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Record W1949066988 · doi:10.18357/ijih92201214365

Medevac and Beyond: The Impact of Medical Travel on Nunavut Residents / ᑐᐊᕕᕐᓇᑐᒃᑰᕐᓂᖅ ᐊᒻᒪᓗ ᐅᖓᑎᒃᑲᓐᓂᐊᓄᑦ: ᓄᓇᕗᒻᒥᐅᑦ ᐋᓐᓂᐊᕕᓕᐊᖅᐸᑦᑐᑦ ᐊᑦᑐᖅᑕᐅᓂᕆᕙᑦᑕᖏᑦ

2015· article· en· W1949066988 on OpenAlexaffvenueabout
Cameron McKenzie

Bibliographic record

VenueInternational Journal of Indigenous Health · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsYork University
Fundersnot available
KeywordsPsychosocialMental healthTRIPS architectureMedicineSocial isolationIsolation (microbiology)Social supportQualitative researchNursingPsychologyPsychiatrySociologySocial psychology

Abstract

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This qualitative study identifies key factors that contribute to negative psychosocial outcomes for Inuit patients using the Iqaluit, Nunavut, medevac (used for emergency transfers) and medical transfer (for non-emergency cases) programs. The study also reports on the existence and appropriateness of social and cultural supports in hospitals and communities for medically transferred patients and their families. I analyzed results from a literature review, document analysis, and 20 in-depth, semi-structured interviews with health care professionals and policy and decision makers in Iqaluit and Ottawa, Ontario. Respondents were either directly involved in medevac and medical transfer programs or were health professionals who work with those using the services. In addition, variables impacting patient speed of recovery and overall mental health were considered, including isolation, social support, and emotional stress. Findings revealed that Inuit patients do experience a lack of social supports such as escorts and translators on medical trips south. They also often encounter a lack of cultural sensitivity once in the south, and suffer from homesickness and isolation. This study demonstrates that the current medical transfer system in Nunavut does not fully meet the psychosocial needs of Inuit patients and their families, which has direct effects on patients’ mental health and on medical outcomes of treatment in the south.ᐅᓇ ᖃᐅᔨᓴᕐᓂᐅᓯᒪᔪᖅ ᐃᓕᓴᖅᓯᕗᖅ ᐱᓗᖅᑯᑕᐅᔪᓂᒃ ᑐᓂᕐᕈᑎᖃᖅᑐᓂᒃ ᐃᓅᓯᕐᒧᑦ ᐃᓱᒪᒃᑯᓪᓗ ᐃᓄᓐᓄᑦ ᐋᓐᓂᐊᕕᓕᐊᖅᐸᑦᑐᓄᑦ ᐊᑲᐃᓪᓕᐅᕈᑎᓂᒃ ᐊᖅᑯᑎᒋᓪᓗᒋᑦ ᐃᖃᓗᐃᑦ, ᓄᓇᕗᑦ ᑐᐊᕕᕐᓇᑐᒃᑯ ᐊᒻᒪᓗ ᐃᖏᕐᕋᓂᒃᑯᑦ (ᑐᐊᕕᕐᓇᖏᑦᑐᑯᓪᓗ ᐊᖅᑯᑕᐅᕙᑦᑐᒃᑯᑦ). ᖃᐅᔨᓴᐅᑎ ᐅᓂᒃᑲᐅᓯᖃᕆᕗᖅ ᐅᓪᓗᒥ ᐋᓐᓂᐊᕕᓐᓂ ᓄᓇᓕᓐᓂᓗ ᐊᑐᐃᓐᓇᐅᒪᔪᓂᒃ ᐊᒻᒪᓗ ᐊᑲᕐᕆᔾᔪᑕᐅᔪᓂᒃ ᐃᓅᖃᑎᒌᓐᓂᒃᑯᑦ ᐊᒻᒪᓗ ᐃᓕᖅᑯᓯᒃᑯᑦ ᐋᓐᓂᐊᕕᓕᐊᖅᓯᒪᔪᓄᑦ ᐃᓚᖏᓐᓄᓪᓗ ᐃᑲᔪᖅᑐᐃᔾᔪᑕᐅᔪᓂᒃ. ᕿᒥᕐᕈᓚᐅᕆᕗᖓ ᖃᐅᔨᓴᐅᑎᒥᓂᕐᓂᒃ ᐅᖃᓕᒫᒐᓕᐊᖑᓯᒪᔪᓂᒃ, ᐅᓂᒃᑳᓪᓗ ᕿᒥᕐᕈᔭᐅᓯᒪᔪᑦ ᐊᕙᑎᑦ ᓈᔭᖅᑕᐅᓯᒪᑦᑎᐊᖅᑐᑎᒃ, ᐊᐱᖅᑯᑎᓪᓗ ᐃᓚᖓᒍᑦ ᑎᑎᕋᖅᑕᐅᓯᒪᓪᓗᑎᒃ ᐋᓐᓂᐊᖅᑐᓕᕆᔨᒃᑯᑦ ᐃᖅᑲᓇᐃᔭᖅᑎᖏᓐᓄᑦ ᐊᒻᒪᓗ ᐊᑐᐊᒐᓕᐅᖅᑎᓄᑦ ᐃᓱᒪᓕᐅᖅᑎᓄᓪᓗ ᐃᖃᓗᓐᓂ ᐋᑐᕚᒥᓗ, ᐋᓐᑎᐅᕆᐅᒥ. ᐊᐱᖅᓱᖅᑕᐅᓯᒪᔪᑦ ᑐᐊᕕᕐᓇᖅᑐᒃᑰᕐᓂᑰᔪᑦ ᐊᐅᓪᓚᖅᑐᓕᕆᔨᒃᑯᓐᓂ ᐅᕝᕙᓗᑭᐊᖅ ᐋᓐᓂᐊᖅᑐᓕᕆᓂᕐᒥ ᐃᖅᑲᓇᐃᔮᖃᐅᖅᑐᑎᒃ. ᑕᐃᒪᓗ, ᐋᓐᓂᐊᕕᓕᐊᖅᓯᒪᔪᓄᑦ ᐱᔾᔪᑕᐅᔪᑦ ᐃᑉᐱᓐᓂᕈᑕᐅᓯᒪᔪᑦ ᐊᑲᐅᓯᕙᓪᓕᐊᓂᖏᓐᓂᒃ ᐊᒻᒪᓗ ᐃᓱᒪᔾᔪᓯᖏᓐᓂᒃ, ᐃᓚᓕᐅᑦᑐᒋᑦ ᐅᖓᓯᑦᑐᒥᐅᑕᐅᓂᖏᑦ, ᐃᓄᓕᕆᓂᒃᑯᑦ ᐃᑲᔫᑕᐅᔪᑦ ᐊᒻᒪᓗ ᐃᓱᒫᓗᓐᓇᖅᑐᑎᒍᑦ. ᖃᐅᔨᔾᔪᑕᐅᔪᑦ ᑐᑭᓯᓇᖅᓯᓚᐅᖅᑯᑦ ᐃᓄᐃᑦ ᐋᓐᓂᐊᕕᓕᐊᖅᐸᑦᑐᑦ ᐃᓄᓕᕆᓂᒃᑯᑦ ᐃᑲᔪᖅᓱᖅᑕᐅᓂᑭᑉᐸᓐᓂᖏᓐᓂᒃ ᓲᕐᓗ ᐃᑲᔪᖅᑎᒡᒋᐊᖃᕋᑎᒃ ᐊᒻᒪᓗ ᑐᓵᔨᑭᔅᓴᐸᑦᑐᑎᒃ ᖃᓪᓗᓈᓕᐊᕋᐃᒐᒥᒃ. ᐊᒥᒐᖅᓯᔾᔪᑕᐅᕙᑦᑐᑦ ᑐᑭᓯᔾᔪᑕᐅᔪᒋᕗᖅ ᐃᓄᐃᑦ ᐱᖅᑯᓯᖏᓐᓂᒃ ᖃᐅᔨᒪᓂᑭᓐᓂᖏᓐᓄᑦ ᐋᓐᓂᐊᖅᑐᓕᕆᔨᒃᑯᑦ, ᐊᖏᕐᕋᓯᖅᐸᑦᑐᓪᓗ ᐊᒻᒪᓗ ᐃᓄᑑᓕᐅᑎᕙᓐᓂᖏᓐᓂᒃ. ᐅᓇ ᖃᐅᔨᓴᐅᑎ ᑕᑯᖅᑯᔾᔨᓚᐅᖅᑯᖅ ᒫᓐᓇᒃᑯᑦ ᐋᓐᓂᐊᕕᓕᐊᕐᓂᕆᕙᑦᑕᖏᑦ ᓄᓇᕗᒻᒥᐅᑕᐃᑦ ᐃᓚᖏᑕᓗ ᐊᑲᕐᕆᔮᓐᖏᒋᐊᖏᑕ ᐋᓐᓂᐊᕕᓕᐊᖅᐸᑦᑐᑦ ᐃᓱᒪᖏᑎᒍᑦ ᐃᓄᓕᕆᓂᒃᑯᑎᒍᓪᓗ. ᑕᒪᒃᑯᐊ ᐋᓐᓂᐊᕕᓕᐊᖅᐸᑦᑐᑦ ᐃᓱᒪᔾᔪᓯᖏᑦ ᐊᒻᒪᓗ ᐋᓐᓂᐊᖏᑕ ᖃᓄᐃᓐᓂᖏᓐᓂᒃ ᐊᑦᑐᐃᕙᑦᑐᑦ ᖃᓪᓗᓈᓃᑎᓪᓗᒋᒃ.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.472
Teacher spread0.408 · 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 teacher head, not a consensus.

Study designObservational
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

Citations8
Published2015
Admission routes3
Has abstractyes

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