Neural Patterns of the Implicit Association Test

Healy, Graham; Boran, Lorraine; Smeaton, Alan F.

doi:10.3389/fnhum.2015.00605

Cited by 34 publications

(37 citation statements)

References 59 publications

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“…Results indicating a two-factor structure further support the ideation-to-action framework of suicidality which highlights the existence of both long-standing suicide risk factors and acute warning signs for imminent suicide (Klonsky & May, 2014;Rudd et al, 2006). Findings from the current study identify Stress, Agitation, and Psychological Pain as possible warning signs for adolescent suicide risk, whereas Self-Hate and Hopelessness are potential long-term risk factors.…”

Section: Discussionsupporting

confidence: 68%

“…Although the UPPS-P was designed to assess traits, and the Agitation item on the SSF-4 assesses a more statespecific level of Agitation, similar measures have been used in past SSF validation studies as a proxy measure of Agitation (Conrad et al, 2009). Both high negative urgency and Agitation have been found to associate with suicide behavior (Busch, Fawcett, & Jacobs, 2003;Klonsky & May, 2010). This subscale is made up of 12 items (ex.…”

Section: Suicide Status Form For Adolescentsmentioning

confidence: 99%

“…Reaction times to classify words in the death or me and life or me categories were recorded in milliseconds and analyzed using the standard IAT algorithm (Greenwald, Nosek, & Banaji, 2003) to calculate a net difference d/s IAT score. The IAT (Greenwald, McGhee, & Schwartz, 1998) has been shown to have strong reliability of Cronbach's alpha = 0.78 (Cunningham, Preacher, & Banaji, 2001;Greenwald & Nosek, 2001) and construct validity (Lane, Banaji, Nosek, & Greenwald, 2007).…”

Section: Suicide Status Form For Adolescentsmentioning

confidence: 99%

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Validating the Suicide Status Form for the Collaborative Assessment and Management of Suicidality in a Psychiatric Adolescent Sample

Brausch

O’Connor

Powers

et al. 2019

Suicide & Life Threat Behav

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Background For adults, the Collaborative Assessment and Management of Suicidality (CAMS; Jobes, (2006, Managing suicidal risk: A collaborative approach, New York, Guilford) and Jobes, (2016, Managing suicidal risk: A collaborative approach, New York, Guilford)) is a treatment framework with replicated evidenced‐based support for effectiveness. The current study is a psychometric validation of the Suicide Status Form (SSF‐IV), the main assessment and treatment planning tool for CAMS, in an adolescent psychiatric sample. Methods Data were collected from 100 adolescents, aged 12–17, in inpatient settings (mean age = 14.6; 67.5% female, 80% white). Adolescents were administered Part A of the SSF‐IV, as well as measures of overall suicide risk (both explicit and implicit), mental pain, Stress, Agitation, reasons for living, and self‐esteem. Results Confirmatory factor analysis found a two‐factor model to fit the data best, with Psychological Pain, Stress, and Agitation loading on one factor, and Hopelessness and Self‐Hate on another. All of the core SSF constructs except Stress were significantly correlated with concurrent measures, and SSF overall suicide risk was significantly correlated with self‐reported and implicit suicidality. Adolescents with suicide attempt history reported significantly higher scores on most core SSF items compared to no attempt history. Conclusions These results provide initial psychometric validation of the SSF for use with adolescents and indicate that it does not need to be adapted or modified for this age group.

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Section: Discussionsupporting

confidence: 68%

Section: Suicide Status Form For Adolescentsmentioning

confidence: 99%

Section: Suicide Status Form For Adolescentsmentioning

confidence: 99%

See 1 more Smart Citation

Validating the Suicide Status Form for the Collaborative Assessment and Management of Suicidality in a Psychiatric Adolescent Sample

Brausch

O’Connor

Powers

et al. 2019

Suicide & Life Threat Behav

View full text Add to dashboard Cite

show abstract

“…Furthermore, one could consider using multimodal measures to further investigate cognitive processes involved in completing implicit measures. For example, Healy et al (2015) demonstrated that Electroencephalography could be used to examine the extent to responses to implicit measures are resulting from automatic association (activation) or context factors, by relating neural activity to different phases in the IAT. Both the advanced modeling and multimodal approaches could contribute to our understanding of implicit attitudes within the educational area.…”

Section: Resultsmentioning

confidence: 99%

Teachers' Implicit Attitudes Toward Students From Different Social Groups: A Meta-Analysis

Cate

Glock

2019

Front. Psychol.

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Teachers' attitudes toward their students have been associated with differential teachers' expectations and, in turn, with students' educational pathways. Theories of social cognition can explain the link between attitudes and behavior. In this regard, the distinction between implicit and explicit attitudes is worth to be considered, whereby implicit attitudes are automatically activated when the attitude object is present and guide automatic behavior. In contrast, explicit attitudes infer deliberation and reflection, hence affecting controlled behavior. As teachers often are required to act immediately in situations that do not allow for thoughtful reflection due to time restraints, teachers' implicit attitudes concerning different student groups with shared characteristics, such as gender or ethnicity, may be especially important when considering teachers' behavior in relation to students' educational pathways. This notion is reflected by an increased interest in adopting implicit methodology in the educational domain. Over the last 10 years, several studies have been conducted in different countries, involving in-and pre-service teachers and investigating their attitudes toward different student groups. Estimates of effects have varied and may be affected by sampling bias. To systematically review and integrate data from different studies, this meta-analysis focuses on teachers' implicit attitudes. Following the systematic search of the database and initial screening, 43 articles were identified from which 22, describing 34 studies, were retained for the meta-analysis after further inspection. First analyses revealed an estimated average effect size of 0.56 for implicit attitudes in favor of non-marginalized groups. As there was a large extent of heterogeneity between studies, several moderator variables were investigated. Results showed that the employed implicit measure and stimulus materials as well as the student target group affected the effect sizes. Low or non-significant relationships were reported between implicit and explicit attitudes. Findings are discussed in terms of theory and future research.

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“…Recordings were taken from 32 scalp electrodes based on the 10/20 system, with a ground electrode at Fpz. Electrodes were referenced online to a virtual ground point (i.e., reference-free acquisition) formed within the amplifier (Luck, 2014), a method used in previous studies (Healy, Boran, & Smeaton, 2015; Novak & Foti, 2015; Weiler, Hassall, Krigolson, & Heath, 2015). The electrooculogram was recorded from two auxiliary electrodes places 1 cm above and below the left eye, forming a bipolar channel.…”

Section: Methodsmentioning

confidence: 99%

The temporal dynamics of reversal learning: P3 amplitude predicts valence-specific behavioral adjustment

Donaldson¹,

Oumeziane²,

Hélie³

et al. 2016

Physiology & Behavior

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Adapting behavior to dynamic stimulus-reward contingences is a core feature of reversal learning and a capacity thought to be critical to socio-emotional behavior. Impairment in reversal learning has been linked to multiple psychiatric outcomes, including depression, Parkinson's disorder, and substance abuse. A recent influential study introduced an innovative laboratory reversal-learning paradigm capable of disentangling the roles of feedback valence and expectancy. Here, we sought to use this paradigm in order to examine the time-course of reward and punishment learning using event-related potentials among a large, representative sample (N = 101). Three distinct phases of processing were examined: initial feedback evaluation (reward positivity, or RewP), allocation of attention (P3), and sustained processing (late positive potential, or LPP). Results indicate a differential pattern of valence and expectancy across these processing stages: the RewP was uniquely related to valence (i.e., positive vs. negative feedback), the P3 was uniquely associated with expectancy (i.e., unexpected vs. expected feedback), and the LPP was sensitive to both valence and expectancy (i.e., main effects of each, but no interaction). The link between ERP amplitudes and behavioral performance was strongest for the P3, and this association was valencespecific. Overall, these findings highlight the potential utility of the P3 as a neural marker for feedback processing in reversal-based learning and establish a foundation for future research in clinical populations.

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Neural Patterns of the Implicit Association Test

Cited by 34 publications

References 59 publications

Validating the Suicide Status Form for the Collaborative Assessment and Management of Suicidality in a Psychiatric Adolescent Sample

Validating the Suicide Status Form for the Collaborative Assessment and Management of Suicidality in a Psychiatric Adolescent Sample

Teachers' Implicit Attitudes Toward Students From Different Social Groups: A Meta-Analysis

The temporal dynamics of reversal learning: P3 amplitude predicts valence-specific behavioral adjustment

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