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Record W7067798930

No. 47: The Haemorrhage of Health Professionals From South Africa: Medical Opinions

2007· article· en· W7067798930 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHealth professionalsEmigrationGeneral partnershipSample (material)The InternetHealth careDeveloping countryComputer-assisted web interviewing
DOInot available

Abstract

fetched live from OpenAlex

The health sector has been especially hard hit by the brain drain from South Africa. Unless the push factors are successfully addressed, intense interest in emigration will continue to translate into departure for as long as demand exists abroad (and there is little sign of this letting up.) Health professional decision-making about leaving, staying or returning is poorly-understood and primarily anecdotal. To understand how push and pull factors interact in decision- making (and the mediating role of variables such as profession, race, class, age, gender income and experience), the opinions of health professionals themselves need to be sought.\nThis paper reports the results of a survey of health professionals in South Africa conducted in 2005-6 by SAMP. Since there is no single reliable database for all practicing health professionals, SAMP used the 29,000 strong database of MEDpages. All those on the list were invited by email to complete an online survey. About 5% of the professionals went to the website and completed the questionnaire; some requested hard copies or electronic copies of the questionnaire which they completed and returned. Although the sample is biased towards professionals who have internet access and those who were willing to complete an online questionnaire, the sample represents a good cross-section (though not necessarily statistically representative sample) of South African health professionals and offers insights into their attitudes and opinions about emigration and other topics. In partnership with the Democratic Nursing Organisation of South Africa (DENOSA), SAMP also distributed the survey manually to a sample of nurses and received an additional 178 responses.\nData on 1,702 health professionals was collected. The largest category of respondents was doctors (44%), followed by nurses (15%), dieticians/therapists (12%), psychologists (10%), pharmacists (7%) and dentists (5%). The sample was almost evenly split between males and females. About 70% of the respondents were white, followed by blacks (10%), Indians (6%) and Coloureds (3%). The pre-dominance of whites is primarily a historical legacy of the apartheid system which was racially biased in its selection of health trainees. About 57% of the sample came from the private sector, 23% from the public sector and 17% had employment in both sectors. Half the respondents were under 42 years of age. Just over 20% were in their first five years of service while 26% had twenty or more years of service. There was more variation within professions but, in general, the sample provided an extremely good mix of professionals at different stages of their career. The survey asked questions relating to (a) living in South Africa, (b) employment conditions and (c) attitudes about moving to another country. Each answer was evaluated against the set of basic demographic characteristics to see if there were important differences in response e.g. did health sector make a difference or did gender make a difference? The seven demographic characteristics analyzed were: sex, race, health sector, health profession, domicile, household income and years of service.\nThe survey revealed the extreme dissatisfaction of many South African health professionals, a sentiment that cut across profession, race and gender. The profession is characterized not by a groundswell of discontent but a tidal wave of unhappiness and dissatisfaction with both economic and social conditions in the country. For example: With regard to general conditions in the country, there were very high levels of dissatisfaction with the HIV/AIDS situation (84% dissatisfied), the upkeep of public amenities (83%), family security (78%), personal safety (74%), prospects for their children’s future (73%) and the cost of living (45%). In only three categories were there fewer dissatisfied than satisfied professionals: availability of schooling (29% dissatisfied versus 46% satisfied), housing (30% versus 45%) and (perhaps unsurprisingly) medical facilities (19% versus 57%). In terms of working conditions, the most important source of dissatisfaction was taxation levels (58% dissatisfied, 14% satisfied) followed by fringe benefits (56% and 17%), then remuneration (53% and 22%), the availability of medical supplies (50% and 28%), workplace infrastructure (50% and 31%). prospects for professional advancement (41% and 30%) and work load (44% and 31%). Consistent with widespread concerns about safety, as many as a third were dissatisfied with the level of personal security in the workplace. Around a third of the respondents were dissatisfied with the level of risk of contracting a life-threatening disease in their work (35% versus 28% for HIV/AIDS; 32% versus 30% for TB and 37% versus 26% for Hepatitis B), an extraordinarily high percentage which is indicative of the conditions under which many work. On only two measures was there general satisfaction among the health professionals: collegial relations (76% satisfied, 5% dissatisfied) and the appropriateness of their training for the job (71% versus 14%). Variables with the greatest impact on satisfaction levels included profession and sector (public or private). Other variables (e.g. age, gender, race and years of experience) were not significant. The highest dissatisfaction levels expressed were as follows: for Workload: public sector employees, nurses and pharmacists; for Workplace Security: public sector, nurses, dentists and pharmacists; for Relationship with Management: public sector and nurses; for Infrastructure: public sector, nurses and black professionals; for Medical Supplies: public sector and public/private employees; for Morale in the Workplace: public and public/private sectors and nurses; for Risk of contracting TB: public sector; for Risk of contracting HIV/AIDS: nurses, doctors and dentists; for Risk of contracting HEP B: nurses and dentists; for Personal Safety: black professionals. Overall, public sector employees and nurses tend to have the highest levels of dissatisfaction. Income levels do significantly influence satisfaction levels on some broad issues including schooling for children, finding a house, cost of living and availability of products. In general, the higher the income the greater the percentage that are satisfied. Black professionals are more dissatisfied than others regarding finding a house (61%), schooling for children (52%) and accessing medical services for family/children (39%). Younger professionals are the most dissatisfied when it comes to finding a house (51%) and nurses have the highest percentage dissatisfied with the cost of living (62%). Comparing life in South Africa today with the situation before 1994, respondents were divided almost equally with 35% feeling it had improved, 31% that it was the same and 35% that it had deteriorated. Not surprisingly, race had a significant impact with over 50% of black, Coloured and Indian respondents feeling that life was better now than before. \nIn sum, it is alarming that South Africa’s health professionals find satisfaction in little except their interaction with colleagues. While their views of living and working in South Africa are very negative, they hold very positive opinions about other places: When asked whether life would be better in a number of potential destination countries overseas, responses were overwhelmingly positive. Topping the list of where life would be better were Australia and New Zealand (77% better, 6% worse), followed by North America (77% better, 7% worse) and Europe (72% better, 10% worse). The Middle East was also rated highly, particularly by dentists and nurses. As many as a half the sample felt that their lives would be better there. There was little evident enthusiasm for the Southern African region with 69% of respondents thinking it would be worse to live there, and only 9% thinking it would be better. However, as many as 30% of black respondents said they would do better in other Southern African countries than in South Africa. Asia was viewed in a more positive light than the rest of Southern Africa. When asked where they would likely go if they left South Africa (their personal MLD or Most Likely Destination), most selected developed countries or regions. The most popular choices were Australia/New Zealand (33%), the United Kingdom (25%), Europe (10%), the United States (10%) and Canada (9%). The results were generally consistent across the demographic variables although the UK is a more likely destination for dentists (38%) and Europe a more likely destination for psychologists (17%). Only black health professionals rated a move to a SADC country (14%) about as likely as a move to a developed country such as Canada (12%) or the United States (21%). Respondents were asked to compare employment conditions in South Africa with those in their MLD. Five features were identified by over 60% of respondents as better in the MLD: workplace security (69%), remuneration (65%), fringe benefits (63%), infrastructure (63%) and medical supplies (61%). Other issues rated by about half as better in the MLD included workload and career and professional advancement. Only training preparation was rated as better in South Africa. Hence, there is a very general perception that most aspects of the work environment are better in the MLD than in South Africa. Many also listed existing push factors that would prompt them to seek employment overseas. Some 72% cited inadequate remuneration as a reason to emigrate. Next came workplace infrastructure (cited by 27%), educational opportunity (25%), professional advancement (23%), job security (22%) and workload (19%). \nHow serious are South African health professionals about actually leaving the country? Almost half of the respondents have given it a great deal of consideration and only 14% have given it no consideration at all. Male health professionals have given emigration more serious cons

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)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0350.008

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 head0.014
GPT teacher head0.267
Teacher spread0.252 · 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 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".

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Citations0
Published2007
Admission routes1
Has abstractyes

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