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Record W7009913062

Healthcare utilization among urbanized syrian refugees in Jordan: exploring access, needs, barriers and adaptation strategies

2023· dissertation· en· W7009913062 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Repository of the University of Granada (University of Granada) · 2023
Typedissertation
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersUNICEF
KeywordsRefugeeThematic analysisNonprobability samplingPopulationQualitative propertyQuarter (Canadian coin)Sample (material)Health careQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Since the Syria crisis started, about one quarter of its population have fled to the neighbouring
\ncountries, mainly Turkey, Lebanon, and Jordan. Jordan has hosted more than 12% of the
\nrefugees from Syria and numbers are increasing. This increase in migration and refugee either
\ndue to long-lasting conflicts or ongoing economic crises has made the refugee movement a
\nconcern at global level and prompted hosting countries, as well as humanitarian organisations
\nto respond to this alarming crisis. The study explores the access to and utilization of healthcare
\nservices among urbanized Syrian refugees in Jordan. Using the mixed method design, this
\nphenomenon was studied among two refugees’ communities urbanized in central governorates.
\nThe study settings were selected conveniently, the participant sample for the quantitative part
\nwere randomly chosen while sampling was purposive for the qualitative part. A cross-sectional
\nsurvey among 383 refugees aged 18 – 75 years old was conducted between November 2019
\nand January 2020. Participants answers were entered directly using on tablet using KOBO tool.
\nConcurrently, in-depth semi-structured interviews were conducted among a subset of twenty
\nparticipants. Data were analyzed with descriptive and thematic analysis, while quantitative data
\nwere analyzed with descriptive statistical analysis, qualitative data were transcribed and
\nanalysed using Braun and Clarke thematic analysis approach.
\nBoth dataset analyses identified a set of fragmented needs in relation to health needs and help
\nseeking, such as emergency care, psychological-mental support needs, rehabilitation, disability,
\nelderly care, childcare, women's care, and chronic disease care. The analysis of seeking
\nbehaviour found that primary awareness, beliefs, access policy, financial capacities and practice
\nare the main drivers for health-seeking behaviours. The standard barriers quantified through
\nquantitative assessment were cost, awareness, quality of services and discrimination. The
\nqualitative assessment detected the same access barriers in addition to access policy, service availability, waiting time and distance. The standard adaptation strategies quantified by
\nquantitative assessment were a theme in qualitative findings. These include seeking free
\nservices, delaying seeking care, reducing, or stopping the use of medication, using alternative
\nmedicine, borrowing money or use saving, and moving onward. However, the qualitative
\nassessment also detected adaptation strategies included self-medication, collection donation,
\nillegal labour, and prioritising between health and other livelihood needs. Four themes found
\nunder the impact of adaptation strategies include psychological and mental health
\nconsequences, compromise of other livelihood needs, deterioration of health status and legal
\nconsequences.
\nThe perceived needs, seeking behaviours, and experienced barriers with healthcare interacts
\nwith each other. Another contextual set-up, inform Syrian refugees’ healthcare utilization
\nbehaviours, drive adaptation strategies and result in a negative impact on refugee health status,
\nbut also may extend to another means of livelihood. The study’s findings may be relevant to
\nthe global responses to the refugee crisis. The hosting countries can use it to develop a balanced
\nresponse regarding health interventions and policies to avoid negative consequences on
\nrefugees and host communities. Additionally, the third countries that received the secondary
\nmovement of refugees may use these findings to enhance support to host countries for better
\naccommodation for refugees' needs and avoid unnecessary subsequent movements that pose
\nadditional global health and other risks.

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.265
Teacher spread0.217 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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