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Record W4386338940 · doi:10.5858/arpa.2022-0272-le

Depression and Suicidality in Pathology and Laboratory Medicine: We Should Be Concerned

2022· article· en· W4386338940 on OpenAlexaff
Vinita Parkash, Stephen J. Smith

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsBurnoutMental healthMedicineDepression (economics)PsychiatrySuicidal ideationDisengagement theorySpecialtyPsychologySuicide preventionPoison controlClinical psychologyMedical emergencyGerontology

Abstract

fetched live from OpenAlex

This note is a plea, a call to action to all of us in this specialty, but especially to the leadership. We need to discuss depression and suicide in pathology and laboratory medicine. Absent this discussion, we risk losing one of our own (again) to suicide, and we put our trainees and staff at risk of suffering the traumatic loss of a work-family member to suicide. When this happens, perhaps the astute leader will send out a supportive email and arrange for a visit from a mental health professional. Of course, none of us will avail ourselves of this service—we do not seek mental health assistance in private—and we are not about to do it in public. Many will suffer long-term effects ranging from prolonged grief reactions to full-blown depression, deterioration in work performance, burnout and disengagement, increased substance abuse, loss of personal relationships, and perhaps even attempted suicide, among others.That healthcare workers have an increased rate of suicidal ideation is broadly recognized. Emerging data suggest that our field may be at higher risk than other specialties. It has been documented that the field of pathology has the highest suicidal ideation among specialties at 13%,1 and low resilience levels.2 We have high depression rates, despite having “low burnout rates,”3 suggesting that the low burnout rates may be spurious. Those burned out are likely self-excluding from surveys (a “not missing at random” bias). Data document introversion4,5 and depression-type symptoms5,6 among pathologists, factors also linked to suicidality.Suicidality has long been known to have social roots, as identified in Durkheim’s7 seminal sociological study “Le Suicide,” and is thus heavily moderated by an individual’s social integration and regulation into a group. Thus, the field of pathology needs to look at itself and consider what in our specialty’s social structure puts our members at risk. Possibly, we receive a subset of medical students at risk. Our own (and others’) stereotyping of ourselves (scientific, factual, cold) may be a hard landing spot for many looking to belong.8,9 The climate is undoubtedly disheartening, with an increasing commoditization in pathology; the oft-repeated minimization of the specialty (“pathology professionals are not medical professionals”); the stigma and perceived low prestige of the specialty;10,11 the prevalent concern that as a non–patient contact specialty, pathologists will soon be obsolete and replaced by computers.9 The majority of us do not see the direct impact of our work for patients; rare is the case in which we hear the protective “thank you” that our clinical colleagues hear from patients. A sense of anomie, especially after the long slog and financial burdens of medical school, is not entirely misplaced.Chair persons and residency directors in pathology need to put depression and suicide central on their “well-being of the field” agenda, and we need to develop pathology-specific strategies to target the issue.12 Universal strategies—strategies designed to influence everyone (eg, organizational “awareness” strategies)—are not enough, not for a subspecialty “at risk” and not for one that gets lost in the larger structure of medicine. One of the authors, who is contacted not infrequently by individuals about suicide, has concern that suicide risk is seemingly higher in US medical graduates.13 This hypothesis should be explored most expeditiously, as it is consistent with data that recent immigrants show a lower incidence of suicide relative to long-term residents of a country. Implicated in this question are concerns of how US medical graduates adjust to the practice of pathology or develop resilience during residency training. How do these trainees adjust to a social structure where the plurality of cotrainees and attending physicians are culturally non-American, especially if trainees have chosen pathology because advisors have suggested pathology because it is “quiet, undemanding, and non–patient contact”?Whatever the drivers, we are morally obligated to discuss depression and suicide in pathology much in the way that other high-risk professions—such as law enforcement, firefighting, and the armed services—are so bound. We need to determine the true risk of depression and subsequent suicide in the field of pathology, and then develop programs to identify, help, and support those at risk. Regrettably, but necessarily, there are also no well-developed guidelines for supporting members of the profession when suicide occurs. We have provided a rough outline of recommendations to accomplish these goals (Table).Action is necessary now—a pathology program lost another recently—not 4 years since we lost one of ours. Pathologists need to embrace the spirit of the Lorna Breen Law16 and take active steps to embrace a wellness leadership process and culture within our profession. The field and practice of pathology can be isolating in healthcare systems; our leadership should proactively work to avoid isolationism in medicine and more effectively engage both patients and clinicians so as to reflect the value and impact of the work of pathologists.

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)0.007
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.014
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.037
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0050.009
Open science0.0010.002
Research integrity0.0140.018
Insufficient payload (model declined to judge)0.0060.002

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 head0.070
GPT teacher head0.426
Teacher spread0.356 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2022
Admission routes1
Has abstractyes

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