behaviour in dementia: A preliminary experimental study
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This study investigated the influence of ‘cognitive busyness’ (competing cognitive demands) on residential care staff attributions of challenging behaviour (CB) related to dementia. Following the model of attribution formation proposed by Gilbert, Pelham, and Krull (1988), it was hypothesised that care staff experiencing competing cognitive demands at the time of observing CBs linked with dementia would be more likely to make internal and controllable attributions regarding the causes of such behaviour. This study employed a cross-over experimental design. Thirty formal dementia care-workers viewed two video clips of simulated CB, one under conditions of cognitive ‘busyness’ and another under control conditions of no extra cognitive demands. These conditions occurred a week apart and were counterbalanced, i.e. one group of participants undertook the control condition first and then the experimental condition whilst another undertook the reverse. Self-report measures of attributions were administered after the viewing of each video clip. Competing cognitive demands significantly influenced staff attributions regarding CB, in relation to internality and controllability, and type of CB emerged as a potential moderating factor. No link was found between cognitive busyness and other attributional dimensions (stability and globality). Concurrent cognitive demands seem capable of impairing the ability to use situational information to form some causal attributions regarding CB in dementia but this might depend on the type of CB being witnessed. The results are discussed in relation to key methodological and conceptual issues.Keywords:
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Summary The impact of consensus information (i.e., information about how most people behave) on causal inferences was investigated. In a questionnaire format, 165 men and women university undergraduates recorded their expectations about the likelihood of target behaviors, received consensus feedback, and made judgments about the dispositional and situational causes of the behaviors. Three kinds of dependent measures (separate rating scales, mutually exclusive choices, and weighted choices) were included in order to explore the influence of different response alternatives on attributional judgments. Dispositional attributions (from the rating scales) produced a significant linear trend—they were largest in the low consensus condition and smallest in the high consensus condition, with the control condition falling between the two extremes. In contrast, situational attributions were unaffected by the consensus manipulation. As predicted, prior expectations mediated the relationship among target behavior, consensus information, and dispositional attributions. The relationship between dispositional and situational attributions was discussed, and the limitations of paper-and-pencil attribution paradigms were considered.
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Nisbett, et al., (1973) presented evidence that male actors use more situational than dispositional explanations for their own behavior and use more dispositional than situational attributions for their best friend. The present study replicated this finding for male actors ( n = 41), and demonstrates that female actors ( n = 41) produce the same pattern. A close examination of this data and Nisbett, et al.'s shows, however, that a different interpretation of the data is possible for a familiar other. Dispositional attributions are made equally to the self and to the best friend. Situational attributions are made primarily to the self.
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The distinction between dispositional and situational attributions initially described by Heider was subsequently incorporated into attribution theory. Most researchers implicitly assume an inversely dependent relationship between dispositional and situational attributions. It is argued, however, that this assumption is untenable by presenting empirical evidence showing that dispositional and situtational attributions do not vary inversely. This suggests that only studies that measure dispositional and situational attributions on separate scales and report the results of both can provide an opportunity for drawing unequivocal conclusions. Methodological implications are discussed and suggestions for future research are made.
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Abstract The present study was designed to assess the joint effects of situational information and the individual's attributional style on the choice and consequences of a stable or unstable attribution for failure. Israeli undergraduates were divided according to their attributional style for negative events into stable, undefined, and unstable attributors and were exposed to no-feedback or failure conditions in which they received instructions encouraging them to attribute failure to stable or unstable causes. Results indicate that the choice of a stable or unstable attribution for failure was influenced mainly by situational cues and that the individual's attributional style contributed to subsequent expectancies and the quality of performance following failure.
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Research in online content moderation has a long history of exploring different forms that moderation can take, including both user-driven moderation models on community-based platforms like Wikipedia, Facebook Groups, and Reddit, and centralized corporate moderation models on platforms like Twitter and Instagram. In this work I review different approaches to moderation research with the goal of providing a roadmap for researchers studying community self-moderation. I contrast community-based moderation research with platforms and policies-focused moderation research, and argue that the former has an important role to play in shaping discussions about the future of online moderation. I provide six guiding questions for future research that, if answered, can support the development of a form of user-driven moderation that is widely implementable across a variety of social spaces online, offering an alternative to the corporate moderation models that dominate public debate and discussion.
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Studies on cyberbullying are replete with questions about whether certain risk or protective factors are likely to predict cyberbullying outcomes such as cybervictimization. Such questions can often be reframed in terms of moderation effects, or hypotheses about how the effect of a predictor variable on an outcome variable depends on the value of a moderator variable. Demonstrating how questions about moderation effects are conventionally tested using the dataset from the Teens and Parents survey conducted by the Pew Research Centre’s Internet and American Life Project, the current study found two sets of significant moderation effects that could be interpreted to mean that the predictive relationship between traditional victimization and cybervictimization depend on the teenager’s intensity of SNS use and gender. A secondary purpose of this paper is to extend the conventional analytic approach in the form of an R package that provide researchers with methods – based on the pick-a-point technique and the Johnson-Neyman technique – which they can use to probe moderation effects they find significant in their research projects. Empirical illustrations with the cyberbullying dataset are provided throughout to demonstrate the use of this R package.
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Research on attribution "error" often implies that situational attributions are generally more accurate than dispositional ones, and the widespread acceptance of this implication has had important consequences for psychology. However, evidence also exists that would tend to support the reverse conclusion. In fact, the important difference between situational and dispositional attributions is not one of accuracy, but of level of analysis.
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