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Record W2070593508 · doi:10.12927/cjnl.2005.19025

The Current Certification Model: Does It Reflect Nursing Knowledge?

2005· article· en· W2070593508 on OpenAlexvenueaboutno aff
Gloria Joachim, Marcy Saxe-Braithwaite, Heather Mass, Robert Calnan, B Ratsoy

Bibliographic record

VenueNursing leadership · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationNursingCurrent (fluid)PsychologyNursing researchKnowledge managementPolitical scienceMedicineComputer scienceEngineering

Abstract

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Although certification is widely believed to be important, little recognition is given to certified nurses. Many nurses choose not to certify or recertify based largely on the lack of recognition and the perception that the certification process is costly and lengthy. The aim of this project was to collect data, in a two-dimensional format, about the amount of time used to prepare for the Canadian Nurses Association (CNA) certification exams. On one axis, the specialties were noted, and on the other, the educational background was noted. A secondary aim of the project was to explore whether the concept of opportunity cost loss is useful for assessing the value of certification. Data from a group of certifying nurses were collected. Preparation time varied widely between individuals The Current Certification Model: Does It Reflect Nursing Knowledge? Gloria Joachim, RN, MSN Associate Professor, University of British Columbia School of Nursing Vancouver, BC Marcy Saxe-Braithwaite, RN, MScN, MBA Vice President, Programs and Chief Nursing Officer Providence Continuing Care Centre Kingston, ON Heather Mass, RN, MSc Chief of Nursing, Children’s and Women’s Health Centre of British Columbia Vancouver, BC Robert Calnan, RN, MEd President, Canadian Nurses Association Manager, Burns, Plastics, EENT and Urology, Capital Health Region Victoria, BC Bernadet Ratsoy, RN, MSc Associate Dean of Health Sciences, British Columbia Institute of Technology (Retired) Burnaby, BC ON-LINE EXCLUSIVE 1 Nursing Leadership On-line Exclusive • April 2005 2 and specialties. The variation in preparation time suggests that differences may be due to age and education. Recommendations are given to change the structure of the certification process from a single-tiered exam to a multi-tiered exam that would reflect differences in nursing education. The purpose of certification is (1) to establish standards in specialty practice that will promote excellence in nursing care for Canadians, (2) to confirm competence in specialty practice and (3) to identify nurses who meet the national standards with a credential (CNA 2004a). Cary (2001) notes that certification should protect the public from unsafe care, distinguish between levels of care provided and give certified nurses a competitive advantage in the workplace. Many institutions now require specialty education or certification for employment in specialty areas (personal communication, Human Resources, St. Paul’s Hospital, Vancouver General Hospital, April 2002). History of Certification in Canada Certification in Canada has a short history. The certification program of the Canadian Nurses Association (CNA) began in 1980 with the recommendation by an ad hoc committee that CNA develop a certification program in the specialties (CNA 2004a). The criteria for a specialty group to qualify for credentialling status included having established standards; addressing a recurrent practice phenomenon; having a role description for practitioners; being supported by literature, education and research; having identified the number and distribution of nurses in the specialty; and having sufficient numbers of practitioners to support certification (CNA 2002: 5). At the time that data were collected for this study, CNA certification was available in 11 specialties; in 2004, 14 specialties were listed (CNA 2004a). Certification status spans five years. Recertification is available in all specialties. Prerequisites for Certification The eligibility criteria for becoming a certified nurse in Canada for all specialties other than Occupational Health consists of two options (CNA 2002: 2). In the first, the nurse must hold current Canadian registration, have accumulated 3,900 practising hours in the specialty during the last five years and have a supervisor or consultant in the specialty verification. In the second, one must hold current Canadian registration, have a nursing degree or post-basic nursing specialty course with at least 300 hours of work in the specialty, accumulate a minimum of 1,950 practice hours in the specialty during the last three years and have a supervisor or consultant verify the experience. To be eligible for certification in the specialty of Occupational Health, there are also two options. In the first, one must hold current Canadian registration, have accumulated at least 5,000 hours of work in Occupational Health during the last five years, have accumulated 75 hours of continuous education in Occupational Health during the last five years and have supervisor or consultant verification of activities. In the second, one must hold current registration, have a nursing degree or Occupational Health specialty course that is at least 300 hours long, have accumulated 75 hours of continuing education in Occupational Health during the last five years and have supervisor or consultant verification of activities. Methods The CNA certification office assisted by mailing a questionnaire to nurses who wrote the 2001 certification exams. Participants were asked about demographics, educational background and specialty, and were asked to record, on a weekly basis, the amount of time invested in all aspects of preparation for the certification exam. Data would be plotted in a two-dimensional database with specialty on the x axis and educational background on the y axis. If differences between the specialties occurred, the data could become the basis for generating equivalencies between specialties. For example, it may be determined that specialty A is more difficult than specialty B, specialty B is more difficult than specialty C and specialty B = specialty D. Using this logic, equivalencies and rankings could be established among the specialties. If differences within the specialties occurred, they would be analyzed depending upon the educational background. Results Forty nurses certifying in nine specialties returned the completed questionnaire. While this is a small sample, definitive trends emerged. All were women with a mean age of 43. Thirteen had diplomas in nursing, 22 had baccalaureate degrees and five had master’s degrees. Nineteen had some formal specialty education in the specialty in which they were certifying, and 21 had no formal specialty education. Nurses certified in the following specialties: Critical Care, Emergency, Gerontology, Nephrology, Occupational Health, Oncology, Perioperative and Psychiatric/Mental Health. Nurses in the specialties of Critical Care and Emergency had the most specialty education and were the youngest nurses with specialty education. In the Gerontology group, none of the nine nurses had specialty education. There was a wide variety in the mean amounts of preparation time for each specialty. The Perioperative specialty (mean of 40 hours) had the shortest amount of time, while Oncology (mean of 136.6 hours) had the longest. For individuals, preparation time varied from 20 to 350 hours. The youngest nurses with specialty education used the least amount of preparation time, while the oldest and most experienced nurses used the longest amounts of preparation time. The Current Certification Model: Does It Reflect Nursing Knowledge? 3

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)0.016
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.099
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0050.006
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.457
GPT teacher head0.388
Teacher spread0.069 · 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.

Study designTheoretical or conceptual
DomainEvaluation
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
Published2005
Admission routes2
Has abstractyes

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