Comparative reliability of structured versus unstructured interviews in the admission process of a residency program.
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ABSTRACT:
SUBMITTER: Blouin D
PROVIDER: S-EPMC3244318 | biostudies-other | 2011 Dec
REPOSITORIES: biostudies-other
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Project description:Interviews for the integrated plastic surgery residency match took place in a virtual format for the 2020-2021 application cycle. Current literature lacks the perspectives of program directors (PDs) on virtual interviews compared with traditional in-person interviews.MethodsFollowing institutional review board approval, an anonymous 17-question survey was distributed by email to 82 program directors of integrated plastic surgery residency programs in the United States. Participants were asked baseline program information, the number of positions and interview invites offered, and their perspectives on various aspects of the virtual interview process.ResultsSixty-two (75.6%) PDs completed the survey. Thirty-seven percent reported increasing the number of interview offers per available residency spot. On a five-point Likert scale (1, not well at all; 5, extremely well), PDs showed no significant differences in their ability judge an applicant's professionalism (3.1 ± 1.1), interpersonal and communication skills (3.2 ± 1.1), and "fit" with their program (2.9 ± 0.9) during virtual interviews (P = 0.360). Sixty-eight percent reported being satisfied (15.3% extremely satisfied, 52.5% somewhat satisfied) with the virtual interview process, though 76.3% preferred in-person interviews.ConclusionsThis study is the first to provide insight into PDs' impressions of virtual residency interviews. Although most reported being satisfied with the virtual interview process, the majority still preferred in-person interviews. Further long-term studies evaluating the pros and cons of each interview modality may provide more information on whether virtual interviews could become a sustainable alternative to the traditional in-person residency interview.
| S-EPMC8376389 | biostudies-literature
Project description:BackgroundDifferent diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.MethodData collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.ResultsA total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15-3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98-10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) (OR = 0.96; 95% CI = 0.56-1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26-0.97).ConclusionsThe MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
| S-EPMC6415695 | biostudies-literature
Project description:ObjectiveTo determine 2020 residency cycle application practices and to model potential consequences in the 2021 cycle if (1) applicants scheduled an uncapped number of interviews; (2) applicants were capped to schedule 12 interviews; (3) residency programs kept their number of interview offers unchanged; and (4) programs increased their interview offers by 20%.Design and settingThe authors sent an anonymous survey to all obstetrics and gynecology applicants registered through the Electronic Residency Application Service in February 2020 asking respondents to share demographics and number of interview offers received and completed. Based on prior estimates that 12 interviews are needed to match in obstetrics and gynecology, respondents were divided into Group 12+ (those receiving ≥12 interview offers) and Group <12 (those receiving <12 offers). Model assumptions were (1) applicants can complete all interviews they are offered because they are virtual; (2) interview offers that applicants in Group 12+ decline are subsequently offered to applicants in Group <12; (3) the proportions of interviews offered to Group 12+ and Group <12 will remain the same if programs chose to increase their total number of interview spots.ParticipantsAmong 2508 applicants, 750 (30%) provided the number of interview offers received and completed: 417 (56%) in Group 12+ and 333 (44%) in Group <12.ResultsIn models where applicants are uncapped in the number of interviews, Group <12 applicants receive <1 interview offer, even if programs increase the number of interviews offered and performed. If applicants are capped at 12 interviews, Group <12 applicants will receive 9 interview offers on average and will reach 12 if programs increase the number of interviews offered by 20%.ConclusionsThis work highlights how current inefficiencies may lead to negative consequences with virtual interviews. Interview caps and preference signaling systems need to be urgently considered.
| S-EPMC7489264 | biostudies-literature
Project description:PurposeUsing 2020 match applicants, the purpose of this study was to identify baseline applicant perspectives on the match process surveying (1) away rotations, (2) interview/postinterview communications, and (3) factors influencing applicant rank order lists.Methods and materialsApplicants in the 2020 match cycle at a large radiation oncology (RO) residency program received a questionnaire covering demographics and the match process: away rotations, interview/postinterview communications, and ranking. Univariable and multivariable logistic regression analyses were used to identify factors associated with completing fewer away rotations.ResultsOf 141 surveys sent, 76 were completed, for a response rate of 54%. Most applicants were White, male, and matched into RO. One in 3 applicants did not have a home RO program. Most applicants completed 2 RO rotations (ie, a home rotation and an additional away rotation; range, 0-4 total rotations); RO rotations influenced the applicant rank order lists and the ultimate match result for 94% and 79% of applicants, respectively. Forty-seven percent of applicants reported being asked inappropriate questions during the interview (eg, parental or marital status). Applicants did not perceive a consistent message regarding postinterview communications from program directors. Most applicants were contacted postinterview. Interviews cost most applicants more than $5000. Thirty-seven percent of respondents reported submitting a letter of interest after the interview, hoping to improve their rank. When applying to programs, general reputation and location were the most common influential factors mentioned. When ranking programs, informal conversations with residents and program culture observations were the most common influential factors mentioned. Based on multivariable analysis, applicants who completed fewer RO rotations (including away rotations) had greater odds of matching to their home program (odds ratio [OR], 12.05; 95% CI, 1.27-206.69), lower odds of program location influencing where to apply (OR, 0.04; 95% CI, 0.003-0.37), and lower odds of the program's general reputation affecting their rank list (OR, 0.04; 95% CI, 0.001-0.47).ConclusionsThe results suggest that medical students perceive away rotations as an important influencer of their match process. Although applicants and program directors both participate in postinterview communications, interactions with residents influence rank order lists. These data may serve as an up-to-date baseline to evaluate the influence of the COVID-19 pandemic on the RO match process.
| S-EPMC8170351 | biostudies-literature
Project description:BackgroundDuring interviews, medical students may feel uncomfortable asking questions that might be important to them, such as parental leave. Parental leave policies may be difficult for applicants to access without asking the program director or other interviewers. The goal of this study is to evaluate whether parental leave information is presented to prospective residents and whether medical students want this information.MethodsFifty-two program directors (PD's) at 3 sites of a single institution received a survey in 2019 to identify whether parental leave information is presented at residency interviews. Medical students received a separate survey in 2020 to identify their preferences. Fisher exact tests, Pearson χ2 tests and Cochran-Armitage tests were used where appropriate to assess for differences in responses.ResultsOf the 52 PD's, 27 responded (52%) and 19 (70%) indicated that information on parental leave was not provided to candidates. The most common reason cited was the belief that the information was not relevant (n = 7; 37%). Of the 373 medical students, 179 responded (48%). Most respondents (92%) wanted parental leave information formally presented, and many anticipated they would feel extremely or somewhat uncomfortable (68%) asking about parental leave. The majority (61%) felt that these policies would impact ranking of programs "somewhat" or "very much."ConclusionsParental leave policies may not be readily available to interviewees despite strong interest and their impact on ranking of programs by prospective residents.
| S-EPMC8684616 | biostudies-literature
Project description:Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data-defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction.
| S-EPMC4892825 | biostudies-other
Project description:BackgroundElectronic health records (EHRs) have yet to fully capture social determinants of health (SDOH) due to challenges such as nonexistent or inconsistent data capture tools across clinics, lack of time, and the burden of extra steps for the clinician. However, patient clinical notes (unstructured data) may be a better source of patient-related SDOH information.ObjectiveIt is unclear how accurately EHR data reflect patients' lived experience of SDOH. The manual process of retrieving SDOH information from clinical notes is time-consuming and not feasible. We leveraged two high-throughput tools to identify SDOH mappings to structured and unstructured patient data: PatientExploreR and Electronic Medical Record Search Engine (EMERSE).MethodsWe included adult patients (≥18 years of age) receiving primary care for their diabetes at the University of California, San Francisco (UCSF), from January 1, 2018, to December 31, 2019. We used expert raters to develop a corpus using SDOH in the compendium as a knowledge base as targets for the natural language processing (NLP) text string mapping to find string stems, roots, and syntactic similarities in the clinical notes of patients with diabetes. We applied advanced built-in EMERSE NLP query parsers implemented with JavaCC.ResultsWe included 4283 adult patients receiving primary care for diabetes at UCSF. Our study revealed that SDOH may be more significant in the lives of patients with diabetes than is evident from structured data recorded on EHRs. With the application of EMERSE NLP rules, we uncovered additional information from patient clinical notes on problems related to social connectionsisolation, employment, financial insecurity, housing insecurity, food insecurity, education, and stress.ConclusionsWe discovered more patient information related to SDOH in unstructured data than in structured data. The application of this technique and further investment in similar user-friendly tools and infrastructure to extract SDOH information from unstructured data may help to identify the range of social conditions that influence patients' disease experiences and inform clinical decision-making.
| S-EPMC10466443 | biostudies-literature
Project description:BackgroundVideoconference interviews (VCIs) are increasingly being used in the selection process of residency program candidates across a number of medical specialties, but nevertheless remain an underutilized approach, particularly in the field of primary care.ObjectiveThis retrospective data review with cost analysis explores financial and acceptability outcomes of VCI implementation over a 9-year period.MethodsVCIs were incorporated into the recruitment process at a community-based academic family medicine residency program in 2011, whereby suitable candidates were selected for VCIs after Electronic Residency Application Service (ERAS) application review. Based on the outcome of VCI, candidates were invited via a structured interview tool for a subsequent in-person interviews to determine final rank decisions. Costs of the interview process were tracked, as well as perceptions of VCIs.ResultsVCI implementation over 9 years demonstrated a median 48% reduction of in-person interviews-or 95 applicants eliminated out of a total 195 VCIs performed. This represents a mean annual direct cost savings estimated at $9,154, equating to a 55% reduction in allocated program costs, in addition to indirect cost savings to both applicants and the program.ConclusionsCompared to exclusively in-person interviewing, the utilization of VCIs is potentially more cost-effective for residency programs and candidates, while creating a more personal experience for applicants early in the recruitment process. Limited data of acceptability among faculty and candidates is generally favorable but remains mixed.
| S-EPMC7771615 | biostudies-literature
Project description:BackgroundThe shift from in-person to virtual residency interviews may impact greenhouse gas emissions (GHGE) and costs but the direction and amount of this change is not yet clear.ObjectiveTo estimate GHGE and financial impacts of virtual interviews among applicants and programs.MethodsIn 2020-2021 we sent a postinterview survey to 1429 applicants from 7 residency programs and 1 clinical psychology program at 1 institution. The survey collected origin of travel and transit type if in-person interviews had been held and excluded responses if the applicant would not have participated in an in-person interview, or if travel type or original city was missing. We used the International Civil Aviation Organization calculator to estimate flight-related GHGE in metric tons of carbon dioxide equivalent (MTCO2e) and Google Maps to estimate ground travel, with a standard CO2e per mile. Flight, hotel, and airport taxi costs were estimated using Expedia.com, Hotels.com, Uber, and Lyft. We aggregated these data and calculated median and interquartile ranges (IQRs) for applicant GHGE and cost savings, and assumed no cost or GHGE from virtual interviews. We used Wilcoxon signed rank sum tests to compare in-person 2019-2020 and virtual 2020-2021 GME program interview budgets.ResultsThe survey response rate was 565, or 40% of applicants; 543 remained after the exclusion criteria were applied. Reduction in applicant travel due to virtual interviews led to median estimated GHGE savings of 0.47 (IQR 0.30-0.61) MTCO2e and $490 (IQR $392-$544) per applicant, per interview. Programs savings ranged from $7,615 to $33,670 for the interview season.ConclusionsVirtual interviews in 8 GME programs were associated with lower estimated GHGE and costs, for applicants and programs, compared with in-person interviews.
| S-EPMC9934836 | biostudies-literature
Project description:BACKGROUND: Residency interviews can place significant time and financial burdens on applicants. OBJECTIVE: To determine whether the use of Skype as a screening tool during interview season in a family medicine residency is cost-effective and time-efficient for the applicant and the residency program. METHODS: We surveyed 2 groups of medical students during interviews for our family medicine program. Thirty-two students were interviewed via our face-to-face, traditional interview (TI) process, and 10 students, the second group, who did not meet the program's standard interview selection criteria for TI, underwent our Skype interview (SI) process. RESULTS: Using an unpaired t test, we found that the applicants' costs of an SI were significantly less than a TI, $566 (95% confidence interval [CI] $784-$349, P < .001). Direct cash savings plus indirect salary savings to the program were $5,864, with a time savings of 7 interview days. Three of the applicants who were participants in the SI limb of the study were in our final rank order list. CONCLUSIONS: For interviewing in family medicine residencies, use of Skype may be a cost-effective and time-efficient screening tool for both the applicant and the program. Alternate uses of SI may include the time-sensitive, postmatch Supplemental Offer and Acceptance Program.
| S-EPMC3771184 | biostudies-other