Manual Manual of Diagnostic and Therapeutic Techniques for Disorders of Deglutition

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Dysphagia , 12 , — In MISA, this process is expressed as 43 ingestive skill items to be rated on a three-point ordinal scale, which are summed into five subscale scores related to positioning, self - feeding skills, liquid ingestion, solid ingestion and texture management as well as into a total score Lambert et al. Rasch models in health.

Hoboken, NJ : Wiley. Scandinavian Journal of Occupational Therapy , 18 , — Reliability of the Danish version of the McGill Ingestive Skills Assessment for observation-based measures during meals. Scandinavian Journal of Occupational Therapy , 19 , — Disability and Rehabilitation , 34 , — The Rasch methodology involves statistical analysis for investigating whether a set of rating scale data satisfies the assumptions of the model, which is based on principles of fundamental measurement Christensen et al.

The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper? If ordinal data in a rating scale fit the assumptions in the Rasch model, transformation into an interval scale is permitted, and the summed scores are regarded as specific objective and sufficient Christensen et al. Such features make an outcome measure very useful in clinical practice and research trials de Vet et al. Since the exact number of dimensions and the factor structure of the original MISA have never been established Lambert et al.

The study used a cross-sectional design and involved OT departments at four regional hospitals and three community-based rehabilitation CBR units in Denmark ClinicalTrials. All participants provided written informed consent that their data were used for the study. Participants with severe cognitive impairment, poorly controlled psychosis or known contraindications to ingest any liquids and foods were excluded. No: According to Danish legislation, the study did not need approval by the local ethical committee in the Capital Region Reg.

No: H MISA2 - DK consists of 36 ingestive skill items distributed into four subscales: positioning for meals four items ; self-feeding skills seven items ; liquid ingestion 11 items and solid ingestion 14 items.

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This format is a result of the revisions that included clarifications of five items, development of three new items and replication of three items from the solid ingestion subscale to the liquid ingestion subscale. The texture management items from the original version are regarded as single items not to be summarised. Instead, these items reflect the test-meal of four liquid texture categories thin, mildly thick, moderately thick, and extremely thick and four main solid texture categories regular, soft, minced and moist, and pureed.

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The effect of rater training on scoring performance and scale-specific expertise amongst occupational therapists participating in a multicentre study: A single-group pre—post-test study. Disability and Rehabilitation , 38 , — For inpatient participants, the assessments occurred at the hospital ward.

Manual of Diagnostic and Therapeutic Techniques for Disorders of Deglutition

The psychometric properties were analysed in three stages. The first stage used item analysis by the Rasch model to test whether the MISA2-DK total scale and the proposed subscales met the model expectations. The second stage used exploratory factor analysis EFA to determine the dimensions underpinning MISA2-DK, and the third stage tested whether these new subscales met the assumptions in the Rasch model.

Conditional pairwise estimation in the Rasch model for ordered response categories using principal components. Journal of Applied Measurement , 4 , — Because of the specific objectivity property of the Rasch model Christensen et al.

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The analysis followed established procedures Christensen et al. Using the Rasch model in nursing research: An introduction and illustrative example. International Journal of Nursing Studies , 46 , — British Journal of Clinical Psychology , 46 1 , 1 — A non-significant probability value indicates that there is no substantial deviation from the model and that the scale items function hierarchically from easy to difficult in the same pattern across all ability groups i. In addition, the overall person and item fit was addressed by inspecting the mean item and person standardised fit residuals FR , which should be close to zero with a SD of 1.

The unidimensionality of the scale i. Person estimates from these two subsets of items were compared through a series of independent t -tests. Open Journal of Statistics , 4 , — Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals.

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Journal of Applied Measurement , 3 , — Reliability statistics. Rasch measurement transactions , 6 , Next, sources of deviation from model expectations were addressed. Misfitting items or persons were removed in a stepwise procedure to obtain an overall fit to the model. The structure of the score categories was investigated by studying the thresholds of each item.

Thresholds refer to the point between two adjacent score categories where both scores are equally probable and monotonicity is expected. Diagnostic opportunities with the Rasch model for ordered response categories. Langeheine Eds. Disordered thresholds were resolved by combining adjacent categories Andrich et al. Department of Biostatistics, University of Copenhagen. Formalizing dimension and response violations of local independence in the unidimensional Rasch model. Journal of Applied Measurement , 9 , — If the pattern of the residual correlations suggests that LID were between clusters of items within subscales, the items were grouped and treated as a testlet Andrich, Andrich, D.

Components of variance of scales with a subscale structure using two calculations of coefficient alpha. Journal of Rehabilitation Medicine , 43 , — The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Quality of Life Research , 16 , 19 — When testlets of subscale domains are added to form a total score, RUMM allows the variance components of a multidimensional construct to be separated into the common variance component responsible for the correlation of the dimensions and the dimension-specific variance component Andrich, Andrich, D.

The latent estimate i. The absence of a differential item function DIF was also addressed. DIF matters: A practical approach to test if differential item functioning makes a difference. Rasch Measurement Transactions , 20 , — If there is a consistent systematic difference in the records to an item across the latent construct i.

For all final solutions, targeting was evaluated. To be acceptable, mean person locations should approximate the mean item threshold location i. Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables. Behavior Research Methods , 38 , 88 — Observations with missing values were excluded. Practical considerations for using exploratory factor analysis in educational research. The method of factor extraction was unweighted least squares ULS followed by oblique direct oblimin rotation of factors, which allow factors to be correlated.

The scree plot and parallel analysis PA with optimal implementation guided the number of retained factors Baglin, Baglin, J. Sample size: For item analysis by the Rasch model, a sample size of more than allows for accurate and stable person and item estimates Chen et al. Is Rasch model analysis applicable in small sample size pilot studies for assessing item characteristics? Quality of Life Research , 23 , — For EFA, the subject-to-item ratio should to be more than five Beavers et al. In total, participants were included.

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Table 1 displays the characteristics of the sample. Table 2 Analyses 1—9 displays the overall summary fit statistics, and Table 3 shows the item fit statistics of the initial analysis. LID was identified between items within and between all four subscales see Table 3. The best fitting solution was to use testlets to adjust LID between items within the four subscales, which provided excellent overall fit Table 2 , Analysis 2.

Separate analysis of the four subscales revealed that the positioning subscale was initially consistent with the Rasch model expectations Table 2 , Analysis 3. The best fitting solution was removal of the three misfitting items.


However, the item-trait interaction remained significant and the reliability became very low Table 3 , Analyses 4 and 5. No items displayed DIF. As seen in Table 4 , the Oblimin rotation of the five-latent-factor solution revealed that most of the 36 items loaded significantly on only one factor.

Item 20, Drinks with a sequence of sips, failed to load significantly on any factors. The five-factor solution could be interpreted as representing different aspects of ingestion: anticipation items 1—13 and item 23 , bolus formation item 24 and items 26—28 , bolus manipulation items 14, 25, 33 and 34 , bolus propulsion in the oral cavity items 15, 16, and 29 and the pharyngeal cavity items 17, 18, 30, and 31 , and airway protection items 19, 21, 22, 35, 32, and The anticipation subscale did not fit the model.

The bolus formation subscale showed model misfit.

The bolus manipulation subscale showed misfit to the model. Given the misfit of these two subscales, and since their items relate to bolus preparation in the mouth, they were combined. The bolus propulsion subscale showed adequate fit to the model. The airway protection subscale showed adequate overall fit statistics Table 2 , Analysis Analysis using testlets of the four subscales anticipation, bolus preparation, bolus propulsion and airway protection resulted in approximately good model fit Table 2 , Analysis For all final analyses in stages 1 and 3, targeting was suboptimal Table 5.

The number of missing values was acceptable de Vet et al.