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1.
BMC Med Educ ; 21(1): 191, 2021 Apr 05.
Article in English | MEDLINE | ID: mdl-33820542

ABSTRACT

CONTEXT: Shortage of physicians in the UK has been a long-standing issue. Graduate entry medicine (GEM) may offer a second point of entry for potential doctors. However, the challenges of developing and implementing these programmes are still unrecognised. This small-scale study aimed to briefly explore the opportunities and challenges facing students at two UK GEM programmes. METHODS: Two case studies were conducted at Imperial College and Scotland's GEM (ScotGEM) and used a triangulated qualitative approach via semi-structured and elite interviews. Data analysis, informed by grounded theory, applied thematic and force-field analysis in an empirical approach to generate evidence and instrumental interpretations for Higher Education Institutions. RESULTS: Although GEM forms an opportunity for graduates to enter medicine, the different drivers of each programme were key in determining entry requirements and challenges experienced by postgraduates. Three key dilemmas seem to influence the experiences of learners in GEM programmes: (a) postgraduate identity and the everchanging sense-of-self; (b)self-directed and self-regulated learning skills, and (c) servicescape, management and marketing concepts. CONCLUSIONS: Graduate entry programmes may support policy makers and faculty to fill the workforce gap of healthcare professionals. However, their successful implementation requires careful considerations to the needs of graduates to harness their creativity, resilience and professional development as future healthcare workers.


Subject(s)
Faculty , Physicians , Humans , Students , United Kingdom , Workforce
2.
Eur Spine J ; 26(4): 1291-1297, 2017 04.
Article in English | MEDLINE | ID: mdl-28102448

ABSTRACT

PURPOSE: To assess the reliability and validity of a hand motion sensor, Leap Motion Controller (LMC), in the 15-s hand grip-and-release test, as compared against human inspection of an external digital camera recording. METHODS: Fifty healthy participants were asked to fully grip-and-release their dominant hand as rapidly as possible for two trials with a 10-min rest in-between, while wearing a non-metal wrist splint. Each test lasted for 15 s, and a digital camera was used to film the anterolateral side of the hand on the first test. Three assessors counted the frequency of grip-and-release (G-R) cycles independently and in a blinded fashion. The average mean of the three was compared with that measured by LMC using the Bland-Altman method. Test-retest reliability was examined by comparing the two 15-s tests. RESULTS: The mean number of G-R cycles recorded was: 47.8 ± 6.4 (test 1, video observer); 47.7 ± 6.5 (test 1, LMC); and 50.2 ± 6.5 (test 2, LMC). Bland-Altman indicated good agreement, with a low bias (0.15 cycles) and narrow limits of agreement. The ICC showed high inter-rater agreement and the coefficient of repeatability for the number of cycles was ±5.393, with a mean bias of 3.63. CONCLUSIONS: LMC appears to be valid and reliable in the 15-s grip-and-release test. This serves as a first step towards the development of an objective myelopathy assessment device and platform for the assessment of neuromotor hand function in general. Further assessment in a clinical setting and to gauge healthy benchmark values is warranted.


Subject(s)
Cervical Vertebrae/physiopathology , Diagnosis, Computer-Assisted , Hand Strength/physiology , Neurologic Examination/instrumentation , Spinal Cord Compression/diagnosis , Adult , Female , Humans , Male , Reproducibility of Results , Severity of Illness Index , Spinal Cord Compression/physiopathology , Virtual Reality , Young Adult
3.
Eur Spine J ; 26(4): 1298-1304, 2017 04.
Article in English | MEDLINE | ID: mdl-28102449

ABSTRACT

PURPOSE: To set a baseline measurement of the number of hand flexion-extension cycles and analyse the degree of motion in young healthy individuals, measured by leap motion controller (LMC), besides describing gender and dominant hand differences. METHODS: Fifty healthy participants were asked to fully grip-and-release their dominant hand as rapidly as possible for a maximum of 3 min or until subjects fatigued, while wearing a non-metal wrist splint. Participants also performed a 15-s grip-and-release test. An assessor blindly counted the frequency of grip-and-release cycles and magnitude of motion from the LMC data. RESULTS: The mean number of the 15-s G-R cycles recorded by LMC was: 47.7 ± 6.5 (test 1, LMC); and 50.2 ± 6.5 (test 2, LMC). In the 3-min test, the total number of hand flexion-extension cycles and the degree of motion decreased as the person fatigued. However, the decline in frequency preceded that of motion's magnitude. The mean frequency of cycles per 10-s interval decreased from 35.4 to 26.6 over the 3 min. Participants reached fatigue from 59.38 s; 43 participants were able to complete the 3-min test. CONCLUSIONS: Normative values of the frequency of cycles and extent of motion for young healthy individuals, aged 18-35 years, are provided. Future work is needed to establish values in a wider age range and in a clinical setting.


Subject(s)
Cervical Vertebrae/physiopathology , Hand Strength/physiology , Neurologic Examination/instrumentation , Reference Values , Spinal Cord Compression/physiopathology , Adolescent , Adult , Diagnosis, Computer-Assisted , Female , Humans , Male , Severity of Illness Index , Spinal Cord Compression/diagnosis , Virtual Reality , Young Adult
4.
BMJ Surg Interv Health Technol ; 5(1): e000141, 2023.
Article in English | MEDLINE | ID: mdl-36817624

ABSTRACT

Objectives: Knee osteoarthritis is a major cause of physical disability and reduced quality of life, with end-stage disease often treated by total knee replacement (TKR). We set out to develop and externally validate a machine learning model capable of predicting the need for a TKR in 2 and 5 years time using routinely collected health data. Design: A prospective study using datasets Osteoarthritis Initiative (OAI) and the Multicentre Osteoarthritis Study (MOST). OAI data were used to train the models while MOST data formed the external test set. The data were preprocessed using feature selection to curate 45 candidate features including demographics, medical history, imaging assessments, history of intervention and outcome. Setting: The study was conducted using two multicentre USA-based datasets of participants with or at high risk of knee OA. Participants: The study excluded participants with at least one existing TKR. OAI dataset included participants aged 45-79 years of which 3234 were used for training and 809 for internal testing, while MOST involved participants aged 50-79 and 2248 were used for external testing. Main outcome measures: The primary outcome of this study was prediction of TKR onset at 2 and 5 years. Performance was evaluated using area under the curve (AUC) and F1-score and key predictors identified. Results: For the best performing model (gradient boosting machine), the AUC at 2 years was 0.913 (95% CI 0.876 to 0.951), and at 5 years 0.873 (95% CI 0.839 to 0.907). Radiographic-derived features, questionnaire-based assessments alongside the patient's educational attainment were key predictors for these models. Conclusions: Our approach suggests that routinely collected patient data are sufficient to drive a predictive model with a clinically acceptable level of accuracy (AUC>0.7) and is the first such tool to be externally validated. This level of accuracy is higher than previously published models utilising MRI data, which is not routinely collected.

5.
Bioengineering (Basel) ; 10(8)2023 Aug 07.
Article in English | MEDLINE | ID: mdl-37627824

ABSTRACT

Three-dimensional planning of hip arthroplasty is associated with better visualisation of anatomical landmarks and enhanced mapping for preoperative implant sizing, which can lead to a decrease in surgical time and complications. Despite the advantages of hip resurfacing arthroplasty (HRA), it is considered a technically challenging procedure and associated with inaccurate implant placement. This study aimed to examine the validity, reliability, and usability of preoperative 3D Hip Planner software for HRA. Fifty random cases of various hip osteoarthritis severity were planned twice by two junior trainees using the 3D Hip Planner within a one-month interval. Outcome measures included femoral/cup implant size, stem-shaft angle, and cup inclination angle, and were assessed by comparing outcomes from 2D and 3D planning. An adapted unified theory of acceptance and use of technology (UTAUT) survey was used for software usability. Bland-Altman plots between 3D and 2D planning for stem-shaft and inclination angles showed mean differences of 0.7 and -0.6, respectively (r = 0.93, p < 0.001). Stem-shaft and inclination angles showed inter-rater reliability biases of around -2° and 3°, respectively. Chi-square and Pearson's correlation for femoral implant size showed a significant association between the two assessors (r = 0.91, p < 0.001). The 3D test-retest coefficient of repeatability for stem-shaft and inclination angles were around ±2° and ±3°, respectively, with a strong significant association for femoral implant size (r = 0.98, p < 0.001). Survey analyses showed that 70-90% agreed that 3D planning improved expectancy in four domains. 3D hip planner appears to be valid and reliable in preoperative HRA and shows significant potential in optimising the quality and accuracy of surgical planning.

6.
JMIR Form Res ; 6(9): e36130, 2022 Sep 13.
Article in English | MEDLINE | ID: mdl-36099008

ABSTRACT

BACKGROUND: Knee osteoarthritis (OA) is the most common form of OA and a leading cause of disability worldwide. Chronic pain and functional loss secondary to knee OA put patients at risk of developing depression, which can also impair their treatment response. However, no tools exist to assist clinicians in identifying patients at risk. Machine learning (ML) predictive models may offer a solution. We investigated whether ML models could predict the development of depression in patients with knee OA and examined which features are the most predictive. OBJECTIVE: The primary aim of this study was to develop and test an ML model to predict depression in patients with knee OA at 2 years and to validate the models using an external data set. The secondary aim was to identify the most important predictive features used by the ML algorithms. METHODS: Osteoarthritis Initiative Study (OAI) data were used for model development and external validation was performed using Multicenter Osteoarthritis Study (MOST) data. Forty-two features were selected, which denoted routinely collected demographic and clinical data such as patient demographics, past medical history, knee OA history, baseline examination findings, and patient-reported outcome measures. Six different ML classification models were trained (logistic regression, least absolute shrinkage and selection operator [LASSO], ridge regression, decision tree, random forest, and gradient boosting machine). The primary outcome was to predict depression at 2 years following study enrollment. The presence of depression was defined using the Center for Epidemiological Studies Depression Scale. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1 score. The most important features were extracted from the best-performing model on external validation. RESULTS: A total of 5947 patients were included in this study, with 2969 in the training set, 742 in the test set, and 2236 in the external validation set. For the test set, the AUC ranged from 0.673 (95% CI 0.604-0.742) to 0.869 (95% CI 0.824-0.913), with an F1 score of 0.435 to 0.490. On external validation, the AUC varied from 0.720 (95% CI 0.685-0.755) to 0.876 (95% CI 0.853-0.899), with an F1 score of 0.456 to 0.563. LASSO modeling offered the highest predictive performance. Blood pressure, baseline depression score, knee pain and stiffness, and quality of life were the most predictive features. CONCLUSIONS: To our knowledge, this is the first study to apply ML classification models to predict depression in patients with knee OA. Our study showed that ML models can deliver a clinically acceptable level of performance (AUC>0.7) in predicting the development of depression using routinely available demographic and clinical data. Further work is required to address the class imbalance in the training data and to evaluate the clinical utility of the models in facilitating early intervention and improved outcomes.

7.
BDJ Open ; 8(1): 22, 2022 Aug 01.
Article in English | MEDLINE | ID: mdl-35915067

ABSTRACT

OBJECTIVES: The study was conducted to investigate whether peer-assessment among dental students at the clinical stage can be fostered and become closer to that of experienced faculty assessors. METHODS: A prospective pilot study was conducted in 2021 at the Faculty of Dentistry, Damascus University. Sixteen 5th year clinical students volunteered to participate in the study. A modified version of the validated Peer Direct Observation of Procedural Skills (Peer-DOPS) assessment form was used together with a grading rubric. Participants undertook peer-assessment on their colleagues across three encounters. The difference between peers and faculty assessment was the main variable. RESULTS: The mean difference between peers and faculty assessment decreased after each encounter with a significant difference and a medium effect size between the first and third encounters (p = 0.016, d = 0.67). Peer-assessment was significantly higher than faculty, however, the overestimation declined with each encounter reducing the difference between peer- and faculty assessment. Peers' perception of the educational benefit of conducting assessment was overwhelmingly positive, reporting improvements in their own performance. CONCLUSION: This pilot study provides preliminary evidence that dental students assessment ability of their peers can be fostered and become closer to that of experienced faculty assessment with practice and assessment-specific instruction.

8.
Clin Exp Dent Res ; 8(4): 883-892, 2022 08.
Article in English | MEDLINE | ID: mdl-35385226

ABSTRACT

PURPOSE/OBJECTIVES: The current study was undertaken to investigate whether self-assessment of clinical skills of undergraduate dental students could be bridged with faculty assessment by deliberate training over an extended period. A secondary aim was to explore students' perception of self-assessment and its effect on their learning and motivation. MATERIAL AND METHODS: A prospective pilot study was conducted at the Department of Restorative Dentistry at Damascus University. Sixteen students participated in the study, ranging in age between 22 and 23 years. A modified Direct Observation of Procedural Skills form with a grading rubric was used to register and guide students' self-assessment; both were pretested on four students before the study. In total, four clinical encounters were completed by each student. Students were trained on how to conduct proper self-assessment before and after each clinical encounter. A postcourse questionnaire was used to investigate students' perception of self-assessment. RESULTS: Bias in self-assessment decreased consistently after each encounter, and the difference in bias between the first (bias = 0.77) and the last encounter (bias = 0.21) was significant with a medium effect size (p = .022, d = 0.64). The percentage of disconfirming performance dimensions decreased from 39.7% to 26.9%. Students' ability to exactly pinpoint strengths improved consistently and significantly. However, their ability to pinpoint areas of improvement was volatile and showed no significant difference. Bland-Altman graph plots showed higher levels of agreement between self-assessment and faculty assessment. Moreover, students' perception of self-assessment was very positive overall. CONCLUSIONS: These findings suggest the possibility that the gap between self-assessment and faculty assessment could be bridged through deliberate training. Future longitudinal research using a larger sample size is still required to further explore whether self-assessment can be actively bridged with faculty assessment by deliberate training.


Subject(s)
Faculty, Dental , Self-Assessment , Adult , Clinical Competence , Dentistry , Education, Dental/methods , Educational Measurement/methods , Humans , Pilot Projects , Prospective Studies , Students, Dental , Young Adult
9.
J Dent ; 114: 103816, 2021 11.
Article in English | MEDLINE | ID: mdl-34560227

ABSTRACT

OBJECTIVES: This meta-analysis review aims to answer two questions: 1) What is the effectiveness of hydrophilic resin-based sealant (RBS) in preventing/arresting pits and fissures caries in permanent teeth, and 2) What is the retention rate of a hydrophilic RBS as compared to alternative treatments. DATA: Randomized control trials investigating the efficacy of hydrophilic RBS compared to any other (placebo) treatment for permanent teeth. Outcomes were retention rate and caries prevention/arresting. SOURCES: A systematic search for eligible studies was conducted on six electronic databases (Scopus, Ovid MEDLINE, Ovid Embase, Cochrane; Web of Science, PubMed) from inception to March 2021. The Cochrane guidelines were used to classify the risk of bias. STUDY SELECTION/RESULTS: A systematic literature search resulted in 290 studies. Thirteen articles met our inclusion criteria and were included in the systematic review. Six articles were identified as good or fair quality and were included in the quantitative analysis. Meta-analysis results indicated that there is no significant difference in retention (RR 1.01, 95% CI:0.96-1.07, P-value 0.66), (RR 1.03, 95% CI: 0.89-1.19, P-value 0.0009) at six and twelve months, respectively. Likewise, for caries prevention there is no significant difference (RR 0.97, 95% CI: 0.91-1.03, P-value 0.19), (RR 0.30, 95% CI: 0.91-1.03, P-value 0.30) at six and twelve months. CONCLUSIONS: This meta-analysis showed no statistically significant difference between the hydrophilic RBS and alternative treatment options (such as conventional resin or glass ionomer) regarding retention or caries prevention at six- and twelve-month follow-up. Future studies are required to investigate longer-term outcomes.


Subject(s)
Dental Caries , Pit and Fissure Sealants , Bias , Bibliometrics , Dental Caries/prevention & control , Dentition, Permanent , Humans , Pit and Fissure Sealants/therapeutic use
10.
JMIR Med Educ ; 7(4): e26251, 2021 Oct 18.
Article in English | MEDLINE | ID: mdl-34661542

ABSTRACT

BACKGROUND: Virtual supervisory relationships provide an infrastructure for flexible learning, global accessibility, and outreach, connecting individuals worldwide. The surge in web-based educational activities in recent years provides an opportunity to understand the attributes of an effective supervisor-student or mentor-student relationship. OBJECTIVE: The aim of this study is to compare the published literature (through a critical review) with our collective experiences (using small-scale appreciative inquiry [AI]) in an effort to structure and identify the dilemmas and opportunities for virtual supervisory and mentoring relationships, both in terms of stakeholder attributes and skills as well as providing instructional recommendations to enhance virtual learning. METHODS: A critical review of the literature was conducted followed by an AI of reflections by the authors. The AI questions were derived from the 4D AI framework. RESULTS: Despite the multitude of differences between face-to-face and web-based supervision and mentoring, four key dilemmas seem to influence the experiences of stakeholders involved in virtual learning: informal discourses and approachability of mentors; effective virtual communication strategies; authenticity, trust, and work ethics; and sense of self and cultural considerations. CONCLUSIONS: Virtual mentorship or supervision can be as equally rewarding as an in-person relationship. However, its successful implementation requires active acknowledgment of learners' needs and careful consideration to develop effective and mutually beneficial student-educator relationships.

11.
Cartilage ; 13(2_suppl): 53S-67S, 2021 12.
Article in English | MEDLINE | ID: mdl-32059614

ABSTRACT

OBJECTIVE: Circadian rhythms in cartilage homeostasis are hypothesized to temporally segregate and synchronize the activities of chondrocytes to different times of the day, and thus may provide an efficient mechanism by which articular cartilage can recover following physical activity. While the circadian clock is clearly involved in chondrocyte homeostasis in health and disease, it is unclear as to what roles it may play during early chondrogenesis. DESIGN: The purpose of this study was to determine whether the rhythmic expression of the core circadian clock was detectable at the earliest stages of chondrocyte differentiation, and if so, whether a synchronized expression pattern of chondrogenic transcription factors and developing cartilage matrix constituents was present during cartilage formation. RESULTS: Following serum shock, embryonic limb bud-derived chondrifying micromass cultures exhibited synchronized temporal expression patterns of core clock genes involved in the molecular circadian clock. We also observed that chondrogenic marker genes followed a circadian oscillatory pattern. Clock synchronization significantly enhanced cartilage matrix production and elevated SOX9, ACAN, and COL2A1 gene expression. The observed chondrogenesis-promoting effect of the serum shock was likely attributable to its synchronizing effect on the molecular clockwork, as co-application of small molecule modulators (longdaysin and KL001) abolished the stimulating effects on extracellular matrix production and chondrogenic marker gene expression. CONCLUSIONS: Results from this study suggest that a functional molecular clockwork plays a positive role in tissue homeostasis and histogenesis during early chondrogenesis.


Subject(s)
Cartilage, Articular , Circadian Clocks , Cartilage, Articular/metabolism , Chondrocytes/metabolism , Chondrogenesis , Circadian Clocks/genetics , Extracellular Matrix/metabolism
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