Representing space: the development, content and accuracy of mental representations by the blind and visually impaired

This thesis reports on two studies on the perception and cognition of space by individuals who are blind and visually impaired. Research was conducted with students from Dorton College at the Royal London Society for the Blind (RLSB) in Kent. The first experiment examined the content and accuracy of mental representations of a well-known environment. Students walked a route around the RLSB campus and learned the position of ten buildings and structures. They were then asked to make pointing judgments, estimate distances and complete a spatial cued model of the campus. The second experiment considered the wayflnding strategies and spatial coding heuristics used to explore a complex novel environment. Students were asked to explore a maze and learn the position of six different locations. Their search patterns were recorded and analyzed using Geographic Information Systems (GIS) software. Students were tested using the same methods as in the previous experiment and their performance was related to the type and frequency of strategies used during exploration. Results were complemented with a mobility questionnaire, a low vision quality of life questionnaire and data from a literacy and numeracy assessment as well as ethnographic material collected by the author during the two years spent working and living at the RLSB. The thesis begins with a discussion of disability and society framed within the context of geography, urban planning and design. The concepts of blindness and visual impairment are then examined with particular attention given to the psychosocial implications of visual loss. This is followed by a discussion of growth and development, and in-depth review of research on the development, content and accuracy of mental representations by the blind and visually impaired. Finally, the methods used to collect and analyse data for both experiments are considered in light of individual differences and the inadequacy of some statistical techniques to account for the heterogeneous nature of visual impairment. Results from the first experiment revealed significant differences in the accuracy and content of mental representation between the sighted, visually impaired and blind groups for the pointing and model construction tasks. Performance in the distance estimation task was similar across groups. Large individual differences were identified, with the performance of individuals in the same group varying according to the type and requirement of the task. Results from the second experiment also revealed significant differences between the different groups, this time for all three tasks. Here again, large individual differences were found within each group. An analysis of distortions revealed that despite a disparity in accuracy, the blind and visually impaired shared many of the systematic distortions typically found in the mental representation of sighted individuals further confirming their ability develop functional mental representations of space. Performance in the pointing, distance estimation and model construction tasks were also related to the type and frequency of strategies used to explore the maze with the best performers using a combination of egocentric and allocentric strategies. In general, results from the two experiments support the amodal notion that the construction of accurate mental representations of space is not limited to any particular sensory modality but facilitated by the visual system. It also emphasizes the need for mutually supportive techniques that incorporate both quantitative and qualitative methods in the collection and analysis of cognitive data

Variation in the Frequency and Extent of Hybridization between <i>Leucosceptrum japonicum</i> and <i>L</i>. <i>stellipilum</i> (Lamiaceae) in the Central Japanese Mainland

<div><p>Variations in the frequency and extent of hybridization among mixed populations located in the same contact zone provide natural laboratories for the study of extrinsic reproductive isolation maintaining species integrity. In this study, we examined the pattern of hybridization between <i>L</i>. <i>japonicum</i> and <i>L</i>. <i>stellipilum</i> among mixed populations in different localities of a contact zone. The genetic structures from three sympatric populations and six mixed populations in the hybrid zone, and five reference populations far from the contact zone, were characterized using 10 neutral nuclear microsatellite markers. Evidence from genetic distance-based clustering analysis, the frequency distribution of admixture proportion values, and the hybrid category assignment approaches indicated that the frequency and extent of hybridization varied considerably among populations in the contact zone between <i>L</i>. <i>japonicum</i> and <i>L</i>. <i>stellipilum</i>. One likely explanation is that variation in exogenous (ecological) selection among populations might contribute to differences in frequency and extent of hybridization. The present study will facilitate future research exploring the evolution of reproductive isolation between <i>L</i>. <i>japonicum</i> and <i>L</i>. <i>stellipilum</i>.</p></div

Microsatellite dataset for Leucosceptrum

Microsatellite dataset (10 markers) given here as a Genepop input file. The file contains data from 313 individuals sampled from three sympatric populations and six mixed populations in a hybrid zone between Leucosceptrum japonicum and L. stellipilum, and five reference populations far from the hybrid zone

Are AMI Patients with Comorbid Mental Illness More Likely to be Admitted to Hospitals with Lower Quality of AMI Care?

<div><p>Objective</p><p>Older patients with comorbid mental illness are shown to receive less appropriate care for their medical conditions. This study analyzed Medicare patients hospitalized for acute myocardial infarction (AMI) and determined whether those with comorbid mental illness were more likely to present to hospitals with lower quality of AMI care.</p> <p>Methods</p><p>Retrospective analyses of Medicare claims in 2008. Hospital quality was measured using the five “Hospital Compare” process indicators (aspirin at admission/discharge, beta-blocker at admission/discharge, and angiotension-converting enzyme inhibitor or angiotension receptor blocker for left ventricular dysfunction). Multinomial logit model determined the association of mental illness with admission to low-quality hospitals (rank of the composite process score <10^th percentile) or high-quality hospitals (rank>90^th percentile), compared to admissions to other hospitals with medium quality. Multivariate analyses further determined the effects of hospital type and mental diagnosis on outcomes.</p> <p>Results</p><p>Among all AMI admissions to 2,845 hospitals, 41,044 out of 287,881 patients were diagnosed with mental illness. Mental illness predicted a higher likelihood of admission to low-quality hospitals (unadjusted rate 2.9% vs. 2.0%; adjusted odds ratio [OR]1.25, 95% confidence interval [CI] 1.17–1.34, p<0.01), and an equal likelihood to high-quality hospitals (unadjusted rate 9.8% vs. 10.3%; adjusted OR 0.97, 95% CI 0.93–1.01, p = 0.11). Both lower hospital quality and mental diagnosis predicted higher rates of 30-day readmission, 30-day mortality, and 1-year mortality.</p> <p>Conclusions</p><p>Among Medicare myocardial infarction patients, comorbid mental illness was associated with an increased risk for admission to lower-quality hospitals. Both lower hospital quality and mental illness predicted worse post-AMI outcomes.</p> </div

Characteristics of Medicare AMI patients, by mental illness.

<p>AMI = acute myocardial infarction; SD = standard deviation.</p>*<p>P<0.01 for comparisons across mental illness groups based on χ² tests or analyses of variance.</p

The number of <i>L</i>. <i>japonicum</i> (LJ), <i>L</i>. <i>stellipilum</i> (LS), F1, F2, advanced-generation hybrids (F_n), first generation backcross to <i>L</i>. <i>japonicum</i> (BC1J), first generation backcross to <i>L</i>. <i>stellipilum</i> (BC1S), later generation backcross to <i>L</i>. <i>japonicum</i> genotypes (BCJ), later generation backcross to <i>L</i>. <i>stellipilum</i> (BCS) genotypes.

<p>The number of <i>L</i>. <i>japonicum</i> (LJ), <i>L</i>. <i>stellipilum</i> (LS), F1, F2, advanced-generation hybrids (F_n), first generation backcross to <i>L</i>. <i>japonicum</i> (BC1J), first generation backcross to <i>L</i>. <i>stellipilum</i> (BC1S), later generation backcross to <i>L</i>. <i>japonicum</i> genotypes (BCJ), later generation backcross to <i>L</i>. <i>stellipilum</i> (BCS) genotypes.</p

Admission to hospitals with low and high composite quality scores by Medicare acute myocardial infarction patients.

*<p>Defined as hospitals in the bottom (low quality) or top (high quality) 10% rankings of the composite quality score.</p>**<p>Multivariate multinomial logistic models adjusted for patient age, gender, race, median household income, high school graduation rate, tobacco use, distances to the admitting hospital and to the nearest hospital, and individual medical comorbidities (congestive heart failure, cardiac arrhythmias, valvular disease, pulmonary circulation disorders, peripheral vascular disorders, hypertension, paralysis, other neurological disorders, chronic pulmonary disease, diabetes, hypothyroidism, renal failure, liver disease, peptic ulcer disease excluding bleeding, lymphoma, metastatic cancer, solid tumor without metastasis, rheumatoid arthritis, coagulopathy, obesity, weight loss, fluid and electrolyte disorders, blood loss anemia, and deficiency anemia).</p

Genetic variation in pure <i>L</i>. <i>japonicum</i> populations, pure <i>L</i>. <i>stellipilum</i> populations, sympatric <i>L</i>. <i>japonicum</i>, sympatric <i>L</i>. <i>stellipilum</i>, and putative hybrids.

<p>(a) Admixture analyses showing the proportion of the genome of each individual originating from <i>L</i>. <i>japonicum</i> or <i>L</i>. <i>stellipilum</i> using the program STRUCTURE. Each individual is represented as a vertical bar divided into two segments representing the proportion of the genome from each of the genetic groups of <i>L</i>. <i>japonicum</i> (white) or <i>L</i>. <i>stellipilum</i> (blue). (b) Posterior probabilities of the genotype class estimated with NEWHYBRIDS. Each individual is represented as a vertical bar divided into six segments. Each color indicates the posterior probabilities of an individual assignment to pure <i>L</i>. <i>japonicum</i> (LJ), pure <i>L</i>. <i>stellipilum</i> (LS), F₁, F₂, and first generation backcross of a F₁ hybrid with a pure <i>L</i>. <i>japonicum</i> (BC1J) or with a pure <i>L</i>. <i>stellipilum</i> (BC1S). Populations are labeled above the bar plots.</p

Mean number of alleles per locus (<i>N</i>_a), observed heterozygosities (<i>H</i>_O), expected heterozygosities (<i>H</i>_E)and fixation index (<i>F</i>_IS) estimated at ten microsatellite loci in <i>L</i>. <i>japonicum</i>, <i>L</i>. <i>stellipium</i> and their hybrids.

<p>Mean number of alleles per locus (<i>N</i>_a), observed heterozygosities (<i>H</i>_O), expected heterozygosities (<i>H</i>_E)and fixation index (<i>F</i>_IS) estimated at ten microsatellite loci in <i>L</i>. <i>japonicum</i>, <i>L</i>. <i>stellipium</i> and their hybrids.</p

Outcomes of acute myocardial infarction patients admitted to different hospitals.

<p>OR = odds ratio; CI = confidence interval; HR = hazard ratio.</p><p>Note: The analyses of length of stay and 30-day readmissions excluded patients who died in hospital or were transferred to another acute care hospital after admission. The analyses of 30-day readmissions also excluded readmissions for rehabilitations and were limited to patients admitted before November 30, 2008.</p>*<p>Multivariate generalized linear (for length of stay), logistic (for readmissions and 30-day mortality) and Cox proportional hazard (for 1-year mortality) models adjusted for patient age, gender, race, median household income, high school graduation rate, tobacco use, individual medical comorbidities (congestive heart failure, cardiac arrhythmias, valvular disease, pulmonary circulation disorders, peripheral vascular disorders, hypertension, paralysis, other neurological disorders, chronic pulmonary disease, diabetes, hypothyroidism, renal failure, liver disease, peptic ulcer disease excluding bleeding, lymphoma, metastatic cancer, solid tumor without metastasis, rheumatoid arthritis, coagulopathy, obesity, weight loss, fluid and electrolyte disorders, blood loss anemia, and deficiency anemia), and hospital characteristics (including number of beds, profit status, rural vs. urban location, teaching status, and nurse staffing ratio).</p>**<p>Low-quality hospitals were defined as those in the bottom 10% rankings of the composite quality score, medium-quality hospitals in the middle 80%, and high-quality hospitals in the top 10% rankings of the composite quality score.</p