In recent studies of the structure of affect, positive and negative affect have consistently emerged as two dominant and relatively independent dimensions. A number of mood scales have been created to measure these factors; however, many existing measures are inadequate, showing low reliability or poor convergent or discriminant validity. To fill the need for reliable and valid Positive Affect and Negative Affect scales that are also brief and easy to administer, we developed two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS). The scales are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period. Normative data and factorial and external evidence of convergent and discriminant validity for the scales are also presented.

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Development and validation of brief measures of positive and negative affect: The PANAS scales.

XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

Introduction 1. Woman's Place in Man's Life Cycle 2. Images of Relationship 3. Concepts of Self and Morality 4. Crisis and Transition 5. Women's Rights and Women's Judgment 6. Visions of Maturity References Index of Study Participants General Index

In a Different Voice. Psychological Theory and Women’s Development. Cambridge, MA (Harvard University Press) 1982.

Attachment--and loss.

Background 
The quality and quantity of individuals' social relationships has been linked not only to mental health but also to both morbidity and mortality.
Objectives 
This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk.
Data Extraction 
Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships.
Results 
Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44).
Conclusions 
The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality.

Please see later in the article for the Editors' Summary

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Social Relationships and Mortality Risk: A Meta-analytic Review

Old Age Mortality in Japan

The purpose of this study is empirically evaluate a coping response that is thought to be unique among older Catholics - suffering in silence. Two hypotheses are examined. The first predicts that older Catholics will be more likely than older Protestants to suffer in silence when ongoing economic difficulty is encountered. The second hypothesis specifies that the potentially deleterious effects of financial problems on depressive symptoms will be offset for older adults who prefer to suffer in silence. Data from an ongoing nationwide survey of older people in the United States provide support for both hypotheses.

Assessing coping responses within specific faith traditions: suffering in silence, stress, and depressive symptoms among older Catholics

W E appreciate the comments by Mendes de Leon (2007) regarding the challenges involved in using multilevel models to analyze aging effects in samples of older adults that combine multiple birth cohorts. The core argument in the latter portion of his commentary focuses on the advantages of using continuous, rather than categorical, outcome variables when analyzing aging-related change. We are in complete agreement with Mendes de Leon on this point. In Part 1 of his commentary, Mendes de Leon expresses concern over our approach of modeling change by age at the time of each interview as opposed to time since baseline (see Shaw, Krause, Liang, & Bennett, 2007). His major concern is that our age-based approach fails to fully distinguish between cross-sectional age differences and longitudinal changes in a variable of interest. He indicates that failing to distinguish between these two effects could result in estimates of aging effects that are biased, due either to birth cohort effects or the ‘‘healthy participation effect.’’ We wish to convey our view that using a time-based approach is not the only means for addressing this concern. First, crosssectional age differences can be controlled for in age-based models just as they are in time-based models. As we noted in our article, we did this by including dummy variables for 10-year birth cohorts (corresponding to baseline ages of 85 and older, 75–84, and 65–74) into our between-persons (Level 2) models. We should note that including measures of birth cohorts in our models should have controlled for both the cohort effect and the healthy participation effect referred to by Mendes de Leon. That is, in addition to accounting for differences in social relations between cohorts observed at the same point in time (i.e., a cohort effect), including measures of birth cohorts should also have accounted for differences in social relations between individuals who were the same age at different points in time (e.g., individuals who were 75 years old at baseline vs individuals who were 65 years old at baseline and 75 years old at follow-up) as is proposed by the healthy participation effect. Nevertheless, some may raise concerns about the coarseness of our cohort definitions relative to a continuous age variable. For example, Mendes de Leon suggests that our measures of birth cohorts might be inadequate controls for the healthy participation effect because ‘‘a healthy participation effect may not manifest itself in discrete 10-year age intervals’’ (p. S199). Although this may be true, it is not an issue of age-based versus time-based models. In fact, in a set of supplementary (unpublished) analyses we estimated our age-based models using a continuous measure of baseline age rather than the cohort dummy variables. The results regarding aging effects were quite similar. With controls for baseline age (measured either as dummy cohort variables or as a continuous variable) in place, we feel that the choice of time versus age as the time scale should not have major substantive implications. Time and age are perfectly colinear, with equal increments. The main difference is that time effects from time-based models estimate change over a common period of time for each individual (e.g., from Year 0 to Year 10), whereas age effects from age-based models estimate change over the entire course of later adulthood (e.g., from age 65 to age 100). We acknowledge that spreading the aging effects across the entire age range resulted in trajectories that probably did not fully distinguish between aging and cohort effects, even after we included measures of birth cohorts in our models. However, because our major objective was to examine changes in social relations across this entire age range and not just over a certain 10-year period, we feel that this is a limitation we can live with. This is especially true given that our data showed only modest differences in the results when we compared age-based and time-based approaches. We have done our best to describe these differences for readers as clearly as possible and have also noted the potential limitations of our age-based approach. At this time, we should also note that, to the best of our knowledge, the extent of any healthy participation effect in longitudinal data is not well established. Although we believe that it is reasonable to assume that the average 75-year-old who enters a study at baseline is relatively healthy (otherwise this individual would not have participated in the first place), it is also reasonable to assume that the average person who turns 75 years old during follow-up is relatively healthy as well (otherwise this individual would have dropped out). Thus, it is not clear how influential the healthy participant effect really is. We surmise that the extent to which aging effects are influenced by healthy participation effects probably has more to do with the outcome studied and the length of follow-up than the particular indicator of the passage of time used. Journal of Gerontology: SOCIAL SCIENCES Copyright 2007 by The Gerontological Society of America 2007, Vol. 62B, No. 3, S203–S204

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Age Versus Time Since Baseline as the Time Scale in the Analysis of Change

The purpose of this article is to examine the relationship between self-esteem and psychological distress in later life. The majority of researchers who have assessed this relationship assume that ...

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Self-Esteem and Psychological Distress in Later Life:

Positive health outcomes are related to adults’ religious congregational participation. For parents of children with chronic disease, structured daily care routines and/or strict infection control precautions may limit participation. For this exploratory study, we examined the relationship between congregational support and religious coping by parents of children with cystic fibrosis (CF) compared to parents for whom child health issues were not significant stressors. CF parents reported higher levels of emotional support from congregation members and use of religious coping. Within-group differences were found for CF parents by denominational affiliation. Congregational support for parents dealing with child chronic disease is important.

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Neal Krause

Papers

Old Age Mortality in Japan

Assessing coping responses within specific faith traditions: suffering in silence, stress, and depressive symptoms among older Catholics

Age Versus Time Since Baseline as the Time Scale in the Analysis of Change

Self-Esteem and Psychological Distress in Later Life:

Increased congregational support for parents of children with cystic fibrosis.