Nutrition information on food labels is an important source of nutrition information but is typically underutilized by consumers. This review examined whether consumer nutrition knowledge is important for communication of nutrition information through labels on packaged foods. A cognitive processing model posits that consumers with prior knowledge are more likely to use label information effectively, that is, focus on salient information, understand information, and make healthful decisions based on this information. Consistent with this model, the review found that nutrition knowledge provides support for food label use. However, nutrition knowledge measures varied widely in terms of the dimensions they included and the extensiveness of the assessment. Relatively few studies investigated knowledge effects on the use of ingredient lists and claims, compared to nutrition facts labels. We also found an overreliance on convenience samples relying on younger adults, limiting our understanding of how knowledge supports food label use in later life. Future research should 1) investigate which dimensions, or forms, of nutrition knowledge are most critical to food label use and dietary decision making and 2) determine whether increases in nutrition knowledge can promote great use of nutrition information on food labels.

BackgroundChronic illnesses are significant to individuals and costly to society. When systematically implemented, the well-established and tested Chronic Care Model (CCM) is shown to improve health outcomes for people with chronic conditions. Since the development of the original CCM, tremendous information management, communication, and technology advancements have been established. An opportunity exists to improve the time-honored CCM with clinically efficacious eHealth tools.ObjectiveThe first goal of this paper was to review research on eHealth tools that support self-management of chronic disease using the CCM. The second goal was to present a revised model, the eHealth Enhanced Chronic Care Model (eCCM), to show how eHealth tools can be used to increase efficiency of how patients manage their own chronic illnesses.MethodsUsing Theory Derivation processes, we identified a “parent theory”, the Chronic Care Model, and conducted a thorough review of the literature using CINAHL, Medline, OVID, EMBASE PsychINFO, Science Direct, as well as government reports, industry reports, legislation using search terms “CCM or Chronic Care Model” AND “eHealth” or the specific identified components of eHealth. Additionally, “Chronic Illness Self-management support” AND “Technology” AND several identified eHealth tools were also used as search terms. We then used a review of the literature and specific components of the CCM to create the eCCM.ResultsWe identified 260 papers at the intersection of technology, chronic disease self-management support, the CCM, and eHealth and organized a high-quality subset (n=95) using the components of CCM, self-management support, delivery system design, clinical decision support, and clinical information systems. In general, results showed that eHealth tools make important contributions to chronic care and the CCM but that the model requires modification in several key areas. Specifically, (1) eHealth education is critical for self-care, (2) eHealth support needs to be placed within the context of community and enhanced with the benefits of the eCommunity or virtual communities, and (3) a complete feedback loop is needed to assure productive technology-based interactions between the patient and provider.ConclusionsThe revised model, eCCM, offers insight into the role of eHealth tools in self-management support for people with chronic conditions. Additional research and testing of the eCCM are the logical next steps.

Young and older adults read a series of passages of 3 different genres for an immediate assessment of text memory (measured by recall and true/false questions). Word-by-word reading times were measured and decomposed into components reflecting resource allocation to particular linguistic processes using regression. Allocation to word and textbase processes showed some consistency across the 3 text types and was predictive of memory performance. Older adults allocated more time to word and textbase processes than the young adults did but showed enhanced contextual facilitation. Structural equation modeling showed that greater resource allocation to word processes was required among readers with relatively low working memory spans and poorer verbal ability and that greater resource allocation to textbase processes was engendered by higher verbal ability. Results are discussed in terms of a model of self-regulated language processing suggesting that older readers may compensate for processing deficiencies through greater reliance on discourse context and on increases in resource allocation that are enabled through growth in crystallized ability.

This paper introduces an adult developmental model of self-regulated language processing (SRLP), in which the allocation policy with which a reader engages text is driven by declines in processing capacity, growth in knowledge-based processes, and age-related shifts in reading goals. Evidence is presented to show that the individual reader's allocation policy is consistent across time and across different types of text, can serve a compensatory function in relation to abilities, and is predictive of subsequent memory performance. As such, it is an important facet of language understanding and learning from text through the adult life span.

Anxiety disorders are estimated to affect 26.9 million individuals in the United States at some point during their lives. This study used the human capital approach to estimate the direct and indirect costs of these highly prevalent disorders. In 1990, costs associated with anxiety disorders were $46.6 billion, 31.5% of total expenditures for mental illness. Less than one‐quarter of costs associated with anxiety disorders were for direct medical treatment; over three‐quarters were attributable to lost or reduced productivity. Most of these indirect costs were associated with morbidity, as mortality accounted for just 2.7% of the total. Greater availability of effective, relatively low‐cost outpatient treatment could substantially reduce the economic and social burden of these common and often crippling disorders. Anxiety 2:167–172 (1996). © 1996 Wiley‐Liss, Inc.

The prevention of major depression is an important research goal which deserves increased attention. Depressive symptoms and disorders are particularly common in primary care patients and have a negative impact on functioning and well-being comparable with other major chronic medical conditions. The San Francisco Depression Prevention Research project conducted a randomized, controlled, prevention trial to demonstrate the feasibility of implementing such research in a public sector setting serving low-income, predominantly minority individuals: 150 primary care patients free from depression or other major mental disorders were randomized to an experimental cognitive-behavioral intervention or to a control condition. The experimental intervention group reported a significantly greater reduction in depressive levels. Decline in depressive levels was significantly mediated by decline in the frequency of negative conditions. Group differences in the number of new episodes (incidence) of major depression did not reach significance during the 1-year trial. We conclude that depression prevention trials in public sector primary care settings are feasible, and that depressive symptoms can be reduced even in low-income, minority populations. To conduct randomized prevention trials that can test effects on incidence with sufficient statistical power, subgroups at greater imminent risk have to be identified.

Background Mental disorders impose a multi-billion dollar burden on the economy each year; translating the burden into economic terms is important to facilitate formulating policies about the use of resources.Method For direct costs, data were obtained from national household interview and provider surveys; for morbidity costs, a timing model was used that measures the lifetime effect on current income of individuals with mental disorders, taking into account the timing of onset and the duration of these disorders, based on regression analysis of Epidemiologic Catchment Area study data.Results The total economic costs of mental disorders amounted to US$ 147.8 billion in 1990. Anxiety disorders are the most costly, amounting to $46.6 billion, or 31.5% of the total; schizophrenic disorders accounted for $32.5 billion, affective disorders for $30.4 billion, and other mental disorders for $38.4 billion.Conclusions Mental illnesses, especially anxiety disorders, are costly to society. Although anxiety disorders have a higher prevalence than affective disorders and schizophrenia, use of medical care services is lowest for anxiety disorders. Anxiety disorders appear to be under-recognised and untreated even though treatment interventions have been shown to be effective and can be delivered in a cost-efficient manner.

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