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Record W2807096336

The Mental and Physical Human Health Impacts of Residential Basement Flooding and Associated Financial Costs: Interviews with Households in Southern Ontario, Canada

2018· dissertation· en· W2807096336 on OpenAlexaboutno aff
Dana Decent

Bibliographic record

VenueUWSpace (University of Waterloo) · 2018
Typedissertation
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthFlooding (psychology)GeographyBusinessSocioeconomicsEnvironmental healthEconomic growthMedicinePsychologyEconomicsPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

This thesis summarizes primary research conducted on the mental and physical health impacts associated with residential basement flooding and their associated financial costs (e.g. days off work, visits to health services, medication use). This thesis focuses on residential basement flooding because flooding has become the costliest of all extreme weather events in Canada, as it increases in frequency and severity. The three research questions of this thesis are: \n1.\tWhat are the short-term and long-term mental and physical health impacts associated with residential basement flooding? \n2.\tWhat are the attributes affecting vulnerability to identified health impacts? \n3.\tWhat are the mental and physical health financial costs associated with residential basement flooding? \nThis author interviewed 100 residents in flood-impacted neighbourhoods in Burlington, Ontario, a city where over 3,500 homes were flooded in August 2014 (Conservation Halton, 2015). The author interviewed 58 residents, who had experienced basement flooding, in reference to health impacts realized within the first 30 days of flooding, and those realized anytime after those first 30 days. A total of 42 residents who lived in the same neighbourhood but had not experienced flooding in their home formed the control, and the author interviewed them in reference to specific health impacts realized in the last three years since flooding. \n \nIn response to the first research question, the thesis found that there were significant mental health impacts (increased worry and stress) realized both in the first 30 days of experiencing flooding and approximately three years later. This suggests that there are both short-term and long-term mental health impacts associated with residential basement flooding. \n \nIn response to the second research question, there were several attributes identified in this study that significantly correlated with higher worry and stress. These attributes included age (adults and seniors from flooded households exhibited higher worry and stress than adults and seniors in the control), water height, difficulty contacting an insurance provider, and worsening of existing health issues. \n \nIn response to the third research question, the study found that over half (56%) of flooded households that had at least one working member (n=25) took time off work, and the average time off work was seven person days per household. This is substantially higher than the average for Ontario in 2014 (<1 day), suggesting that residential basement flooding significantly affects productivity for workers. Almost half (49%) of flooded households did not have full property and casualty insurance coverage. \nAdditional research could build on this study through examination of medical data and health claims in flood-impacted communities to further explore financial costs resulting from the health impacts of flooding. Additional research in another community with a different socio-economic background could help to determine the breadth of applicability of the study findings. \n \nThis thesis provides insight into the real worry, stress and financial impact that flooding can cause for households. As flooding increases in frequency and severity (Insurance Bureau of Canada, 2017a), this thesis provides additional urgency and rationale to implement flood mitigation measures in Canada to secure homeowners’ peace of mind and reduce financial costs that otherwise may escalate in the years to come.

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)0.001
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0180.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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
Published2018
Admission routes1
Has abstractyes

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