Mapping Attitude Formation as a Function of Information Input: Online Processing Models of Attitude Formation

Consistent with calls for a dynamical social psychology (Jacoby et al., 1987; Nowak, Lewenstein, & Vallacher, 1994), attitude formation was studied using a recently developed, computer‐based simulation technique termed Higher Order Cognitive Tracing (see Jacoby et al., 1994). Participants’ attitudes toward 12 different products in 3 product categories were investigated as a function of incremental information input. As opposed to traditional memory‐based models of attitude formation, the study explored online processing models. Results indicate that the impact of information tends to decrease the later in the sequence that information is accessed. In addition, new information that is affectively inconsistent with prior information tends to have a greater impact on attitudes than information that is affectively redundant. This effect is more pronounced earlier rather than later in the sequence of information acquisition. Implications and suggestions for future research are discussed.     

Internet use and social support in women with breast cancer.

Many Web sites offer information to breast cancer patients, who are increasingly using these sites. The authors investigated the potential psychological benefits of Internet use for medical information by breast cancer patients. Of the 251 women approached, 188 were successfully interviewed (74.9%). Forty-two percent used the Internet for medical information related to breast health issues and did so for an average of 0.80 hr per week. The Interpersonal Support Evaluation List and the UCLA Loneliness Scale, with results controlled for covariates, showed that Internet use for breast health issues was associated with greater social support and less loneliness than Internet use for other purposes or nonuse. Breast cancer patients may obtain these psychological benefits with only a minimal weekly time commitment.     

Substance use/abuse as a predictor to illegal and violent behavior: A review of the relevant literature

The preponderance of the research evidence supports the conclusion that abuse of certain types of illicit drugs, separately from the abuse of alcohol, predisposes to subsequent violent behavior. The relationship of cocaine/crack to violent crime has been established more clearly for users of crack in inner city areas than it has for those who are users of other forms of cocaine in the general population.In regard to any race/ethnic or socioeconomic factors in the relationships between substance use/abuse and violent behavior, most clearly established is that a higher proportion of young Black males, compared to other race/ethnic groups, are actively involved in dealing cocaine/crack in some inner city poverty areas.As for gender differences, the research evidence indicates that alcohol abuse as a predictor to and a precipitant of violent behavior, is more clearly established for males than for females. Drug abuse, as distinct from alcohol abuse, has been found to predict subsequent violent behavior, for females as well as for males. “Co-morbidity,” the combination of substance use with and psychopathology, appears more likely to predict for females to later violent behavior. Psychopathology and mental health problems are less likely to predict occurrence of either violent or criminal behavior in the future than are either alcohol abuse or drug abuse.     

From simple associations to the building blocks of language: Modeling meaning in memory with the HAL model

This paper presents a theoretical approach of how simple, episodic associations are transduced into semantic and grammatical categorical knowledge. The approach is implemented in the hyperspace analogue to language (HAL) model of memory, which uses a simple global co-occurrence learning algorithm to encode the context in which words occur. This encoding is the basis for the formation of meaning representations in a high-dimensional context space. Results are presented, and the argument is made that this simple process can ultimately provide the language-comprehension system with semantic and grammatical information required in the comprehension process.     

The effect of corpus size in predicting reaction time in a basic word recognition task: Moving on from Kučera and Francis

Word frequency is one of the strongest determiners of reaction time (RT) in word recognition tasks; it is an important theoretical and methodological variable. The Ku?era and Francis (1967) word frequency count (derived from the 1-million-word Brown corpus) is used by most investigators concerned with the issue of word frequency. Word frequency estimates from the Brown corpus were compared with those from a 131-million-word corpus (the HAL corpus; conversational text gathered from Usenet) in a standard word naming task with 32 subjects. RT was predicted equally well by both corpora for high-frequency words, but the larger corpus provided better predictors for low- and medium-frequency words. Furthermore, the larger corpus provides estimates for 97,261 lexical items; the smaller corpus, for 50,406 items.