Rasch analysis of the Modified Fatigue Impact Scale (MFIS) in multiple sclerosis

Mills, Roger; Young, Carolyn A; Pallant, Julie; Tennant, Alan

doi:10.1136/jnnp.2008.151340

Cited by 83 publications

(86 citation statements)

References 16 publications

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“…This could be an explanation why the ICCs found in this study were higher than in the other studies. Another limitation is that FSS and MFIS were used as comparator instruments despite their problems regarding reliability and validity 4,6 . These were administered in the present study because there were no other Brazilian specific instrument for assessing MS fatigue.…”

Section: Discussionmentioning

confidence: 99%

“…Considering limitations relating to the most widely used instruments for assessing MS fatigue (FSS and MFIS) 4,6,12 , hypotheses were made to include other instruments, so as to attribute more evidence for checking the construct validity of the NFI-MS/BR. Even though the correlation scores turned out to be very low between the nonsimilar subscales of the instruments that measure the same construct all the hypotheses were confirmed.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, they were not specifically developed for MS patients 4,5,6 . Studies using the Rasch measurement model have identified a need for certain items to be removed from the FSS [4] and MFIS [6] so that their measurements can be considered valid and reliable.In Brazil, FSS 7 and MFIS 8 have been widely used, despite the failings of their design and psychometric properties in Brazilian cross-cultural adaptation studies. These Brazilian versions did not fulfill the criteria for adequate sample size and design.…”

mentioning

confidence: 99%

“…The Fatigue Severity Scale (FSS) 2 and Modified Fatigue Impact Scale (MFIS) 3 are the most widely used instruments for measuring MS fatigue, although limitations regarding their development and measurement properties have been reported. Moreover, they were not specifically developed for MS patients 4,5,6 . Studies using the Rasch measurement model have identified a need for certain items to be removed from the FSS [4] and MFIS [6] so that their measurements can be considered valid and reliable.…”

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confidence: 99%

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Validation of the Brazilian version of the neurological fatigue index for multiple sclerosis

Lopes

Lavado

Kaimen-Maciel

2016

Arq. Neuro-Psiquiatr.

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Fatigue is the most frequent and severe of symptoms causing morbidity and disability in multiple sclerosis (MS) patients. However, measuring fatigue is a difficult task. There is no clear definition; it is complex and multidimensional, and is a highly subjective symptom with many uncertainties regarding its pathophysiology. No biological or neuroimaging markers for fatigue are currently known 1 . The lack of standardization for fatigue measurement has resulted in development of several assessment instruments, but none of them is universally accepted. The Fatigue Severity Scale (FSS) 2 and Modified Fatigue Impact Scale (MFIS) 3 are the most widely used instruments for measuring MS fatigue, although limitations regarding their development and measurement properties have been reported. Moreover, they were not specifically developed for MS patients 4,5,6 . Studies using the Rasch measurement model have identified a need for certain items to be removed from the FSS [4] and MFIS [6] so that their measurements can be considered valid and reliable.In Brazil, FSS 7 and MFIS 8 have been widely used, despite the failings of their design and psychometric properties in Brazilian cross-cultural adaptation studies. These Brazilian versions did not fulfill the criteria for adequate sample size and design. Moreover, the psychometric properties of the Brazilian FSS adaptation were not assessed. Therefore, there are no Brazilian MS-specific instrument for assessing fatigue with reported methodological and psychometric properties ABstrACtThe Neurological Fatigue Index for Multiple Sclerosis (NFI-MS) is a new fatigue assessment instrument. The aim of this study was to cross-culturally adapt and assess the psychometric properties of the Brazilian version of the NFI-MS (NFI-MS/BR). Method: Two hundred and forty subjects with MS were recruited for this study. The adaptation of the NFI-MS was performed by translation and back translation methodology. In psychometric analysis was performed the administration of the questionnaires Epworth Sleep Scale, Fatigue Severity Scale, Modified Fatigue Impact Scale, Multiple Sclerosis Impact Scale-29, NFI-MS/BR and Pittsburgh Sleep Quality Index with retest of the NFI-MS/BR after 7 days. Results: Reliability was assessed (intraclass correlation coefficients between 0.77 and 0.86), and validity by testing 41 hypotheses about expected correlations between subscales and confirmed 36. The majority of correlations were demonstrated. Conclusion: The NFI-MS/BR is a cross-culturally adapted, valid, and reliable instrument for assessing MS fatigue among Brazilian subjects.Keywords: multiple sclerosis; fatigue; assessment; validation studies; psychometrics. resumo O índice neurológico de fadiga na esclerose múltipla (EM) (NFI-MS) é um novo instrumento de avaliação da fadiga. O objetivo deste estudo foi adaptar transculturalmente e avaliar as propriedades psicométricas da versão Brasileira do NFI-MS (NFI-MS/BR).Método: Duzentos e quarenta indivíduos com EM participaram deste estudo. A adaptação do NFI-MS/BR f...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Validation of the Brazilian version of the neurological fatigue index for multiple sclerosis

Lopes

Lavado

Kaimen-Maciel

2016

Arq. Neuro-Psiquiatr.

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“…The Modified Fatigue Impact Scale (MFIS) [28] is another self-reported measure concerning the impact of fatigue on daily life. The total score is the sum of the scores for the 21 items, each ranging from 0 to 4.…”

Section: Datamentioning

confidence: 99%

Extraction of Information from Inertial Sensors to Aid Health Assessment

Dandu¹

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Tracking human activity and fitness have been the latest trends in the world of wearable technology.Inertial sensors offer a practical and low cost method for objectively monitoring human movements, and particularly have the applicability to monitor free-living subjects. Shoes, smart phones, watches and other wearables equipped with inertial sensors are able to capture human motion in a non-obtrusive way.Similar sensors are placed on several positions on the human body to monitor a range of different movements, including gait, sit-to-stand transfers, postural sway and limb movements. Inertial sensors have provided a simple and reliable approach to collect human kinematics data. The inertial data collected by these sensors contains valuable information related to human movements, which can be used to monitor and assess the health of a person. But the field of wearable technology still struggles to develop a methodology which can derive relevant information, from the raw inertial data, to aid in health assessment.This work presents a framework to extract information from raw inertial data corresponding to human motion. The framework is a sequential learning process coupled with application-specific knowledge.This framework has three stages: data preparation, feature engineering and information extraction. The first stage converts the raw data into usable data, the second stage extracts relevant attributes from the data and the third stage derives information from these attributes to aid health assessment. A number of techniques can be used at each of the stages, and the appropriate ones are chosen by employing application-specific knowledge as the cornerstone.

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