2017
DOI: 10.1002/ajcp.12140
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Applying a Time‐Patterned Typology of Homelessness Among Individuals with Mental Illness

Abstract: Identification of subgroups of the homeless populations, or typologies, has been an important research priority to guide homelessness services and policies. This study builds on previous typological research conducted in the general homeless population by focusing on individuals with mental illness to further delineate typologies within a more homogenous subset of the homeless population. A time-patterned typology based on episodes of street and shelter homelessness over a four-year period was applied to a sam… Show more

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Cited by 22 publications
(24 citation statements)
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“…Similar trends have also been found across Europe, with the exception of Finland where there has been a marked reduction in homelessness [ 3 ]. For most people, homelessness is experienced as a single episode that is short in length but, for others, homelessness is longer in duration and re-occurring [ 4 , 5 , 6 ].…”
Section: Introductionmentioning
confidence: 99%
“…Similar trends have also been found across Europe, with the exception of Finland where there has been a marked reduction in homelessness [ 3 ]. For most people, homelessness is experienced as a single episode that is short in length but, for others, homelessness is longer in duration and re-occurring [ 4 , 5 , 6 ].…”
Section: Introductionmentioning
confidence: 99%
“…Homelessness isa significant social problem in North America, with recent estimates of over 560,000 people in the United States (National Alliance to End Homelessness, ) and 35,000 people in Canada(Gaetz, Dej, Richter, & Redman, ) experiencing homelessness on a given night. Based on residential administrative data, previous research has found various subgroups of the homeless population (Aubry, Farrell, Hwang, & Calhoun, ; Brown, Chodzen, Mihelicova, & Collins, ; Kuhn & Culhane, ). Of particular interest are those experiencing chronic homelessness.…”
Section: Introductionmentioning
confidence: 99%
“…One such example has been the challenge of identifying homelessness in some patients. [57][58][59] These patients may require care in varying locations over a short period, requiring frequent reassessments of patient demographic data. Related issues, such as transportation, providing medications that require refrigeration, or using diagnostic modalities that require electricity (for monitoring), need to be modified accordingly.…”
Section: Future Synergies Between Ai and Precision Medicinementioning
confidence: 99%