PubMed · 8577440
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
S L Campbell. 1995. Is your safety training program accessible?. https://pubmed.ncbi.nlm.nih.gov/8577440/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
OBJECTIVE: To introduce conjoint analysis (CA) as a method to explain choice decisions of hearing aid users and to measure the contributions of different hearing aid attributes involved. DESIGN: The study was conducted using CA, a method that is well established in marketing, but has not been used for hearing aid research. CA examines the contributions (importance) various attributes make to overall preference judgements. It is based on the premises that objects (i.e., hearing aids) can be described as different combinations of several attributes. The relative importance of the attributes is estimated from integral judgements of hypothetical hearing aids. The advantages of CA are a more realistic presentation of complete products instead of isolated attributes and the consideration of trade-offs between the features. The following attributes selected from 12 features in a prestudy were included in the application: speech perception in quiet, speech perception in noise, handling, sound quality, localization, and feedback. 93 randomly chosen experienced hearing aid wearers participated in the survey. RESULTS: It was found that the attributes concerning speech perception were by far most important. Speech discrimination in quiet and in noise were almost equally significant and contributed with 56% to the preference decisions of the subjects. The remaining attributes showed values in the range of 10% to 12%. When comparing various subgroups dependent on age, sex, hearing loss, satisfaction, etc., significant differences concerning the preferences were found. Elder and female subjects attached greater importance of the attribute "handling" whereas younger patients judged "speech in noise" more important. In general, subjects with greater hearing loss considered speech intelligibility in quiet to be more important than in noisy surroundings. Moreover, sound quality seems to be a significant indicator for satisfaction with the hearing aid. CONCLUSIONS: This study proposes CA as a survey technique to examine individual preferences for hearing aids. Several assumptions about the importance of hearing aid features for different groups of users could be confirmed quantitatively. Segmentation showed valid results depending on socio-demographic and user-specific parameters. The method used and the results are of interest for audiologists as well as the hearing aid industry. They provide valuable tools for future hearing aid design and should be considered in the development of self-assessment inventories.
This brief review article addresses the quality of self-report rating scale outcome measures in relation to audiological rehabilitation with hearing aids. It is intended to assist those who may wish to evaluate, select, or adapt existing self-report measurement tools, or to develop new ones. The focus is not on specific scales but on the key issues in scale development and evaluation. A modern perspective is presented. Areas addressed include measurement goal definition, specification of the target population, the importance of conceptual frameworks, evaluation of reliability, validity and responsiveness, and production of norms. Reliability includes internal consistency and test-retest reliability concepts, related statistical measures such as the standard error of measurement, confidence intervals and critical differences, and some specific numerical criteria. Validity includes construct, content, face and criterion validities. Responsiveness includes some principles in the measurement of change, causes of poor responsiveness, reliability of change measures, and effect size. Concluding remarks touch on the practicality of self-report scales. It is emphasized that measurement goals and target population characteristics must be defined precisely, that existing measures should be evaluated carefully before undertaking new development, that the properties of any measure may depend strongly on its purpose and context of use, and that quantitative statistical criteria should guide the evaluation of measures as well as the design of experiments or clinical trials.
The purpose of this article was to provide information about the importance of outcome measures in the health-care resource allocation scenario. The increasing focus on outcome measures as a more suitable way to demonstrate the value of services is discussed. Health-care trends toward the use of data from patient outcomes to justify treatment needs and reimbursement are described. Important outcomes including patient satisfaction, functional status, and quality of life are presented. Outcome assessment strategies and requirements are considered in the wider context of evidence-based practice, clinical practice guidelines, and performance measures. An outcomes management approach using the World Health Organization's classification system is suggested. Examples of audiological rehabilitation with hearing aids are provided to illustrate the application of outcome measures to hearing health care.