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Record W4382447950 · doi:10.32598/rj.24.1.3582.1

Comparing the Rehabilitation Structures in the Health Systems of Iran, Germany, Japan, Canada, Turkey, and South Africa

2023· article· en· W4382447950 on OpenAlexaboutno aff
Mojgan Farahbod, Iravan Masoudi Asl, Seyyed Jamaloddin Tabibi, Mohammad Kamali

Bibliographic record

VenueJournal of Rehabilitation · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsnot available
FundersIslamic Azad University
KeywordsRehabilitationOrganizational structureChristian ministryMedicineBusinessPolitical sciencePhysical therapy

Abstract

fetched live from OpenAlex

Objective Because of the increasing number of people with disabilities and the lack of awareness of disability prevention methods in developing countries, creating a proper rehabilitation structure and providing appropriate services are among the important goals of every health system. Conducting comparative studies is one of the research methods for reviewing the structure of the rehabilitation system in the country’s health system. This study aimed to compare the rehabilitation structure in Iran with 5 other countries. Materials & Methods This research is a comparative study conducted in 2022. In this study, sampling was purposeful. Five countries of Germany, Japan, Canada, Turkey, and South Africa were compared in terms of organizational and health management, financial and legal components, and social policy components with Iran. Reliable databases and related resources in the rehabilitation structure were used to collect data. In this study, the obtained data were analyzed using the Bereday model containing four stages: Description, interpretation, proximity, and comparison. The findings were evaluated in a comparative table. Results The findings indicated that in terms of organization and health management, the Ministry of Health should be responsible for health management and rehabilitation, but in Iran, in addition to the Ministry of Health, the Red Crescent, the Martyr Foundation, and Exceptional Education Organization are also involved in the management of rehabilitation. Financial issues and problems are significant barriers for people with disabilities to access rehabilitation services in these countries. In Iran, a large part of these costs is paid from the pockets of families. Regarding legal components in Iran, as in other countries, specific rules exist to provide services to people with disabilities. But sometimes, these rules are not properly implemented. From the sociodemographic perspective, Iran has an aging population, welcomes immigrants, and holds diverse cultures. The access of all people in need of rehabilitation in this diverse population to the services needed is limited. In terms of policy components, regulating national health policy requires review and, if necessary, changes in existing health system policies. Conclusion The existence of a specific position for rehabilitation in the Iranian health system, provision of services, and management of rehabilitation affairs by a single organization such as the Ministry of Health, as well as proper implementation of laws and policies, can lead to structural improvement and management of the health system and rehabilitation. Financial obstacles and problems to rehabilitation services should be reduced, and government and insurance must cover most of the costs of rehabilitation services. Also, a review of national health policies and legislation in the country should be done to improve the access of all people with disabilities to health and rehabilitation services. Therefore, it is necessary to fundamentally review and reform the structure, value, and process of providing rehabilitation services.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.036
GPT teacher head0.308
Teacher spread0.272 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2023
Admission routes1
Has abstractyes

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