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Publications of Patrick Gallagher    :chronological  alphabetical  combined listing:

%% Journal Articles   
   Author = {P. Gallagher and C.I. Voils},
   Title = {The percentage of people's behaviors that reflects their
             personality traits},
   Journal = {Under review},
   Year = {2011},
   Abstract = {Behavior can be highly variable across situations and can
             reflect many different levels of personality traits. Despite
             this variability, personality traits predict many different
             patterns of behavior and life outcomes. The purpose of the
             current research was to quantify how traits are related to
             behavior by measuring the percentage of behaviors that
             reflect trait standing. Participants completed standard
             Big-Five quesionnaires to assess trait standing and then
             reported the degree to which behaviors manifested
             personality trait content (personality states) several times
             per day for a week. Across Big-Five domains, 44% of
             behaviors were within one standard deviation of trait
             standing. The percentage of trait-reflective behaviors
             differed according to trait standing in three domains and
             according to intraindividual variability in the other two
             domains. These findings are the first to estimate the
             probability that any single behavior will reflect the
             actor’s trait standing, and have implications for behavior
             prediction and personality inference.},
   Key = {fds188041}

   Author = {P. Gallagher and R. Hoyle and W. Fleeson},
   Title = {Self-awareness of variability of trait expression in
   Journal = {Under review},
   Year = {2011},
   Abstract = {Personality traits are typically measured with single
             numbers that summarize self-beliefs or frequencies of
             certain behaviors. Trait manifestation in behavior, however,
             can be highly variable within individuals across time and
             situations. This variability gives rise to several aspects
             of trait expression that single-number summaries do not
             capture, such as average levels of variability and median or
             maximum levels of trait expression. The current research
             examined (1) whether people’s self-concepts include
             variability in trait expression, (2) whether people can
             accurately describe not only their average level of trait
             expression, but their entire distributions of trait
             expression via self-report, and (3) what implications this
             variability might have. In four studies, participants
             reported substantial amounts of variability in trait
             expression using a new measure of traits. This new
             instrument demonstrated discriminant, convergent, and
             predictive validity, as well as internal consistency and
             clear factor structure. Several parameters of
             participants’ self-reported distributions of trait
             expression strongly predicted corresponding parameters of
             actual behavioral distributions, and higher variability was
             related to long-term negative affect and low self-concept
             clarity. Self-reported variability was not related to
             several alternative measures of variability. Results
             indicate that variability in trait expression is part of
             people’s self-concepts, that people can report this
             variability, and that this variability might have important
   Key = {fds188028}

   Author = {P. Gallagher and W. Fleeson and R. Hoyle},
   Title = {A Self-regulatory Mechanism for Personality Trait Stability:
             Contra-trait Effort},
   Journal = {Social Psychological and Personality Science},
   Year = {2009},
   Abstract = {Despite the considerable influence of situational factors
             and the resulting variability in behavior, individuals
             maintain stable average ways of acting. The purpose of the
             current research was to investigate one possible explanation
             for this stability. It was hypothesized that behaviors that
             are at levels different from the actor’s average trait
             levels (contra-trait behaviors) demand more effort, or
             self-control, than do trait-typical behaviors. In Study 1,
             extraverted participants who acted at contra-trait levels
             reported their behaviors as more effortful, and this effect
             grew stronger over time. In addition, in a subsequent
             activity, observers rated extraverts who had acted
             contra-trait as behaving more extraverted, suggesting that
             fatigue from sustaining contra-trait behaviors may result in
             subsequent behaviors returning to trait-typical levels. In
             Study 2, participants reported on contextualized behaviors
             for seven days, and rated contra-trait behaviors as more
             effortful than trait-typical behaviors. This effect only
             held among non-habitual behaviors, implicating self-control
   Key = {fds164710}

   Author = {Fleeson, W. and Gallagher, P.},
   Title = {The implications of big-five standing for the distribution
             of trait manifestation in behavior: Fifteen
             experience-sampling studies and a meta-analysis},
   Journal = {Journal of Personality and Social Psychology},
   Volume = {97},
   Number = {6},
   Pages = {1097-1114},
   Year = {2009},
   Abstract = {One of the fundamental questions in personality psychology
             is whether and how strongly trait standing relates to the
             traits that people actually manifest in their behavior, when
             faced with real pressures and real consequences of their
             actions. One reason this question is fundamental is the
             common belief that traits do not predict how individuals
             behave, which leads to the reasonable conclusion that traits
             are not important to study. However, this conclusion is
             surprising given that there is almost no data on the ability
             of traits to predict distributions of naturally occurring,
             representative behaviors of individuals (and that there are
             many studies showing that traits do indeed predict specific
             behaviors). This paper describes a meta-analysis of 15
             experience-sampling studies, conducted over the course of
             eight years, amassing over 20,000 reports of trait
             manifestation in behavior. Participants reported traits on
             typical self-report questionnaires, then described their
             current behavior multiple times per day for several days, as
             the behavior was occurring. Results showed that traits,
             contrary to expectations, were strongly predictive of
             individual differences in trait manifestation in behavior,
             predicting average levels with correlations between .42 and
             .56 (approaching .60 for stringently restricted studies).
             Several other ways of summarizing trait manifestation in
             behavior were also predicted from traits. These studies
             provide evidence that traits are powerful predictors of
             actual manifestation of traits in behavior.},
   Key = {fds144718}

   Author = {Gallagher, P. and Dagenbach, D.},
   Title = {Manipulating noise frequencies alters hemispheric
             contributions to decision making},
   Journal = {Brain & Cognition, 64, 42-49},
   Year = {2007},
   Abstract = {Participants listened to the Asian disease problem framed in
             terms of either gains or losses and chose between two plans
             to combat the disease. All participants heard the problem
             embedded in other sounds; for some it was the relatively
             lower-frequency information, and for others it was the
             relatively higher-frequency information. The classic framing
             effect appeared only for those participants for whom the
             problem was the relatively lower-frequency information (p <
             .05). These results suggest that mixing filtered speech
             signals and noise may be a way to assess the role of the
             left and right hemisphere in various aspects of decision
   Key = {fds49897}

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