Biomedical subjects

R Shellenberger

Publications and source records attributed to R Shellenberger.

4 recordsLinked to original sources

PubMed1996

A guide for planning community-oriented health care: the health sector resource allocation model.

The objective of this study was to demonstrate the value of a planning model for the design and evaluation of community health services. The health status of Washtenaw County, Michigan was modeled. Data were obtained from the Michigan Department of Public Health, Medstat Systems, and the medical literature for 32 diseases or conditions, representing approximately 85% of causes of death and 56% of medical payments (excluding medication costs). An expanded life-table approach was used for 16 age-and sex-matched cohorts exposed to a disease attack rate, access-to-care rate, case fatality rate, morbidity, and costs. Rates can be modified to reflect changes due to treatment, secular trends, or prevention programs. Two alternative delivery methods were considered to show the potential impact of reducing cardiovascular deaths (worksite initiative), or increasing utilization of services (lay health promotion) on county health status and costs over time. Deaths, bed days, and annual medical payments were the main outcome measurements. Cardiovascular and cancer conditions are and will be the primary causes of death in this population. The most important causes of bed days are musculoskeletal conditions, chronic obstructive pulmonary disease, accidents, strokes, and depression. The major health-care payments are for angina pectoris and/or other cardiac conditions, musculoskeletal conditions, accidents, prenatal care, and/or childbirth, and depression. The two alternative scenarios illustrate how reductions in mortality are not necessarily equated with similar improvements in morbidity or costs. This model presents an overview of the current and projected health status of a community. With such a planning tool, a community can better understand the impact of potential prevention or intervention programs, and help design its health-care system within the constraints of available resources.

Cause of Death↗

PubMed1996

The healing energy of love.

That love promotes health surprises few people, yet the scientific study of love and physical health is in its infancy. Because love has many facets and is manifested in many ways, as described here, it was banned from Western science, which insisted on observable and simple independent variables. This article presents data indicating the salutary effects of love on physical health. These data are from several areas-psychology, sociology, medicine, epidemiology, and healing-and together form a foundation for understanding and enhancing love and its effects. Three processes are formulated to explain the health-promoting effects of love: psychophysiologic, psychophysical, and psychosocial/behavioral. Love is described as an energy by virtue of its capacity to produce effects.

Humans↗

PubMed1989

An epidemiologic investigation of forced expiratory volume at 1 second and respiratory symptoms among employees of a toluene diisocyanate production plant.

Pulmonary function tests were done and compared to current and past potential exposure levels of toluene diisocyanate (TDI) for 57 TDI manufacturing workers and 89 workers not exposed to TDI or other known respiratory hazards. The average TDI plant experience was 4.1 years (standard deviation = 2.8). Routine industrial hygiene measurements have shown TDI exposure below a time-weighted average of 0.005 parts per million and a short-term exposure level of 0.02 parts per million. A certified industrial hygienist ranked department and job classification by level of potential exposure to TDI (none, low, moderate, and high). A questionnaire was administered to determine the prevalence of respiratory symptoms and smoking habits. Using backward regression analysis, cumulative pack-years of cigarette smoking and prevalence of lower respiratory symptoms were statistically significant predictors of a standardized forced expiratory volume at 1 second observed v expected difference; however, TDI exposure, whether classified as current, highest career level, cumulative, or cumulative highest-to-date, was not associated with a decline in forced expiratory volume.

Adult↗

PubMed1987

Specific effects and biofeedback versus biofeedback-assisted self-regulation training.

In any field, clear and logical conceptualizations are the basis of accurate models----correct research design----correct results----correct conclusions----advancement in the field. Faulty conceptualizations----faulty models----faulty research design----faulty results----faulty conclusions----confusion. In analyzing the conceptualizations of "biofeedback" as expressed by John Furedy (1987) in, "Specific versus Placebo Effects in Biofeedback Training: A Critical Lay Perspective," we focus on two issues: Does biofeedback have a treatment effect? Is biofeedback necessary for the training effect? In discussing issue (1) we describe the multiple meanings of "biofeedback" and raise the fundamental question: Is biofeedback a treatment? We argue that faulty conceptualizations of clinical biofeedback (1) assume that the treatment in clinical biofeedback is "biofeedback" with specific effects, (2) assume that the scientific basis of biofeedback is dependent upon demonstrations of these specific effects through double-blind design that distinguish "specific" from "placebo effects," and (3) trivialize clinical research by attempting to determine the usefulness of biofeedback information--usefulness that is already understood logically by professionals and consumers and demonstrated by clinical studies in the laboratory and in the clinic. We further argue that accurate conceptualizations of clinical biofeedback (1) identify self-regulation skills as the treatment with specific effects of physiological change and symptom reduction, and (2) describe the use of information from biofeedback instruments as scientific verification of self-regulation skills. Finally, the scientific basis of clinical biofeedback is based on (1) evidence from experimental and clinical control studies that have demonstrated the effectiveness of self-regulation skills for symptom alleviation, and (2) the use of biofeedback instruments to verify the acquisition of self-regulatory skills, thus fulfilling the scientific dictum of verifiability.

Biofeedback, Psychology↗