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In recent years increased attention has been directed to prevention research as a means of solving the multitude of complex social and health problems which confront individuals and their societies. Abuse of substances, behavioral dysfunctions, violence, emotional disorders, educational failures, unwanted pregnancies and sexually transmitted diseases are but a few examples of these most difficult problems.

Not a MyNAP member yet? Register for a free account to start saving and receiving special member only perks. Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Ultimately, such research should be able to demonstrate that there is a causal relation- ship between an educational intervention and immediate or long-term changes that occur in development, behavior, social relationships, and normative life circumstances. A primary goal of early intervention re- search is to determine the types of practices that are most effective for children with specific characteristics Guralnick,

Collection Book Methodological Issues and Strategies in Clinical Research

Not a MyNAP member yet? Register for a free account to start saving and receiving special member only perks. E nd-of-life researchers and others working more broadly with large datasets have identified several methodological issues that require consideration as we look at the use of existing datasets to better understand quality of life and care at the end of life.

Small sample sizes are always an obstacle, particularly when using nationally collected health data that are not focused on people who are dying. For adults, with sufficient accumulation of years of data, large enough samples can be assembled for many kinds of analysis of topics related to dying. For children and young adults, however, that is not the case; there have been no studies to date that have focused closely enough on younger people to provide any useful aggregate information about those approaching the end of life.

This chapter describes the most pervasive methodologic issues that make end-of-life research difficult. Some of these issues are specific to research on the dying, but many also apply to other areas of health research. Both the specific and the general are included in this chapter, as they apply to research on death and dying. The various conceptual models described in Chapter 2 of this report which use the original terms, as reported by authors begin to suggest the variety of language used.

The relatively small community of researchers working in this field do interact closely, but should be encouraged to begin converging on a set of defined terms that can then be used in surveys and other types of research to improve comparability among data sets. Obtaining information from varying perspectives. Gathering data in a systematic way that captures the perspectives of patients, their loved ones, and health providers is challenging, though—and at present, it is basically not done.

Coping with variations in the quality of existing data. A second challenge is dealing with the variation in quality—i. Information about quality of life and quality of care at the end of life is important to clinicians and to researchers, to individuals and organizations interested in internal quality improvement efforts, and to agencies concerned with external inspections.

As this field of inquiry grows and develops, there will be variations in the precision of the data collection and in acceptable standards for reliability and validity.

Clearly, some early pilot studies will have to use tools that are not validated, but one aim of that type of research will be to learn about the tools and determine whether they can be used widely.

Similarly, as we look to large datasets for information, we must weigh the advantages of developing a portrait using the relatively crude tools that exist, with the risk of being misled by the use of data originally designed for a wholly different purpose. Coping with the difficulties in collecting data from dying people and their loved ones. A third important challenge is coping with the difficulties of collecting data from dying people and their loved ones.

People who are sick enough to die or struggling to cope with the physical and emotional challenges of caring for a dying loved one are much less likely to be able to respond to surveys or interviews than are people without those burdens.

Investigators estimate that one in three dying persons is unable to be interviewed close to death because of somnolence, other cognitive deficits, asthenia, or other medical reasons Teno et al. Consequently, missing data and the proportion of proxy responses will present significant challenges to those analyzing these data.

Characterizing the quality of end-of-life care. Yet another challenge is characterizing the quality of end-of-life care. Describing quality involves capturing overuse of medical resources and well as underuse, in addition to documenting poor skills and performance on the part of health care providers Donaldson and Field, Judgments in these areas are value laden and must be made with careful consideration of the current evidence base.

Nonetheless, research suggests that expert panels can adequately identify the appropriateness and quality of care Brook et al. Assessing continuity and coordination of care is also important to quality, but, again, methods to do this are very limited at this time.

The changing face of death in this country requires an acknowledgment of the chronic nature of eventually fatal illnesses—such as congestive heart failure and end-stage renal disease—as well as a better understanding of the trajectory of dying from complications associated with dementia and frailty in old age Lunney et al.

This suggests that initial information gathering be done tentatively, with a wide net that can be progressively narrowed, as we begin to better understand these various pathways to death. There are several methodological issues associated with the use of large datasets created for purposes other than end-of-life research.

These generally stem from the methods and sampling strategies used to collect the data for these datasets. Design and scope of the original study. If an existing dataset is the result of a specific survey, the usefulness of the data for research on the quality of life and care at the end of life will depend in part on the design and scope of the original study.

Information from cross-sectional health surveys of the general population may enhance our understanding. The National Health Interview Survey, for example, collects information from 30, respondents each year. Matching information from this survey to the National Death Index has yielded 54, decedents over the period between and Schoeni, , allowing very detailed analyses. However, very few surveys are conducted on such a scale. Data from longitudinal panel studies of the elderly or of others at high risk of death are also valuable, provided that the measurement interval is short and likely to result in data collected close to death.

Sampling strategies. Another important methodological issue in using existing datasets to study quality of life and care at the end of life that warrants attention is the sampling strategies that were used to collect data.

Large surveys based on household sampling strategies will have limited value for end-of-life study, because findings cannot be generalized to institutionalized populations and may not fully represent the aging population. List-based sampling strategies, such as the use of Medicare beneficiary roles, better tap these key populations, but they also result in data that cannot be generalized to the full spectrum of the terminally ill population.

Unit of analysis. Careful consideration needs to be given to the unit of analysis of existing datasets. Institutional-level data that includes information on individual clients could be an important source of information for end-of-life research.

Pooling data from multiple institutions, however, requires careful consideration of the original sampling strategies and timing of data collection. Several aspects of survey methods are particularly troublesome for the purpose of studying individuals who are elderly or sick enough to die.

Variation in responses among people in different age groups. Various age groups are known to derive different meaning from the same question, and elderly people are less comfortable than younger people with questions that require drawing comparisons or psychological self-description Herzog and Rodgers, Elderly respondents also have difficulty making time tradeoff or utility judgments and completing visual analog scales.

Furthermore, age, cognitive ability, and health status. Reliability and validity of administrative data. The reliability and validity of administrative data is an additional concern. Furthermore, information about comorbidity is seriously underreported Green and Wintfeld, ; Iezzoni et al. Use of proxy respondents. The use of proxy respondents warrants special attention because of the critical role they play in collecting information about people who are cognitively impaired or too sick to be studied directly, because proxy respondents represent the key source of information after a death has occurred.

It is important to understand that these proxies are very likely to have been affected by the decedents dying process and death. They may be asked to report both on their own distress as well as provide information about the decedent. Despite this caution, in general, studies report fairly good agreement between subjects and proxies in many types of assessments.

A recent review of clinical studies comparing proxy data with other sources of information for adults Neumann et al. Spouses, children, or other close family members tend to be capable proxies, although proxy reports may be influenced by caregiving burden.

Proxy and subject reports are often comparable in describing levels of functioning, although proxies tend to identify more impairment. Proxies and subjects generally agree on overall health, chronic physical conditions, and physical symptoms. Relatively little is known about the comparability of proxy reports regarding health care utilization.

There is low to moderate agreement between proxies and subjects regarding depressive symptoms and psychological well-being, with proxies describing more problems.

Proxies are often in agreement with subjects on reports of cognitive status, although proxies may overestimate cognitive abilities. Variation in agreement between subjects and proxies. Variation limits the validity of some data and hampers the comparison of large datasets that contain differing proportions of proxy responses.

When possible, it is important to adjust for proxy responses with the develop. Difficulties in measuring complex variables. The measurement of complex variables inevitably introduces another difficult issue— sources of measurement variation among surveys and within rounds of the same survey. First, there are multiple accepted ways of measuring function, including 1 questionnaires or observations of activities of daily living ADLs or instrumental activities of daily living IADLs ; 2 questions about physical activity, exercise, or recreation; 3 questions about mobility, range of motion, strength, and endurance; and 4 clinically administered performance batteries.

Within just one approach—self-administered questionnaires concerning ADLs—seemingly minor differences in the structure and wording of a questionnaire result in major differences in prevalence estimates of disability Freedman and Martin, ; Picavet and van den Bos, ; Wiener et al. Many of the dimensions of quality at the end of life are equally complex and prone to measurement variation. Approaches to handling incomplete data. Handling incomplete data is challenging because variables are likely to be missing for specific reasons, and their absence may bias overall results.

Those most in pain or most disabled are perhaps the least likely to provide data points near the end of life. Careful consideration should be given to techniques to reduce non-response biases Lemke and Drube, Approaches to describing health and functional status. Describing the health and functional status of people sick enough to die is especially difficult because of the complexity of the conditions that interact to produce a given state and then change at individually varying rates over time.

Multivariate statistical approaches are essential, but even then, careful consideration should be given to capturing individual heterogeneity within complex health states Manton and Woolson, This observation implies that subjective, narrative i. Approaches to operationalizing longevity. Operationalizing longevity has been approached in various ways. The majority of studies take. Addressing the interaction between length of life and outcomes of care.

The interaction of length of life and outcomes of care raises another thorny problem. Consequently, care strategies that prolong survival—which themselves may be considered poor outcomes if they only prolong the dying process—may appear to produce poorer outcomes because of the larger numbers of subjects who then fall within this prolonged stage of worsening outcomes.

On the other hand, strategies that appear to improve valued outcomes may do so only by shortening lifespan, thus compressing the period of observation during which these negative outcomes tend to be observed.

The idea of linking records, created for different purposes, and possibly at different times and places, of a single individual, is not new. A recent report of the U. General Accounting Office GAO, cites a paper from the s that discusses linking data from different sources through matching names. Since that time, it has become increasingly clear that linking data sources can create information not available from single sources, and has the potential to reduce both the costs of data collection and the burden on respondents.

Multiple HHS data collection efforts are now linked analytically through the use of common core questionnaires, common sampling frames, and common definitions and terms. This results in an overall reduction in the burden imposed on survey respondents, increases the efficiencies of data collection, and vastly improves the analytic capabilities of HHS surveys HHS, In this report, the value of data linkage is recognized, but the issues related to it are, as well.

Methodological issues & strategies in clinical research

Not a MyNAP member yet? Register for a free account to start saving and receiving special member only perks. E nd-of-life researchers and others working more broadly with large datasets have identified several methodological issues that require consideration as we look at the use of existing datasets to better understand quality of life and care at the end of life. Small sample sizes are always an obstacle, particularly when using nationally collected health data that are not focused on people who are dying. For adults, with sufficient accumulation of years of data, large enough samples can be assembled for many kinds of analysis of topics related to dying. For children and young adults, however, that is not the case; there have been no studies to date that have focused closely enough on younger people to provide any useful aggregate information about those approaching the end of life.


Beginning the Research Process The book is entirely about psychological research, a very welcome compilation and no doubt a great comfort to psychological.


Methodological issues in prevention research: An introduction to the special issue

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Methodological Issues and Strategies in Clinical Research, Third Edition

Its three prior editions have long served as 'one-stop shopping' resources for advanced undergraduates, graduate students, and faculty members hoping to consult the best articles bearing on methodological issues and advances in clinical science Its fourth edition, released this year, maintains and builds on the same standard of scholarly excellence that previous readers of MISCR have come to expect. Alan E. He is the John M. At Yale, Dr. Du kanske gillar.

Oxford University Press makes no representation, express or implied, that the drug dosages in this book are correct. Readers must therefore always check the product information and clinical procedures with the most up to date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulations. The authors and the publishers do not accept responsibility or legal liability for any errors in the text or for the misuse or misapplication of material in this work.

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