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Record W2588944383

Identifying Quality of Life Needs of Youth Experiencing Homelessness: A Community Needs Assessment for Planners in the Region of Waterloo

2016· dissertation· en· W2588944383 on OpenAlexaboutno aff
Jeremy W. Turner

Bibliographic record

VenueUWSpace (University of Waterloo) · 2016
Typedissertation
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersWorld Health Organization
KeywordsQuality (philosophy)Quality of life (healthcare)SociologyPsychologyGerontologyMedicinePsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

Abstract \nBackground: The aim of this study is to capture the most important quality of life (QoL) needs \nidentified by youth experiencing homelessness in the Region of Waterloo. Palepu, Hubley, Russell, Gadermann and Chinni originally conducted a similar study in 2012. Their study identified QoL needs for the broader homeless population. This research study intends to identify age-specific QoL needs specifically for the homeless youth population. Young people who have experienced homelessness are interviewed to identify aspects important to their overall QoL. \n \nMethods: A document analysis was conducted on four local official planning documents, five social planning documents for the Region of Waterloo, and one from the government of Ontario. The document analysis was completed to add empirical substance in order to provide a planning rationale to understand effective engagement processes with homeless youth. Individual interviews were conducted with 15 homeless youths between the ages of 16-25 who identified as homeless or recently homeless. Interviews were conducted at two youth shelters in the Region of Waterloo, OneRoof: Providing a Roof and Lutherwood: SafeHaven. Participants were recruited to participate in 15-20 minute interviews to identify important QoL needs of homeless youth. \n \nResults: The three key findings include the following: QoL is a universal term used across many publications and reports, but is not defined; a general lack of youth engagement and public consultation with homeless youths, and; that the QoL needs of homeless youth are distinct from those of homeless adults. As a result of this study, a clearer understanding exists of the term QoL with respect to the homeless youth population. Six major QoL needs specific to homeless youth were identified through this research. These six QoL needs include: family and friends, basic necessities, education, health, community resources, and self-care/awareness. \n \nRecommendations: The main recommendation to emerge from this study is that social planners consult with homeless youth when creating social planning documents affecting the homeless population. The term QoL must be defined in the context of all populations, including age- specific groups. A multidisciplinary approach is recommended to integrate the helping professions with planners. Planners must work with other professionals in the community to gather more valid and meaningful feedback. \nConclusions: The findings of this study are intended to assist researchers and professionals in understanding differences in age-specific needs within vulnerable population groups. A shift towards collaboration with vulnerable populations redefines the term expert-based model. QoL has become a “trendy” phrase to use in planning documents, however more research is needed to better understand the implications for planners and homeless youths. This research study is exploratory in nature; the results identified in this research study are to be viewed as a stepping- stone toward further research and changes in practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.886

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.094
GPT teacher head0.373
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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