Enhancing Students' Engagement by Increasing Teachers' Autonomy Support

Engagement refers to the behavioral intensity and emotional quality of a person's active involvement during a task. Recognizing the benefits highly engaged people experience, we tested whether classroom teachers could incorporate the relatively foreign concept of autonomy support into their motivating styles as a way to promote their students' engagement during instruction. Teachers in an experimental group and teachers in a delayed-treatment control group received information and guidance consistent with self-determination theory on how to support students' autonomy. Over a series of 3 classroom observations, trained raters scored each teacher's autonomy support and 2 measures of their students' engagement–task involvement and influence attempts. Trained teachers displayed significantly more autonomy-supportive behaviors than did nontrained teachers. Further, the more teachers used autonomy support during instruction, the more engaged were their students. This was true on both measures of engagement.     

When Social Accounts Backfire: The Exacerbating Effects of a Polite Message or an Apology on Reactions to an Unfair Outcome1

We examined the effects of ex ante polite or apologetic messages on an individual's responses to a low (unfair) outcome offered in an ultimatum (take‐it‐or‐leave‐it) situation. Results show that these 2 messages (a) increased, rather than decreased, participants' perceptions of unfairness; and (b) decreased, rather than increased, their acceptance of the outcome. Moreover, participants engaged in more punishing behaviors when the outcome was accompanied by either of the messages than when no account was provided. Further analysis revealed that perceived manipulative intent mediated participants' reactions to the polite message and to the apology. These results indicate that if a message seems insincere and manipulative, it can exacerbate an individual's negative reactions to an unfair outcome accompanying the message.     

Comparison of problematic internet and alcohol use and attachment styles among industrial workers in Korea

The objective of this article is to fully understand Internet addiction, we aimed to compare the attachment styles and psychopathologies associated with problematic Internet use with those related to alcohol use. Through the participation of 141 male participants, the present study assessed problematic Internet and alcohol use, attachment, psychopathology, and demographic data via the use of self-rating questionnaires. We explored the significant predictors among avoidant and anxious attachments, depression, anxiety, and phobia to explain problematic Internet and alcohol use. The results showed that anxious attachment, depression, and anxiety could explain problematic alcohol use. In contrast, both anxious and avoidant attachment as well as depression and phobia explained problematic Internet use. Additionally, depression moderated the effects of avoidant attachment on problematic Internet use. We demonstrated that the interaction of attachment and psychopathology predicts problematic Internet use originating from an earlier stage of life than that associated with problematic alcohol use.     

Etiology of obsessions and compulsions: a behavioral-genetic analysis

It is unknown whether various types of obsessive-compulsive (OC) symptoms have a common genetic or environmental etiology. For example, it is unknown whether hoarding is etiologically associated with prototypic OC symptoms, such as washing, checking, and obsessing. Also unknown is whether particular OC-related symptoms are etiologically linked to the general tendency to experience emotional distress (negative emotionality). To investigate these and other issues, a community sample of 307 pairs of monozygotic and dizygotic adult twins provided scores on 6 OC-related symptoms (obsessing, neutralizing, checking, washing, ordering, and hoarding) and 2 markers of negative emotionality (trait anxiety and affective lability). Genetic factors accounted for 40%-56% of variance in the 8 phenotypic scores (M = 49% of variance for OC-related symptoms). Remaining variance was due to nonshared (person-specific) environment. More detailed analyses revealed a complex etiologic architecture, where OC-related symptoms arise from a mix of common and symptom-specific genetic and environmental factors. A general genetic factor was identified, which influenced all symptoms and negative emotionality. An environmental factor was identified that influenced all symptoms but did not influence negative emotionality. Each of the 6 types of symptoms was also shaped by its own set of symptom-specific genetic and environmental factors. The importance of genetic factors did not vary as a function of age or sex, and the architecture of general and specific etiologic factors was replicated for participants having relatively more severe OC symptoms. Gene-environment interactions were identified. Implications for an etiology-based classification system are discussed.     

The diagnosticity of individual data for model selection: Comparing signal-detection models of recognition memory

We tested whether the unequal-variance signal-detection (UVSD) and dual-process signal-detection (DPSD) models of recognition memory mimic the behavior of each other when applied to individual data. Replicating previous results, there was no mimicry for an analysis that fit each individual, summed the goodness-of-fit values over individuals, and compared the two sums (i.e., a single model selection). However, when the models were compared separately for each individual (i.e., multiple model selections), mimicry was substantial. To quantify the diagnosticity of the individual data, we used mimicry to calculate the probability of making a model selection error for each individual. For nondiagnostic data (high model selection error), the results were compatible with equal-variance signal-detection theory. Although neither model was justified in this situation, a forced-choice between the UVSD and DPSD models favored the DPSD model for being less flexible. For diagnostic data (low model selection error), the UVSD model was selected more often.     

The Reliability,Validity, Discriminant and Predictive Properties of the Social Phobia Inventory (SoPhI)

This paper reports on the psychometric properties of the Social Phobic Inventory (SoPhI) a 21-item scale that was designed to measure social anxiety according to the criteria of DSM-IV (American Psychiatric Association, APA (1994) Diagnostic and Statistical Manual of Mental Disorder , 4th Edn., Washington). Factor analysis of the SoPhI using data from a clinical sample of respondents with social phobia revealed one factor which explained approximately 59% of variance and which demonstrated strong internal reliability ( f = 0.93). The SoPhI demonstrated concurrent validity with the SPAI ( r = 0.86) and convergent validity with the Fear of Negative Evaluations-Revised ( r = 0.68). The predictive utility of the scale was demonstrated in a sample of university students classified as extroverted, normal, shy/introverted, and phobic/withdrawn ( m 2 57%). Multivariate Analysis of Variance (MANOVA) revealed that the combined university sample differed from the clinical sample on the summated scores on the SoPhI and that 43% ( m 2 ) of this difference was attributable to group membership. This figure rose to 58% attributable to group membership when these same groups were compared for differences on the 21 individual items. Scores of the SoPhI that are indicative of concern and of possible diagnostic criteria, as well as suggestions for future research, are discussed.