Using the Rasch model in nursing research: An introduction and illustrative example

Hagquist, Curt; Bruce, Malin; Gustavsson, Petter

doi:10.1016/j.ijnurstu.2008.10.007

Cited by 287 publications

(358 citation statements)

References 18 publications

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“…consistency that is comparable to Cronbach's a (Hagquist et al, 2009). This index is calculated using estimates from the Rasch model and represents the power of the test to discriminate amongst the respondents.…”

Section: Person Reliability the Person Separation Index (Psi) Is An mentioning

confidence: 73%

“…In this respect, fit residuals below -2.5 indicate an overfit and above +2.5 an underfit, respectively. Furthermore, c 2 tests can be performed for each item to identify significant deviations of the model-based item characteristic curves from the observed item characteristic curves (Hagquist, Bruce, & Gustavsson, 2009). To account for multiple difference testing, the p values of the c 2 statistics are Bonferroni adjusted (Bland & Altman, 1995).…”

Section: Running Head: Measuring the Adoption Of Effective Strategies 13mentioning

confidence: 99%

“…Starting with item AUT2, we excluded one item at a time, because the fit of the items depends on the frame of reference (Hagquist et al, 2009) however, there was some misfit at the lower and upper ends of the curve (see Figure 2). A further qualitative investigation of COL3 revealed that the wording appeared imprecise: the item could be understood in different ways, because "students" may either refer to pre-service teachers themselves or the students they teach during their internship.…”

Section: Irt Analysesmentioning

confidence: 99%

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Time for a new approach to prepare future teachers for educational technology use: Its meaning and measurement

Tondeur

Braak

Siddiq

et al. 2016

Computers & Education

206

120

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The main objective of this study is to develop a self-report instrument to measure preservice teachers' perceptions of the extent to which they experience the necessary support and training in order to integrate technology into classroom activities. The questionnaire items of this instrument were drawn up on the basis of a synthesis of 19 qualitative studies (Authors et al., 2012) and were reviewed by experts in the field. In order to study its reliability and aspects of validity, data were collected and analysed consisting of a sample of 688 pre-service teachers in Flanders (Belgium). The resulting scale showed highly satisfactory psychometric properties. Item response theory revealed a good fit of the measurement to a Rating Scale Model for 22 out of 24 items. The results also indicate that the items differ in their degree of difficulty. It seems that helping pre-service teachers to design ICT-rich lessons and providing adequate feedback can be considered more challenging for teacher training institutions.Recommendations are given regarding how the new scale can be useful for both teacher training institutions and schools in developing approaches to equip pre-service teachers with the competencies needed to integrate technology in teaching and learning processes.

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Section: Person Reliability the Person Separation Index (Psi) Is An mentioning

confidence: 73%

Section: Running Head: Measuring the Adoption Of Effective Strategies 13mentioning

confidence: 99%

Section: Irt Analysesmentioning

confidence: 99%

See 1 more Smart Citation

Time for a new approach to prepare future teachers for educational technology use: Its meaning and measurement

Tondeur

Braak

Siddiq

et al. 2016

Computers & Education

206

120

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“…Rasch analysis allows calibration of the items' difficulty and the subjects' abilities independently, but using the same measurement unit, the logit (log-odds) (6)(7) . For Rasch analysis to be carried out, the following presuppositions must be observed: the items should measure only one latent feature (unidimensionality) and the answer to one item must not be associated with the answer of another item (local independence) (8)(9)(10) .…”

Section: Discussionmentioning

confidence: 99%

Informatics competencies essential to decision making in nursing management

Jensen

Guedes

Leite

2016

Rev. esc. enferm. USP

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Objective:To identify informatics abilities essential to decision making in nursing management. Method: Survey study with specialist nurses in health informatics and management. An electronic questionnaire was built based on the competencies Information Literacy (five categories; 40 abilities) and Information Management (nine categories; 69 abilities) of the TIGER -Technology Informatics Guiding Education Reform -initiative, with the guiding question: Which informatics abilities are essential to decision making in management? Answers were sorted in a Likert scale, ranging from 1 to 5. Rasch analysis was conducted with the software WINSTEPS®. Results were presented in logits, with cutoff value zero. Results: Thirty-two specialists participated, coming from all regions of Brazil. In the information literacy competency, 18 abilities were considered essential and in Information Management, 38; these were sorted according to their degree of essentiality. Conclusion: It is believed that the incorporation of these abilities in teaching can support the education of nurse managers and contribute to evidence-based practice, incorporation of information and communication technologies in health and information management.

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“…Several reviews 12, 24, 25 of Rasch analysis have detailed the process and defined terminology; therefore, only a brief overview is provided here. Analysis was conducted in RUMM2020 26 using the dichotomous and partial credit models 27.…”

Section: Methodsmentioning

confidence: 99%

Pain Phenotype in Patients With Knee Osteoarthritis: Classification and Measurement Properties of painDETECT and Self‐Report Leeds Assessment of Neuropathic Symptoms and Signs Scale in a Cross‐Sectional Study

Moreton

Tew

Nair

et al. 2015

Arthritis Care & Research

108

102

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ObjectiveMultiple mechanisms are involved in pain associated with osteoarthritis (OA). The painDETECT and Self‐Report Leeds Assessment of Neuropathic Symptoms and Signs (S‐LANSS) questionnaires screen for neuropathic pain and may also identify individuals with musculoskeletal pain who exhibit abnormal central pain processing. The aim of this cross‐sectional study was to evaluate painDETECT and S‐LANSS for classification agreement and fit to the Rasch model, and to explore their relationship to pain severity and pain mechanisms in OA.MethodsA total of 192 patients with knee OA completed questionnaires covering different aspects of pain. Another group of 77 patients with knee OA completed questionnaires and underwent quantitative sensory testing for pressure–pain thresholds (PPTs). Agreement between painDETECT and S‐LANSS was evaluated using kappa coefficients and receiver operator characteristic (ROC) curves. Rasch analysis of both questionnaires was conducted. Relationships between screening questionnaires and measures of pain severity or PPTs were calculated using correlations.ResultsPainDETECT and S‐LANSS shared a stronger correlation with each other than with measures of pain severity. ROC curves identified optimal cutoff scores for painDETECT and S‐LANSS to maximize agreement, but the kappa coefficient was low (κ = 0.33–0.46). Rasch analysis supported the measurement properties of painDETECT but not those of S‐LANSS. Higher painDETECT scores were associated with widespread reductions in PPTs.ConclusionThe data suggest that painDETECT assesses pain quality associated with augmented central pain processing in patients with OA. Although developed as a screening questionnaire, painDETECT may also function as a measure of characteristics that indicate augmented central pain processing. Agreement between painDETECT and S‐LANSS for pain classification was low, and it is currently unknown which tool may best predict treatment outcome.

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Using the Rasch model in nursing research: An introduction and illustrative example

Cited by 287 publications

References 18 publications

Time for a new approach to prepare future teachers for educational technology use: Its meaning and measurement

Time for a new approach to prepare future teachers for educational technology use: Its meaning and measurement

Informatics competencies essential to decision making in nursing management

Pain Phenotype in Patients With Knee Osteoarthritis: Classification and Measurement Properties of painDETECT and Self‐Report Leeds Assessment of Neuropathic Symptoms and Signs Scale in a Cross‐Sectional Study

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