Modeling Contingency in Veteran Community Reintegration: A Mixed Methods Approach Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.1177/15586898211059616
Researchers need approaches for analyzing complex phenomena when assessing contingency relationships where specific conditions explain an outcome only when combined with other conditions. Using a mixed methods design, we paired configurational methods and qualitative thematic analysis to model contingency in veteran community reintegration outcomes, identifying combinations of conditions that led to success or lack of success in community reintegration among US military veterans. This pairing allowed for modeling contingency at a detailed level beyond the capabilities of either approach alone. Our analysis revealed multiple contingent relationships at work in explaining reintegration, including social support, purpose, cultural adjustment, and military separation experiences. This study contributes to the field of mixed methods by pairing a mathematical cross-case method with a qualitative method to model contingency.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/15586898211059616
- https://journals.sagepub.com/doi/pdf/10.1177/15586898211059616
- OA Status
- bronze
- Cited By
- 22
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4213451875
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4213451875Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1177/15586898211059616Digital Object Identifier
- Title
-
Modeling Contingency in Veteran Community Reintegration: A Mixed Methods ApproachWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-02-24Full publication date if available
- Authors
-
Nicholas A. Rattray, Edward J. Miech, Gala True, Diana Natividad, Brian Laws, Richard M. Frankel, Marina KuklaList of authors in order
- Landing page
-
https://doi.org/10.1177/15586898211059616Publisher landing page
- PDF URL
-
https://journals.sagepub.com/doi/pdf/10.1177/15586898211059616Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://journals.sagepub.com/doi/pdf/10.1177/15586898211059616Direct OA link when available
- Concepts
-
Contingency, Thematic analysis, Contingency table, Contingency management, Qualitative research, Contingency theory, Psychology, Field (mathematics), Outcome (game theory), Contingency plan, Management science, Computer science, Social psychology, Operations research, Sociology, Knowledge management, Intervention (counseling), Engineering, Mathematics, Computer security, Epistemology, Pure mathematics, Social science, Philosophy, Mathematical economics, Psychiatry, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
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22Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 6, 2023: 3, 2022: 6Per-year citation counts (last 5 years)
- References (count)
-
62Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.field | 106 |
| abstract_inverted_index.level | 72 |
| abstract_inverted_index.mixed | 25, 108 |
| abstract_inverted_index.model | 37, 121 |
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| abstract_inverted_index.beyond | 73 |
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| abstract_inverted_index.social | 92 |
| abstract_inverted_index.allowed | 65 |
| abstract_inverted_index.complex | 5 |
| abstract_inverted_index.design, | 27 |
| abstract_inverted_index.explain | 14 |
| abstract_inverted_index.methods | 26, 31, 109 |
| abstract_inverted_index.outcome | 16 |
| abstract_inverted_index.pairing | 64, 111 |
| abstract_inverted_index.success | 51, 55 |
| abstract_inverted_index.veteran | 40 |
| abstract_inverted_index.analysis | 35, 81 |
| abstract_inverted_index.approach | 78 |
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| abstract_inverted_index.cultural | 95 |
| abstract_inverted_index.detailed | 71 |
| abstract_inverted_index.military | 61, 98 |
| abstract_inverted_index.modeling | 67 |
| abstract_inverted_index.multiple | 83 |
| abstract_inverted_index.purpose, | 94 |
| abstract_inverted_index.revealed | 82 |
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| abstract_inverted_index.support, | 93 |
| abstract_inverted_index.thematic | 34 |
| abstract_inverted_index.analyzing | 4 |
| abstract_inverted_index.assessing | 8 |
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| abstract_inverted_index.including | 91 |
| abstract_inverted_index.outcomes, | 43 |
| abstract_inverted_index.phenomena | 6 |
| abstract_inverted_index.veterans. | 62 |
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| abstract_inverted_index.cross-case | 114 |
| abstract_inverted_index.explaining | 89 |
| abstract_inverted_index.separation | 99 |
| abstract_inverted_index.Researchers | 0 |
| abstract_inverted_index.adjustment, | 96 |
| abstract_inverted_index.conditions. | 22 |
| abstract_inverted_index.contingency | 9, 38, 68 |
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| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5039272261 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I1324682000, https://openalex.org/I4210110049, https://openalex.org/I4394709130, https://openalex.org/I55769427 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/10 |
| sustainable_development_goals[0].score | 0.7900000214576721 |
| sustainable_development_goals[0].display_name | Reduced inequalities |
| citation_normalized_percentile.value | 0.94552975 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |