Use of factor analysis in <i>Journal of Advanced Nursing</i>: literature review

Watson, Roger; Thompson, David R.

doi:10.1111/j.1365-2648.2006.03915.x

Cited by 168 publications

(190 citation statements)

References 109 publications

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“…It is unlikely that there is only a single dimension to the multifaceted research student-supervisor relationship. Therefore, this study uses a multivariate statistical method called factor analysis, specifically exploratory factor analysis (EFA), which is used to identify the underlying dimensions in multivariate datasets (Watson & Thompson, 2006) and has been applied to previous studies of different aspects of research student supervision. Ethical approval for the study was obtained from the University Ethics Committee.…”

Section: Methodsmentioning

confidence: 99%

Postgraduate Research Students’ and their Supervisors’ Attitudes towards Supervision

Ali

Watson

Dhingra

2016

IJDS

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There is a need for research exploring postgraduate research students' expectations from research supervisors, the characteristics of effective student-supervisor relationships, and the opinions of students and supervisors about research supervision. We also need instruments to explore the student-supervisor relationship. The present study investigated postgraduate research students' and research supervisors' views about postgraduate research supervision and the student supervisor relationship. It also reports on factor analysis conducted to identify the underlying dimensions in their views about postgraduate research supervision and the student supervisor relationship. Such information can be used to develop strategies to promote student-supervisor relationships and enhance the student experience.Data were collected using an online questionnaire with 30 Likert-scale statements from 131 postgraduate research students and 77 supervisors. Following exploratory factor analysis, a three factor model consisting of leaderhip, knowledge, and support was extracted. Results indicate that students and supervisors agree about the attributes of effective supervision. Both supervisors and students consider that a supervisor should have an interest in the student's research. The supervisor must provide timely and constructive feedback and should help the student to manage time effectively. Students and supervisors believe a supervisor should help the students where limitations and learning needs are identified. Students believe supervisors must encourage students to work independently and use opportunities to present their work.

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Section: Methodsmentioning

confidence: 99%

Postgraduate Research Students’ and their Supervisors’ Attitudes towards Supervision

Ali

Watson

Dhingra

2016

IJDS

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“…For each item, the factor loading (saturation) on the factor was produced, which indicated the correlation between the item and the factor, so that the closer to 100% of covariance, the better the item was considered, since it strongly represented the latent trait measured by the factor. Therefore, description of the factors in terms of the items of which it is composed was made based on the magnitude of correlations (17) . A minimum factor loading = 0.40 was considered, so that the item could be considered representative of the factor (13,18) .…”

Section: Discussionmentioning

confidence: 99%

“…Nonetheless, the use of eigenvalues may lead to overestimation of the number of factors (20) , which tends to be a problem in large data sets, since this produces trivial factors with few variables (17) . An alternative method recommended by experts in factor analysis is the scree plot, which consists of placing an eigenvalues graph against a number of items present (20) .…”

Section: Factor Analysismentioning

confidence: 99%

Análise de fatores do instrumento de medida do impacto da doença no cotidiano

et al. 2016

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RESUMO Objetivo: verificar a estrutura de fatores do Instrumento para Mensuração do Impacto da Doença no Cotidiano do Valvopata (IDCV) quando aplicado em coronariopatas. Método: fizeram parte deste estudo 153 coronariopatas em seguimento ambulatorial. A estrutura de fatores do IDCV foi inicialmente avaliada por meio da análise confirmatória de fatores e, subsequentemente, por meio da análise exploratória de fatores. Utilizou-se o método de estimação dos componentes principais de análise com rotação Varimax e eigenvalues acima de um para extração de fatores e carga fatorial superior a 0,40 para seleção dos itens. A consistência interna foi estimada por meio do coeficiente alfa de Cronbach. Resultados: a análise confirmatória não confirmou a estrutura original de fatores do IDCV. A análise exploratória de fatores evidenciou três dimensões que, em conjunto, explicaram 78% da variância da medida. Conclusão: estudos futuros com ampliação da casuística são necessários para confirmação da nova estrutura de fatores do IDCV.

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“…First, the number of factors was established using exploratory factor analysis (EFA) on one half of the datasets. [38] Because data were ordinal, polychoric rather than Pearson correlation was used. [39] The number of factors to retain was determined based on combining the Kaizer criteria, a parallel analysis and a scree plot.…”

Section: Data Analysesmentioning

confidence: 99%

Physical disability and cognitive impairment among recipients of long-term care

Døhl

Garåsen²,

Kalseth

et al. 2016

JNEP

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Background and objective: For practical policy purposes variables describing disability and impairment should be aggregated into broader factors. By using data from a Norwegian mandatory system the objective of this study was to analyse whether the number of factors describing the need for long-term care differs between recipients of home care and nursing home residents and according to the age or gender of long-term care recipients. The hierarchical order of the variables within each factor is determined to assess whether there are important informational gaps in the description of recipients. Methods: Data are from a mandatory system characterizing all recipients of public long term care in Norway. Two groups of public care recipients were included: elderly (67 years and older) individuals receiving home care services (N = 2,493) and patients in nursing homes (N = 1,218). Exploratory factor analysis (EFA), Confirmatory factor analysis (CFA) and item response analysis (IRT) were used to determine the number of factors and the hierarchical structures of the variables. Results: Two factors were sufficient to characterise need for both nursing home residents and home dwelling elderly. This result is not sensitive to stratification by age and gender. IRT analysis revealed large informational gaps suggesting that the used instrument fails to sufficiently capture important aspects of user needs. Conclusions: Factorization suggests that all elderly long term care users can be adequately described along two dimensions; on reflecting physical disability and one reflecting cognitive impairment. However, both the number of factors and the variable contained in each factor are likely to depend on the instrument used to characterise LTC users. Large informational gaps suggest a need to supplement the national information system used in Norway.

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Use of factor analysis in Journal of Advanced Nursing: literature review

Abstract: Factor analysis is quite commonly used in nursing research reported in Journal of Advanced Nursing. While some papers are exemplary there is room for improvement in the reporting of all aspects of factor analysis.

Cited by 168 publications

References 109 publications

Postgraduate Research Students’ and their Supervisors’ Attitudes towards Supervision

Postgraduate Research Students’ and their Supervisors’ Attitudes towards Supervision

Análise de fatores do instrumento de medida do impacto da doença no cotidiano

Physical disability and cognitive impairment among recipients of long-term care

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