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Record W2907698210 · doi:10.1111/ejn.14320

Establishing online mentorship for early career researchers: Lessons from the Organization for Human Brain Mapping International Mentoring Programme

2018· editorial· en· W2907698210 on OpenAlexaffabout
Natalia Bielczyk, Michele Veldsman, Ayaka Ando, Chiara Caldinelli, Meena M. Makary, Aki Nikolaidis, Marzia A. Scelsi, Melanie I. Stefan

Bibliographic record

VenueEuropean Journal of Neuroscience · 2018
Typeeditorial
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
FundersEngineering and Physical Sciences Research Council
KeywordsMentorshipMedical educationCareer developmentPsychologyMedicine

Abstract

fetched live from OpenAlex

Mentorship facilitates personal growth through pairing trainees with mentors who can share their expertise. In times of global integration, geographical proximity between mentors and mentees is relevant to a lesser degree. This has led to popularization of online mentoring programs. In this editorial, we introduce the history and architecture of the International Online Mentoring Programme organized by the Student and Postdoc Special Interest Group of the Organization for Human Brain Mapping. Mentorship in academia facilitates personal growth through pairing trainees with mentors who can share insight and expertise. Expertise can be purely academic, foucsed on work-life balance, personal branding and networking, or a general career advice. Mentoring has been shown to be beneficial to mentees, both in terms of objective research productivity (van Eck Peluchette & Jeanquart, 2000; Gardiner, Tiggemann, Kearns, & Marshall, 2007; Mundt, 2001; Muschallik & Pull, 2016) and subjective outcomes (e.g. self-perception as an academic, Gardiner et al., 2007; Ehrich, Hansford, & Tennent, 2004; Mundt, 2001; van Eck Peluchette & Jeanquart, 2000). Several institutions/organizations have formal in-person mentoring programmes that pair early- to mid-career researchers with mentors who are not their direct supervisors (Ehrich et al., 2004). With global integration in science, however, geographical proximity between mentors and mentees is relevant to a lesser degree. This phenomenon has led to the popularization of online mentoring programmes (Ensher, Heun, & Blanchard, 2003). Regardless of whether a mentoring programme is in-person or online, its success relies on its design (Long, 1997) and regular evaluations (Ehrich et al., 2004; Muschallik & Pull, 2016). In this editorial, we introduce the history and architecture of one such successful online mentoring programme: the International Online Mentoring Programme organized by the Student and Postdoc Special Interest Group (SP-SIG, https://www.ohbmtrainees.com/mentoring-programme/, www.ohbmtrainees.com) of the Organization for Human Brain Mapping (OHBM, www.humanbrainmapping.org). OHBM is an international society dedicated to using neuroimaging as a tool to discover the organization of the human brain. The mandate of the OHBM SP-SIG is to represent the interests of its early career researchers, which includes the planning/execution of a range of career development initiatives. A significant proportion (63%) of the OHBM community is early-career researchers: graduate students and postdoctoral fellows with less than 4 years of experience. In a recent interview, Dr. Marsel Mesulam, a founding member of OHBM, commented: “there is always this tremendous energy coming from young people, students, postdocs, and that's the driving force behind the society. It's always been that way. It was never top heavy” (Badhwar, 2017). Establishment of the SP-SIG was greenlighted by OHBM in 2014, following a proposal submitted by Dr. Sook-Lei Liew ( http://chan.usc.edu/faculty/directory/Sook-Lei_Liew), a postdoctoral fellow at the time (Figure 1). In the early years of the SP-SIG, negotiating better integration with OHBM central and having a voice at the senior executive level (i.e. OHBM Council) was crucial. In 2016, a mission of SP-SIG co-chair Dr. AmanPreet Badhwar ( https://simexp.github.io/lab-website/team.html) was to implement year-round avenues of online engagement with OHBM trainees (Figure 1). Dr. Badhwar strongly believed that an online platform would equalize trainee access to SP-SIG resources and reduce disparity due to geographic location, economic wealth, and/or ever-changing political climate. With help from JoAnn Taie, the OHBM executive director, she put forth a proposal to OHBM council requesting support for two new initiatives: (a) the International Online Mentoring Programme and (b) a Mentorship Symposium during the OHBM Annual Meeting. The SP-SIG was granted permission to host both events, and was provided with a small start-up budget. The SP-SIG launched these mentorship initiatives at the 2017 OHBM Annual Meeting (OHBM blog, 2017, Figure 1), under the joint guidance of Dr. Badhwar (Chair) and Dr. Michele Veldsman (Chair-Elect). The International Online Mentoring Programme was and remains fully non-profit, and neither participants nor coordinators receive any financial benefits for their involvement. In its first two rounds of signups the programme attracted greater than 450 participants from all around the world (Figure 2), with half of mentor-mentee pairs being able to meet in-person at the 2017 Annual Meeting. In recognition of the successes of both initiatives, the OHBM council has since doubled the SP-SIG's budget for mentoring activities. A formal evaluation of the International Online Mentoring Programme was implemented since its inception, with feedback sought on an annual basis from all participants, which has been overwhelmingly positive. We collected a feedback questionnaire from 82 participants of the programme after the completion of first round of the programme. Roughly, half of the participants met their mentoring partner during the OHBM annual meeting. On the scale 1–5, mentees gave their mentors average score of 4.06 (N = 62). Twenty-four participants declared to be positively surprised by their mentoring partner and two participants declared to be negatively surprised (for the reason that the matching was suboptimal in their opinion). More recently, we have started interviewing participants, and have publicly shared experiences from both sides of the mentoring relationship as part of an ongoing blog ging project (Bielczyk, 2018). It should be noted that the programme is constantly evolving and we continuously implement new solutions across the rounds of the programme, in response to the feedback received. Efficient strategies for matching mentors with mentees are not well explored to date (Bozeman & Feeney, 2008). In our case, we sought to minimize the demands on the participants, as well as allow relationships to be driven by the mentor-mentee partnership. With this in mind, the online application form is brief and requests the following information: contact/affiliation details, requested role (mentor, mentee, both), and number of years of professional experience, that is years spent in academia or industry upon completion of PhD. In addition, a short series of questions are posed to assess a mentee's mentoring needs, as well as career development topics a mentor feels comfortable to advise on (Box 1). Mentors are also asked to (a) specify a maximal number of mentees they are willing to mentor, (b) commit to a minimum of quarterly meetings with their mentees, and (c) commit to provide meaningful feedback on their mentee's CV and at least one application (e.g. fellowship or faculty position) upon mentee’s request. The matching algorithm used by the OHBM SP-SIG for the International Online Mentorship Programme has been kept simple, yet effective. Every mentee is assigned a mentor with at least 3 years additional professional experience. Mentees seeking jobs outside of academia are given priority for being matched with industry mentors. We also respect additional special requests from participants (e.g. trainee physicians often require mentorship from more experienced clinical academics). Since personal requests are taken into account, the matching process is semi-automatic. The programme coordinator first reviews the special requests and manually finds a match that satisfies the participants’ additional needs. In the second step of the matching process, data from the remaining participants are fed into a simple Python algorithm which automatically couples participants according to the following criteria: (a) at least 3 years difference in professional experience between a mentor and a mentee; (b) each mentee is paired with one mentor; (c) each mentor is assigned no more than the number of mentees they declared they are willing to accept. Post matching, mentors and mentees are given mutual contact information and mentees are encouraged to contact their mentor. Mentoring partnerships are given free rein to self-manage their relationship with regard to the schedule and scope of discussed topics. Interventions from the programme lead only take place when a first contact is not initiated, or when one partner asks for rematching. In the case of requests for rematching, this is exceptionally rare, with only two mentees requesting a rematch in our programme to date. In addition, mentoring pairs are encouraged to meet in-person at the OHBM annual meeting. Participants are given the option to re-apply for the programme at each new round to allow them to break unsuccessful partnerships or continue with their pairing if they are satisfied. All participants have an option to give feedback to the programme management in confidence. The OHBM board receives a report from the OHBM SP-SIG per annum, allowing the organization to track the overall progress of the programme (Figure 3). On the basis of our experience in designing and running the above-described mentoring programme, we put forth the following guidelines for launching a successful programme. The needs of the mentees should be foremost in the design and maintenance of an effective mentoring programme. Mentees will benefit most if they are encouraged to reflect on their needs in advance of applying to the programme and initiating a relationship with their mentor. Mentees should identify their expectations (Masters & Kreeger, 2017), and prepare an agenda before every meeting. The quality of the mentorship highly depends on the quality of this preparation (Iversen, Eady, & Wessely, 2014). It can help to collate a set of freely available, online preparatory materials for mentors and mentees. Ideally mentees will go on to become mentors in your programme. Early career researchers should thus be encouraged to mentor trainees junior to them in experience. Many early career researchers do not feel experienced enough to mentor and do not put themselves forward. This issue is often compounded for underrepresented groups. There is an outflow of PhD graduates towards industry (Kruger, 2018), and an associated demand for guidance from non-academic mentors. To facilitate successful transition between fields, mentoring programmes should include mentors from industry and other fields. Below we expand on this important point as it is a mistake to consider academia the traditional career path, when it in fact represents the minority of positions available to mentees. Schillebeeckx et al. (2013) reported a linear increase in the cumulative number of PhDs awarded in the fields of science and engineering from 1982 to 2011, while the number of faculty positions available in the same time interval stayed fundamentally constant. In 2010, The Royal Society analysed emerging trends in post-PhD employment sectors (The Royal Society, 2010). In the UK alone, only an estimated 0.45% of all PhD graduates are awarded a professorship, while 17% end up pursuing a research career in a non-academic setting, and a striking 53% embark on a career completely outside of science. In line with these statistics, we also saw an increase in the proportion of participants considering a career outside academia in our own mentoring programme (Figure 4 in Badhwar, Ando, Bielczyk, Scelsi, & Veldsman, 2018). Given these observations, an important responsibility of graduate training is to provide trainees exposure and preparation for careers outside of academia (e.g. industry, government) that currently are increasingly becoming available (Kruger, 2018). Similarly, mentorship programmes should recognize this shift and prepare themselves to better cater to individuals pursuing careers outside academia (Box 2). For example, mentors may want to make mentees better aware of how their own graduate work has provided them with transferable skills that can be used in both academic and non-academic career paths. How to best evaluate the success of a mentorship programme remains an open question. In the past, evaluation strategies have looked at both “objective” and “subjective” outcomes for mentees (and, to some extent, for mentors). Objective outcomes included numbers of research publications or grants produced (van Eck Peluchette & Jeanquart, 2000; Gardiner et al., 2007; Mundt, 2001; Muschallik & Pull, 2016). Subjective measures included self-reported changes in mentees’ work patterns, or feelings of being supported or satisfied with their career progress (van Eck Peluchette & Jeanquart, 2000; Ehrich et al., 2004; Gardiner et al., 2007; Mundt, 2001). While useful for some purposes, “objective” measures of academic success can be problematic in several ways. First, research productivity as measured by bibliometric indicators or grant income can vary a lot between subject areas (Bishop, 2014; Kreiman & Maunsell, 2011) and is complicated by other factors, such as gender (Bonham & Stefan, 2017; Bornmann, Mutz, & Daniel, 2007; King, Bergstrom, Correll, Jacquet, & West, 2017; West, Jacquet, King, Correll, & Bergstrom, 2013), social capital (Li, Liao, & Yen, 2013), and possibly even stochastic fluctuation (Michalska-Smith & Allesina, 2017). In addition, they may be an indicator of volume, but not necessarily of the quality of academic work (Michalska-Smith & Allesina, 2017). Second, success in academia is not a straight line (Way, Morgan, Clauset, & Larremore, 2017), and definitely not rapid. Many academics have talked about the role of failure (Haushofer, 2016; Stefan, 2010), and that it takes years to build a successful academic career. Most formal mentorship programmes are time-limited, but the impact of good mentoring will continue for years beyond the formal end of the mentoring relationship (Karcher, Kuperminc, Portwood, Sipe, & Taylor, 2006). There is, therefore, a need for long-term research on the impact of early-career mentoring on the future professional lives and career satisfaction of mentees. Crucially, this includes careers outside of academia. Defining success only in terms of success within academia is too short-sighted. Nowadays, the academic career pathway is no longer the default pathway (Kruger, 2018), and most science trainees go on to successful and fulfilling careers outside of academia (Turk-Bicakci, Berger, & Haxton, 2014). We need measures to evaluate the preparedness of mentees for careers outside of academia, and of measuring the impact of mentorship programmes on mentees’ success and satisfaction in a wide range of possible careers. In addition, it is important to evaluate the impact of mentorship programmes on mentors in order to understand what support structures they need, and how they can maximize the benefits of acting as mentors (Ghosh & Reio, 2013). Developing tools to assess the long-term impact of mentoring programmes both on mentees and mentors will provide insights into how programmes can be tailored for optimal impact. Moreover, one sign of success of any mentoring programme is attention in the community, and followers gained. Specifically, with respect to our mentoring programme, blog posts related to the SP-SIG's activities (Badhwar et al., 2018, OHBM 2017; Veldsman & Vij, 2017) are regularly published by the OHBM Communications Committee, and reach a diverse international audience. The readership includes OHBM members, non-member academics, as well as the general public. As a result, the SIGs activities, in particular, its focus on mentorship, has caught the attention of organizations worldwide, including the Canadian Consortium on Neurodegeneration in Aging (CCNA, http://ccna-ccnv.ca/). In particular, the Training and Capacity Building team of the CCNA, whose mission is to develop future research leaders in the area of age-related neurodegenerative conditions, is actively interested in putting together a Canadian mentorship program. The CCNA Trainee Society ( http://ccna-ccnv.ca/2018-trainee-society-executive-committee-members/) was thus officially established in 2018, and is being chaired by Dr. Badhwar, who hopes to adopt some of the SIG's mentoring principles to fit the diverse, and interdisciplinary needs of the CCNA trainees (e.g. specialties ranging from social sciences to health sciences). In order to be truly successful, mentoring programmes need to also consider questions around access, representation, and equality. Under-represented groups in Science, Technology, Engineering, and Mathematics (STEM) include women, people of colour, and people with disabilities (National Science Foundation, 2017), among others. They face challenges around systematic discrimination (O'Brien, McAbee, Hebl, & Rodgers, 2016), unconscious bias (Nosek et al., 2007), stereotype threat (Schmader, Johns, & Forbes, 2008), and a lack of role models (see, for instance, Gardiner et al., 2007). Mentoring programmes can help create a positive environment, provide contact to role models and support career development for scientists from under-represented groups. Indeed, specific mentoring programmes exist for under-represented groups, including women in academia (for an example, see Gardiner et al., 2007), or academics of colour (for an example, see Chan, 2008). While bespoke mentoring programmes are extremely important and useful, their existence does not take away responsibility for more general mentoring programmes to be mindful of the specific needs of minority scientists. Programmes that have been successful in this area should share best practice examples in order to help uncover helpful design elements. In the end, mentorship through one-on-one expert-guided discussion can be an incredible career accelerator and realizing its value will improve mentees’ overall development. Science is collaborative, creative, and heavily depends on the human element - which makes mentoring an integral part of research. We would like to thank to the Organization for Human Brain Mapping for supporting for this project, as well as to the fellow OHBM members for encouragement. We would also like to thank all current and past participants of the OHBM Online Mentoring Programme. For all the parties involved, this a non-profit activity. Therefore, we are grateful for the time and effort the participants have invested working on behalf of the programme. The authors declare no conflict of interest.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.015
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.221
GPT teacher head0.406
Teacher spread0.185 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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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Citations11
Published2018
Admission routes2
Has abstractyes

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