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Cited by 592

The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.

Structural Equation Modeling in Practice: Testing a Theory for Research Use

Johnson, Knowlton W.·1999·Journal of Social Service Research

Abstract

Structural Equation Modeling (SEM) is gaining attention in social work as an analytical method for studying social policy and testing theories for practice. This paper demonstrates a special SEM application to test a theory for research use in the human services. Data from 294 decision-makers in human service organizational units of federal, state, and local governments are used to show the appropriateness of using composites instead of multiple indicators in a SEM model with latent variables. The step-by-step description of a two-stage modeling process is presented. Using a model generation analysis strategy, the results show that a nonrecursive model positing a reciprocal relationship between research use and diffusion could not be confirmed. Instead, a recursive model is uncovered with research use leading to research diffusion. In addition, perceived quality of research, positive interaction between researchers and decision-makers, and transfer intensity of disseminating research results through multiple media, produced direct and indirect effects on research use and diffusion. The limitations and strengths of this study using the special SEM application are discussed.

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Metadata

Authors
Johnson, K. W.
Venue
Journal of Social Service Research
Published
1999-01
Volume
24
Issue
3-4
Pages
131-171
ISSN
  • 0148-8376 (ISSN-L)
  • 1540-7314
OpenAlex
W1833883724
Cited by
592
References
65
FWCI
39.30
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Structural Equation Modeling in Practice: Testing a Theory for Research Use. https://app.cochat.ai/papers/10.1300/j079v24n03_06
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Johnson, K. W. (1999). Structural Equation Modeling in Practice: Testing a Theory for Research Use. Journal of Social Service Research. https://doi.org/10.1300/j079v24n03_06

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.