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Record W7005427070

Psychological status and well being among emergency medical officers in hospitals in Malaysia

2017· dissertation· en· W7005427070 on OpenAlexaboutno aff

Bibliographic record

VenueUniversiti Sains Malaysia Institutional Repository (Universiti Sains Malaysia) · 2017
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsWell-beingOvercrowdingMental healthDepression (economics)MoodJob satisfactionFeelingScarcityEmotional exhaustion
DOInot available

Abstract

fetched live from OpenAlex

Health is defined is a state of complete physical, mental and social wellbeing and not merely the absence of disease or infirmity (Callahan, 1973). As applied to any occupation, an ideal job is likely to be the one which can promote career satisfaction, and at the same time has appropriate pressures on the employee’s abilities and resources. Giving autonomy, providing training in communication and management skills also are found to be important in maintaining satisfaction and enhancement of career (Ramirez et al., 1996).
\nAcross the professions, healthcare workers has been identified to be one of the most striking profession contributing to the prevalence of job dissatisfaction and work related emotional disturbances. The modern medical workplace, such as emergency department is a complex environment and they response to it vary greatly. Overcrowding with resource scarcity (Rondeau et al., 2005) leads to patient’s dissatisfaction, constant exposure to noise pollutants(ringing phones, beeping monitors, slamming doors) leads to unknowingly accumulated stress among workers (Tijunelis et al., 2005) and predisposed to violence from the patients or family members lead to feeling unsafe and job related stress (Gates et al., 2006) despite the necessity of providing essential care for them. The demand of multitasking and continuous interruption due to dynamic changes of the treated patients are common and contribute to significant disturbances of concentration and mental exhaustion (Chisholm et al., 2000).
\nDepression is term as a mood disorder characterized by sadness, lack of interest in daily activities, inability to concentrate, disturbances in appetite and sleeping patterns (Ingram, 2012). The prevalence of depression in Malaysia is estimated from 6.3% to 13.9% (Mukhtar and PS Oei, 2011), whereas it was reported as 10.3% by Maideen et al. (2015). As for the medical students in Malaysia, the prevalence of depression reported was 37.2%by Shamsuddin et al. (2013). In a study conducted in Sheffield, the prevalence of depression among house officers were reported as 28% (Firth-Cozens, 1987), whereas in Kota Kinabalu, Malaysia it was reported as 42.9% (Shahruddin et al., 2016). As for the emergency residents, it was reported as 12.1% by Katz et al. (2006), whereas the mean score for emergency residents were found to be higher in terms of depersonalization due to depression (Michels et al., 2003). Contradicting to this, a study among Canadian family medicine residents reported that the prevalence of depression was 20% (Earle and Kelly, 2005), which is higher as compared to the emergency residents.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.005
GPT teacher head0.249
Teacher spread0.244 · 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
Published2017
Admission routes1
Has abstractyes

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