| Literature DB >> 28360237 |
Rola Ajjawi1, Karen L Barton2, Ashley A Dennis3, Charlotte E Rees4.
Abstract
OBJECTIVES: This study aimed to identify national dental education research (DER) priorities for the next 3-5 years and to identify barriers and enablers to DER.Entities:
Keywords: EDUCATION & TRAINING (see Medical Education & Training); STATISTICS & RESEARCH METHODS; dental education research; online questionnaire; priority setting
Mesh:
Year: 2017 PMID: 28360237 PMCID: PMC5372062 DOI: 10.1136/bmjopen-2016-013129
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Comparison of the American Dental Hygienists' Association priority items listed for the ‘Professional Education and Development’ theme5 10
| Forrest | Forrest and Spolarich (2009) |
|---|---|
|
Investigate the extent to which new research findings are incorporated into the dental hygiene curriculum. Investigate the extent to which students are taught critical thinking and decision-making skills. Identify the factors leading to curriculum modification and reform in dental hygiene academic programmes. Investigate the extent to which students are taught self-assessment and evaluation skills. Develop a predictive model for future needs/demands for dental hygiene personnel. |
Investigate the extent to which new research findings are incorporated into the dental hygiene curriculum. Validate and test measures that evaluate student critical thinking and decision-making skills. Evaluate the extent to which current dental hygiene curriculum prepares dental hygienists to meet the increasingly complex oral health needs of the public. Critically appraise current methods of evaluating (assessing) clinical competency. Investigate how other health professions have established the masters and doctoral levels of education as their entry level into practice. Identify the factors that affect recruitment and retention of faculty. Assess how educators are socialising students into research. Investigate curriculum models for training and certification of competency in specialty areas. |
Characteristics of respondents to both online questionnaires
| Characteristic | Stage 1 (n, (%)) | Stage 2 (n, (%)) |
|---|---|---|
| Age, years (%) | ||
| ≤20 | 0 | 19 (2.9) |
| 20–29 | 8 (9.4) | 219 (33.7) |
| 30–39 | 13 (15.3) | 124 (19.1) |
| 40–49 | 26 (30.6) | 129 (19.9) |
| 50–59 | 30 (35.3) | 136 (21.0) |
| 60–69 | 8 (9.4) | 21 (3.2) |
| ≥70 | 0 | 1 (0.2) |
| Gender (%) | ||
| Male | 46 (54.1) | 242 (37.3) |
| Female | 39 (45.9) | 407 (62.7) |
| Ethnicity (%) | ||
| White, White Scottish, White British | 81 (95.3) | 565 (87.1) |
| Non-White* | 4 (4.7) | 84 (12.9) |
| Stakeholder group† (%) | ||
| Learners | 9 (10.6) | 189 (29.1) |
| Educators | 74 (87.1) | 189 (29.1) |
| Dentists | 53 (62.4) | 581 (89.5) |
| Dental care professionals | 16 (18.8) | 111 (17.1) |
| Researchers | 12 (14.1) | 26 (4.0) |
| Patient representatives | 1 (1.2) | 2 (0.3) |
| Region* (%) | ||
| East | 37 (43.5) | 185 (28.5) |
| North | 20 (23.5) | 89 (13.7) |
| South East | 8 (9.4) | 84 (12.9) |
| West | 19 (22.4) | 267 (41.1) |
| National (Scotland) | 9 (10.6) | 32 (4.9) |
| UK | 3 (3.5) | 13 (2.0) |
| International | 0 | 4 (0.6) |
*Non-White is composed of a heterogeneous grouping of ethnicity in order to maintain anonymity.
†Unless indicated, any percentages that do not add up to 100% are due to rounding; Percentages add up to more than 100% because participants sometimes belonged to multiple groups.
The importance of each topic based on two indicators of perceived priority (higher scores on each indicator reflect greater perceived priority)
| Item | Score, median (IQR) | Total rank score (overall ranking) | |
|---|---|---|---|
| 1 | Role of assessments in identifying competence | 5 (4–6) | 1042 (1) |
| 15 | Undergraduate curriculum prepares for practice | 5 (5–6) | 1021 (2) |
| 12 | Promote teamwork within the dental team | 5 (4–6) | 687 (3) |
| 3 | Role of assessments in identifying underperformance | 5 (4–6) | 679 (4) |
| 2 | Providing useful feedback | 5 (4–6) | 676 (5) |
| 21 | Enhance communication skills | 5 (4–6) | 631 (6) |
| 24 | Teaching evidence-based practice | 5 (4–6) | 505 (7) |
| *7 | Select/approve educators | 5 (4–6) | 452 (8) |
| 11 | Effective workplace learning culture | 5 (4–6) | 418 (9) |
| 4 | Select/recruit dental professionals | 5 (4–6) | 383 (10=) |
| 23 | Tailoring teaching to individual learning needs | 5 (4–6) | 383 (10=) |
| *6 | Resiliency/well-being | 5 (4–6) | 366 (12) |
| 13 | Foster interprofessionalism | 5 (4–6) | 323 (13) |
| 22 | Professionalism | 5 (4–6) | 318 (14) |
| *8 | Support/value role of educators | 5 (4–6) | 288 (15) |
| 10 | Balance education/service conflicts | 5 (4–5) | 282 (16) |
| 20 | Role of simulation in education | 5 (4–6) | 258 (17) |
| 19 | Impact of technology | 4 (4–5) | 216 (18) |
| 16 | Postgraduate curriculum prepares for practice | 5 (4–6) | 179 (19) |
| *14 | Develop leadership | 4 (4–5) | 152 (20) |
| 9 | Faculty development | 5 (4–5) | 150 (21) |
| *5 | Career choice | 4 (3–5) | 126 (22) |
| 18 | Vertically integrate undergraduate/postgraduate curricula | 4 (3–5) | 121 (23) |
| 17 | Role of formal/informal curricula | 4 (3–5) | 52 (24) |
*Items 5, 6, 7, 8, 14 were not identified in Stage 1 dental education research (DER) priority-setting exercise (PSE) but were included in Stage 2 based on the medical education research (MER) PSE.6
Pattern matrix from exploratory factor analysis
| Component | |||||
|---|---|---|---|---|---|
| Item | Description of item | F1 | F2 | F3 | F4 |
| 12. | Promote teamwork within the dental team | 0.865 | |||
| 13. | Foster interprofessionalism | 0.826 | |||
| 21. | Enhance communication skills | 0.679 | |||
| 24. | Teaching evidence-based practice | 0.636 | |||
| 22. | Professionalism | 0.584 | |||
| 14. | Develop leadership | 0.523 | |||
| 11. | Effective workplace learning culture | 0.508 | |||
| 23. | Tailoring teaching to individual learning needs | 0.464 | |||
| 1. | Role of assessments in identifying competence | 0.866 | |||
| 3. | Role of assessments in identifying underperformance | 0.795 | |||
| 2. | Providing useful feedback | 0.521 | |||
| 15. | Undergraduate curriculum prepares for practice | 0.472 | |||
| 7. | Select/approve educators | −0.817 | |||
| 8. | Support/value role of educators | −0.759 | |||
| 9. | Faculty development | −0.654 | |||
| 6. | Resiliency/well-being | −0.615 | |||
| 5. | Career choice | −0.610 | |||
| 10. | Balance education/service conflicts | −0.602 | |||
| 4. | Select/recruit dental professionals | −0.588 | |||
| 18. | Vertically integrate undergraduate/postgraduate curricula | 0.732 | |||
| 19. | Impact of technology | 0.711 | |||
| 17. | Role of formal/informal curricula | 0.700 | |||
| 20. | Role of simulation in education | 0.608 | |||
| 16. | Postgraduate curriculum prepares for practice | 0.331 | 0.415 | ||
| Eigenvalues | 9.88 | 1.69 | 1.37 | 1.20 | |
| % of variance | 41.17 | 7.04 | 5.73 | 4.98 | |
| α-value | 0.89 | 0.79 | 0.86 | 0.81 | |
F1, Teamwork and professionalism; F2, Measuring and enhancing performance; F3, Dental workforce issues; F4, Curriculum integration and innovation.
Relationship between participant characteristics and ratings of importance
| Variable* | Group | Median (IQR) | Test statistics† |
|---|---|---|---|
| Factor 1 | Male | 36 (32–41) | Z=−5.03, p<0.001, r=−0.20 |
| Female | 40 (35–43) | ||
| Factor 3 | Male | 31 (25–35) | Z=−4.03, p<0.001, r=−0.16 |
| Female | 33 (29–36) | ||
| Factor 1 | White | 38 (33.75–42) | Z=−3.98, p=<0.001, r=−0.16 |
| Non-White | 41 (37–45) | ||
| Factor 2 | White | 25 (22–27) | Z=−3.60, p<0.001, r=−0.14 |
| Non-White | 27 (24–29) | ||
| Factor 3 | White | 32 (27–35) | Z=−3.45, p<0.001, r=−0.14 |
| Non-White | 35 (29–38) | ||
| Factor 4 | White | 22 (18–24) | Z=−5.61, p<0.001, r=−0.22 |
| Non-White | 25 (22–27) | ||
| Factor 2 | 18–39 | 25 (23–28) | X2=6.97, d.f.=2, p=0.031, φc=0.07 |
| 40–59 | 24 (20.5–26) | ||
| 60+ | 26 (23–28) | ||
| Factor 1 | Dentist | 37 (32–42) | Z=−6.74, p<0.001, r=−0.27 |
| Non-dentist | 41 (37–45) | ||
| Dental care professional | 41 (37–45) | Z=−6.55, p<0.001, r=−0.26 | |
| Non-dental care professional | 37 (33–42) | ||
| Factor 3 | Dentist | 31 (26–35) | Z=−5.55, p<0.001, r=−0.22 |
| Non-dentist | 34 (30.25–37) | ||
| Dental care professional | 34 (31–38) | Z=−5.58, p<0.001, r=−0.22 | |
| Non-dental care professional | 31 (26–35) | ||
| Factor 4 | Dentist | 22 (18–24) | Z=−4.13, p<0.001, r=−0.16 |
| Non-dentist | 23 (20–26) | ||
| Dental care professional | 23 (21–26) | Z=−4.03, p<0.001, r=−0.16 | |
| Non-dental care professional | 22 (18–24) |
*Factor 1= teamwork and professionalism; factor 2= measuring and enhancing performance; factor 3= dental workforce issues; factor 4= curriculum integration and innovation.
†Test statistics are Mann-Whitney Z-scores, p value, effect size r or Kruskal-Wallis χ2 value with d.f., p value, effect size Φc. For the Mann-Whitney test, effect sizes for significant findings were calculated as: r=Z/√n. Magnitudes of effect sizes for Cohen's r are: 0.1: small; 0.3: medium and 0.5: large.23 For the Kruskal-Wallis test, effect sizes were calculated using Cramer's V Φc=√(χ2/[n{k−1}]), where k equals the smaller of rows or columns. Magnitudes of effect sizes for Cramer's phi are: 0.1 to <0.2: weak association; 0.2 to <0.4: moderate association; 0.4 to <0.6: relatively strong association and ≥0.6: strong association.24