It's all in the name, or is it? The impact of labelling on health state values

Many descriptions of health used in vignettes and condition-specific measures refer to the medical condition. This paper assesses the impact of referring to the medical condition in the descriptions of health states valued by members of the general population. A sample of 241 members of the UK general population each valued 8 health states using time trade-off. All respondents valued essentially the same health states, but for each respondent the descriptions featured either an irritable bowel syndrome label, a cancer label or no label. Regression techniques were used to estimate the impact of each label and experience of the condition on health state values. We find that the inclusion of a cancer label in health state descriptions affects health state values and that the impact is dependent upon the severity of the state. A condition label can affect health state values, but this is dependent upon the specific condition and severity. It is recommended to avoid condition labels in health state descriptions (where possible) to ensure that values are not affected by prior knowledge or preconception of the condition that may distort the health state being valued

The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results

Background: Previous methods of empirical mapping involve using regressions on patient or general population self-report data from datasets involving 2 or more instruments. This approach relies on overlap in the descriptive systems of the measures, but key dimensions may not be present in both measures. Furthermore, this assumes it is appropriate to use different instruments on the same population, which may not be the case for all patient groups. The aim of the study described here is to develop a new method of mapping using general population preferences for hypothetical health states defined by the descriptive systems of different measures. This paper presents a description of the methods used in the study and reports on the results of the valuation study including details about the respondents, feasibility and quality (e.g. response rate, completion and consistency) and descriptive results on VAS and ranking data. The use of these results to estimate mapping functions between instruments will be presented in a companion paper. Methods: The study used interviewer administered versions of ranking and VAS techniques to value 13 health states defined by each of 6 instruments: EQ-5D (generic), SF-6D (generic), HUI2 (generic for children), AQL-5D (asthma specific), OPUS (social care specific), ICECAP (capabilities). Each interview involved 3 ranking and visual analogue scale (VAS) tasks with states from 3 different instruments where each task involves the simultaneous valuation of multiple instruments. The study includes 13 health and well-being states for each instrument (16 for EQ-5D) that reflect a range of health state values according to the published health state values for each instrument and each health state is valued approximately 75-100 times. Results: The sample consists of 499 members of the UK general population with a reasonable spread of background characteristics (response rate=55%). The study achieved a completion rate of 99% for all states included in the rank and rating tasks and 94.8% of respondents have complete VAS responses and 97.2% have complete rank responses. Interviewers reported that it is doubtful for 4.1% of respondents that they understood the tasks, and 29.3% of respondents stated that they found the tasks difficult. The results suggest important differences in the range of mean VAS and mean rank values per state across instruments; for example, mean VAS values for the worst state vary across instruments from 0.075 to 0.324. Respondents are able to change the ordering of states between the rank and VAS tasks and 12.0% of respondents have one or more differences in their rank and VAS orderings for every task. Conclusions: This study has demonstrated the feasibility of simultaneously valuing health states from different preference-based instruments. The preliminary analysis of the results presented here provides the basis for a new method of mapping between measures based on general population preferences

The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results

Background: Previous methods of empirical mapping involve using regressions on patient or general population self-report data from datasets involving two or more instruments. This approach relies on overlap in the descriptive systems of the measures, but key dimensions may not be present in both measures. Furthermore this assumes it is appropriate to use different instruments on the same population, which may not be the case for all patient groups. The aim of the study described here is to develop a new method of mapping using general population preferences for hypothetical health states defined by the descriptive systems of different measures. This paper presents a description of the methods used in the study and reports on the results of the valuation study including details about the respondents, feasibility and quality (e.g. response rate, completion and consistency) and descriptive results on VAS and ranking data. The use of these results to estimate mapping functions between instruments will be presented in a companion paper. Methods: The study used interviewer administered versions of ranking and VAS techniques to value 13 health states defined by each of 6 instruments: EQ-5D (generic), SF-6D (generic), HUI2 (generic for children), AQL-5D (asthma specific), OPUS (social care specific), ICECAP (capabilities). Each interview involved 3 ranking and visual analogue scale (VAS) tasks with states from 3 different instruments where each task involves the simultaneous valuation of multiple instruments. The study includes 13 health and well-being states for each instrument (16 for EQ-5D) that reflect a range of health state values according to the published health state values for each instrument and each health state is valued approximately 75-100 times. Results: The sample consists of 499 members of the UK general population with a reasonable spread of background characteristics (response rate=55%). The study achieved a completion rate of 99% for all states included in the rank and rating tasks and 94.8% of respondents have complete VAS responses and 97.2% have complete rank responses. Interviewers reported that it is doubtful for 4.1% of respondents that they understood the tasks, and 29.3% of respondents stated that they found the tasks difficult. The results suggest important differences in the range of mean VAS and mean rank values per state across instruments, for example mean VAS values for the worst state vary across instruments from 0.075 to 0.324. Respondents are able to change the ordering of states between the rank and VAS tasks and 12.0% of respondents have one or more differences in their rank and VAS orderings for every task. Conclusions: This study has demonstrated the feasibility of simultaneously valuing health states from different preference-based instruments. The preliminary analysis of the results presented here provides the basis for a new method of mapping between measures based on general population preferences.preference-based measures of health; quality of life; mapping; visual analogue scale; ranking

It's all in the name, or is it? The impact of labelling on health state values

Many descriptions of health used in vignettes and condition-specific measures refer to the medical condition. This paper assesses the impact of referring to the medical condition in the descriptions of health states valued by members of the general population. A sample of 241 members of the UK general population each valued 8 health states using time trade-off. All respondents valued essentially the same health states, but for each respondent the descriptions featured either an irritable bowel syndrome label, a cancer label or no label. Regression techniques were used to estimate the impact of each label and experience of the condition on health state values. We find that the inclusion of a cancer label in health state descriptions affects health state values and that the impact is dependent upon the severity of the state. A condition label can affect health state values, but this is dependent upon the specific condition and severity. It is recommended to avoid condition labels in health state descriptions (where possible) to ensure that values are not affected by prior knowledge or preconception of the condition that may distort the health state being valued

Ecological studies on keratinophilic fungi

The seasonal distribution of keratinophilic fungi bas been studied in the soils surrounding an outdoor swimming pool and in soils of summer pens of hedgehogs. The species isolated were conidial and cleistocarpic Arthroderma uncinatum, Trichohyton terrestre, Chrysosorium keratinophilum, Microsporum cookei and Microsporum gypseum. A correlation between some species and. The numbers of hedgehogs in the pens was seen, due to the influence of keratin provided by the quills and scales of the hedgehogs. No such relationship was seen at the swimming pool, although conidial A. uncinatum was seen to decrease when the swimming pool was open to the public in the summer. However, this appears to be the normal seasonal occurrence since a similar pattern of distribution in soils collected from outside the swimming pool was seen. The effects of the addition of fungicides to soil upon the isolation of keratinophilic fungi have been studied, using the hair-baiting technique. The general pattern showed an initial fall in percentage colonisation of baits followed by a fairly rapid recovery to give greater colonisation of greasy baits compared with controls, and a return to the same or less than the control on degreased wool. This contrasts with the normal observation that the majority of keratinophilic fungi grow better on degreased than greasy wool. A study of the keratinophilic flora of soils of different pH values and from coastal regions has been made as ground work for the experimental section. The new intake of students living in halls of residence at Nottingham University was studied in relation to tinea pedis over an academic year. The initial level in October 1972 was 9% by May 1973 it had increased to 24% but returned to 11% in October 1973. In addition to any seasonal influence, there seemed to be a correlation between the sports played by the students and the incidence of tinea pedis. The showers in halls of residence and the University sports centre were thought to be the main points of cross transfer of the infection. In the experimental section, the effects of pH, temperature, fungicides and sea water upon certain keratinophilic fungi have been examined in vitro. Aspects of the nutrition of C. keratinophllum, A. uncinatum and T. terrestre were studied and the most suitable combinations of carbon and nitrogen sources for optimal growth were determined. A study of the competitive saprophytic ability of several dermatophytes was made using various techniques. By use of the fluorescent antibody technique, it was found that A. uncinatum was a good competitive saprophyte in the presence of keratin and can thus be regarded as a true soil inhabitant. Finally, the mating structures of Arthroderma benhamiae, A. tuberculatum, A. uncinatum, Nannizzia cajetani, N. gypsea and N. incurvata were studied using the scanning electron microscope

Locations of marine animals revealed by carbon isotopes

Knowing the distribution of marine animals is central to understanding climatic and other environmental influences on population ecology. This information has proven difficult to gain through capture-based methods biased by capture location. Here we show that marine location can be inferred from animal tissues. As the carbon isotope composition of animal tissues varies with sea surface temperature, marine location can be identified by matching time series of carbon isotopes measured in tissues to sea surface temperature records. Applying this technique to populations of Atlantic salmon (Salmo salar L.) produces isotopically-derived maps of oceanic feeding grounds, consistent with the current understanding of salmon migrations, that additionally reveal geographic segregation in feeding grounds between individual philopatric populations and age-classes. Carbon isotope ratios can be used to identify the location of open ocean feeding grounds for any pelagic animals for which tissue archives and matching records of sea surface temperature are available