Prevalence of Depression, Depressive Symptoms, and Suicidal Ideation Among Medical Students: A Systematic Review and Meta-Analysis

Lisa S Rotenstein; Marco A Ramos; Matthew Torre; J Bradley Segal; Michael J Peluso; Constance Guille; Srijan Sen; Douglas A Mata

doi:10.1001/jama.2016.17324

. Author manuscript; available in PMC: 2017 Sep 26.

Published in final edited form as: JAMA. 2016 Dec 6;316(21):2214–2236. doi: 10.1001/jama.2016.17324

Prevalence of Depression, Depressive Symptoms, and Suicidal Ideation Among Medical Students

A Systematic Review and Meta-Analysis

Lisa S Rotenstein ¹, Marco A Ramos ¹, Matthew Torre ¹, J Bradley Segal ¹, Michael J Peluso ¹, Constance Guille ¹, Srijan Sen ¹, Douglas A Mata ¹

PMCID: PMC5613659 NIHMSID: NIHMS875825 PMID: 27923088

Abstract

IMPORTANCE

Medical students are at high risk for depression and suicidal ideation. However, the prevalence estimates of these disorders vary between studies.

OBJECTIVE

To estimate the prevalence of depression, depressive symptoms, and suicidal ideation in medical students.

DATA SOURCES AND STUDY SELECTION

Systematic search of EMBASE, ERIC, MEDLINE, psycARTICLES, and psycINFO without language restriction for studies on the prevalence of depression, depressive symptoms, or suicidal ideation in medical students published before September 17, 2016. Studies that were published in the peer-reviewed literature and used validated assessment methods were included.

DATA EXTRACTION AND SYNTHESIS

Information on study characteristics; prevalence of depression or depressive symptoms and suicidal ideation; and whether students who screened positive for depression sought treatment was extracted independently by 3 investigators. Estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using stratified meta-analysis and meta-regression.

MAIN OUTCOMES AND MEASURES

Point or period prevalence of depression, depressive symptoms, or suicidal ideation as assessed by validated questionnaire or structured interview.

RESULTS

Depression or depressive symptom prevalence data were extracted from 167 cross-sectional studies (n = 116 628) and 16 longitudinal studies (n = 5728) from 43 countries. All but 1 study used self-report instruments. The overall pooled crude prevalence of depression or depressive symptoms was 27.2% (37 933/122 356 individuals; 95% CI, 24.7% to 29.9%, I² = 98.9%). Summary prevalence estimates ranged across assessment modalities from 9.3% to 55.9%. Depressive symptom prevalence remained relatively constant over the period studied (baseline survey year range of 1982–2015; slope, 0.2% increase per year [95% CI, −0.2% to 0.7%]). In the 9 longitudinal studies that assessed depressive symptoms before and during medical school (n = 2432), the median absolute increase in symptoms was 13.5% (range, 0.6% to 35.3%). Prevalence estimates did not significantly differ between studies of only preclinical students and studies of only clinical students (23.7% [95% CI, 19.5% to 28.5%] vs 22.4% [95% CI, 17.6% to 28.2%]; P = .72). The percentage of medical students screening positive for depression who sought psychiatric treatment was 15.7% (110/954 individuals; 95% CI, 10.2% to 23.4%, I² = 70.1%). Suicidal ideation prevalence data were extracted from 24 cross-sectional studies (n = 21 002) from 15 countries. All but 1 study used self-report instruments. The overall pooled crude prevalence of suicidal ideation was 11.1% (2043/21 002 individuals; 95% CI, 9.0% to 13.7%, I² = 95.8%). Summary prevalence estimates ranged across assessment modalities from 7.4% to 24.2%.

CONCLUSIONS AND RELEVANCE

In this systematic review, the summary estimate of the prevalence of depression or depressive symptoms among medical students was 27.2% and that of suicidal ideation was 11.1%. Further research is needed to identify strategies for preventing and treating these disorders in this population.

Studies have suggested that medical students experience high rates of depression and suicidal ideation.¹ However, estimates of the prevalence of depression or depressive symptoms among students vary across studies from 1.4% to 73.5%,^2,3 and those of suicidal ideation vary from 4.9% to 35.6%.^4,5 Studies also report conflicting findings about whether student depression and suicidality vary by undergraduate year, sex, or other characteristics.^6–11

Reliable estimates of depression and suicidal ideation prevalence during medical training are important for informing efforts to prevent, treat, and identify causes of emotional distress among medical students,¹² especially in light of recent work revealing a high prevalence of depression in resident physicians.¹³ We conducted a systematic review and meta-analysis of published studies of depression, depressive symptoms, and suicidal ideation in undergraduate medical trainees.

Methods

Search Strategy and Study Eligibility

Two authors (M.A.R. and D.A.M.) independently identified cross-sectional and longitudinal studies published prior to September 17, 2016, that reported on the prevalence of depression, depressive symptoms, or suicidal ideation in medical students by systematically searching EMBASE, ERIC, MEDLINE, psycARTICLES, and psycINFO. In addition, the authors screened the reference lists of identified articles and corresponded with study investigators using the approaches implied by the Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology reporting guidelines.^14,15

For the database searches, terms related to medical students and study design were combined with those related to depression and suicide without language restriction (complete details of the search strategy appear in eMethods 1 in the Supplement). Included studies (1) reported data on medical students, (2) were published in peer-reviewed journals, and (3) used a validated method to assess for depression, depressive symptoms, or suicidal ideation.¹⁶ A third author (L.S.R.) resolved discrepancies by discussion and adjudication.

Data Extraction and Quality Assessment

Three authors (L.S.R., M.T., and J.B.S.) independently extracted the following data from each article using a standardized form: study design; geographic location; years of survey; year in school; sample size; average age of participants; number and percentage of male participants; diagnostic or screening method used; outcome definition (ie, specific diagnostic criteria or screening instrument cutoff); and reported prevalence estimates of depression, depressive symptoms, or suicidal ideation. Whether students who screened positive for depression sought psychiatric or other mental health treatment also was extracted. When there were studies involving the same population of students, only the most comprehensive or recent publication was included.

The same 3 authors independently assessed the risk of bias of these nonrandomized studies using a modified version of the Newcastle-Ottawa scale, which assesses sample representativeness and size, comparability between respondents and nonrespondents, ascertainment of depressive or suicidal symptoms, and thoroughness of descriptive statistics reporting (complete details regarding scoring appear in eMethods 2 in the Supplement).¹⁷ Studies were judged to be at low risk of bias (≥3 points) or high risk of bias (<3 points). A fourth author (D.A.M.) resolved discrepancies through discussion and adjudication.

Data Synthesis and Analysis

Prevalence estimates of depression or depressive symptoms and suicidal ideation were calculated by pooling the study-specific estimates using random-effects meta-analyses that accounted for between-study heterogeneity.¹⁸ The same approach was used to estimate the summary percentage of students screening positive for depression who sought treatment. When studies reported point prevalence estimates made at different periods within the year, the overall period prevalence was used. Standard χ² tests and the I² statistic (ie, the percentage of variability in prevalence estimates due to heterogeneity rather than sampling error, or chance, with values ≥75% indicating considerable heterogeneity) were used to assess between-study heterogeneity.^19,20

Sensitivity analyses were performed by serially excluding each study to determine the influence of individual studies on the overall prevalence estimates. Results from studies grouped according to prespecified study-level characteristics were compared using stratified meta-analysis (for diagnostic criteria or screening instrument cutoff, study design, undergraduate level, continent or region, country, and Newcastle-Ottawa Scale components) or random-effects meta-regression (for year of baseline survey, age, and sex).^21,22 To isolate associations within the medical school experience from associations with assessment tools, an analysis restricted to longitudinal studies reporting both pre- and intramedical school depressive symptom prevalence estimates was performed.

Bias secondary to small study effects was investigated using funnel plots and the Egger test.^23,24 All analyses were performed using R version 3.2.3 (R Foundation for Statistical Computing).²⁵ Statistical tests were 2-sided and used a significance threshold of P < .05.

Results

Study Characteristics

One hundred ninety-five studies^{2–11,26–210} involving a total of 129 123 individuals in 47 countries were included in the analysis (Figure 1). The median number of participants per study was 336 (range, 44–10 140). One hundred sixty-seven cross-sectional studies^{2–4,6–9,11,26–184} (n = 116 628) and 16 longitudinal studies^10,196–210 (n = 5728) in 43 countries reported on depression or depressive symptom prevalence (Table 1). Twenty-four cross-sectional studies (n = 21 002) in 15 countries reported on the prevalence of suicidal ideation (Table 2).^{4,5,34,62,65,73,74,79,112,160,165,167,174,185–195}

Table 1.

Selected Characteristics of the 183 Studies of Depression or Depressive Symptoms^a

Source	Country	Survey Years	Year of Training	No. of Students	Age, y	Men, No. (%)	Instrument and Cutoff Score
Bore et al,⁵² 2016	Australia	2013	1–5	127	Mean (SD): 23 (5.6)	32 (25.6)	DASS-21 ≥10
De Sousa Lima et al,⁶⁷ 2010	Brazil	2001	1–4	80	Range: 18–30	45 (56.3)	BDI ≥10
de Melo Cavestro and Rocha,⁶⁵2006	Brazil	2003	1–6	213	Mean (SD): 23.1 (2.3)	109 (51.2)	MINI ≥ DSM IV criteria
Amaral et al,³⁹ 2008	Brazil	2006	1–6	287	Mean: 21.3	131 (45.7)	BDI ≥10
Costa et al,⁶¹ 2012	Brazil	2008	5, 6	84	NR	NR	BDI ≥10
Serra et al,¹⁴⁷ 2015	Brazil	2012	1–6	657	Mean: 22.7	255 (38.8)	BDI ≥10
Castaldelli-Maia et al,⁵⁵ 2012	Brazil	2001–2006	1–6	465	NR	NR	BDI ≥15
Alexandrino-Silva et al,³⁴ 2009	Brazil	2006–2007	1–6	336	Mean (SD): 22.4 (2.5)	105 (31)	BDI ≥21
Paro et al,¹³⁰ 2010	Brazil	2006–2007	1–6	352	Mean (SD): 22.3 (2.4)	134 (38.4)	BDI >9
Bassols et al,⁴⁹ 2014	Brazil	2010–2011	1, 6	232	Mean (SD): 23.1 (3.2)	117 (50.4)	BDI ≥11
Del-Ben et al,²⁰⁰ 2013	Brazil	NR	1	85	Mean (SD): 19.1 (1.6)	58 (68.2)	BDI ≥10
Leão et al,⁶⁶ 2011	Brazil	NR	6	111	Mean (SD): 24.6 (1.4)	87 (56)	BDI ≥12
Hirata et al,⁸⁷ 2007	Brazil	NR	1–2	161	Mean (SD): 22.1 (2.1)	77 (47.8)	BDI >10
Baldassin et al,⁴⁷ 2008	Brazil	NR	1–6	481	Mean (SD): 21.9 (2.4)	195 (40.5)	BDI ≥10
Matheson et al,¹¹⁷ 2016	Canada	2013	1–4	232	NR	NR	K-10 ≥20
Helmers et al,⁸⁴ 1997	Canada	1994–1995	1–4	356	Mean (SD): 23.5 (2.6)	185 (52)	DSP >50
Berner et al,⁵¹ 2014	Chile	2012	1–5	384	Mean (SD): 20.8 (1.8)	224 (58.3)	GHQ-12 ≥5
Tang,¹⁶³ 2005	China	2003	2	121	NR	0	Zung-SDS ≥50
Shen et al,¹⁵¹ 2009	China	2006	1	313	Mean (SD): 23.8 (1.8)	NR	Zung-SDS ≥53
Wan et al,⁴ 2012	China	2010	1–5	4063	Mean (SD): 20.5 (1.1)	1895 (46.6)	Zung-SDS ≥50
Sobowale et al,¹⁶⁰ 2014	China	2012	2–3	348	NR	NR	PHQ-9 ≥10
Shi et al,¹⁵⁴ 2015	China	2014	1–5	1738	Mean (SD): 21.4 (1.6)	586 (33.7)	CES-D ≥16
Shi et al,¹⁵³ 2016	China	2014	1–7	2925	Mean (SD): 21.7 (2)	1028 (35.2)	CES-D ≥16
Pan et al,¹²⁹ 2016	China	2013–2014	1–5	8819	Mean (SD): 20.7 (1.6)	3415 (37.9)	BDI ≥14
Liao et al,¹¹⁰ 2010	China	NR	1	487	Mean (SD): 18.5 (0.8)	181 (37.4)	Zung-SDS ≥50
Sun et al,¹⁶² 2011	China	NR	1–2	10140	Mean (SD): 19.6 (1.3)	4680 (46.2)	BDI ≥10
Yang et al,⁶ 2014	China	NR	1–5	1137	Range: 17–24	624 (54.9)	SCL-90 >2
Pinzón-Amado et al,¹³⁷ 2013	Colombia	2006	1–6	973	Mean (SD): 20.3 (2.3)	414 (43)	CES-D ≥16
Amir and Gillany,⁴⁰ 2010	Egypt	2010	1–6	311	Mean (SD): 20.7 (2.4)	164 (52.7)	HADS-D ≥8
Ibrahim and Abdelreheem,⁸⁹ 2015	Egypt	2013	1	164	NR	82 (50)	BDI ≥17
Abdel Wahed and Hassan,²⁷ 2016	Egypt	2015	1–4	442	Mean (SD): 20.2 (1.9)	172 (38.9)	DASS-21 ≥10
Eller et al,¹⁸⁴ 2006	Estonia	2003	1–6	413	Mean (SD): 21.3 (2.5)	95 (23)	EST-Q ≥12
Vaysse et al,¹⁷¹ 2014	France	2012–2013	2	197	Mean (SD): 19.7 (0.9)	79 (39.9)	HADS-D ≥8
Prinz et al,² 2012	Germany	2008	4, 5	73	NR	54 (74)	HADS-D ≥11
Voltmer et al,¹⁷² 2012	Germany	2010–2011	1, 2, 5	153	Mean (SD): 25.6 (3.1)	44 (28.7)	HADS-D ≥11
Kötter et al,¹⁰⁷ 2014	Germany	2011–2012	1	350	Mean (SD): 20.9 (3.2)	118 (33.7)	HADS-D ≥8
Wege et al,¹⁷⁴ 2016	Germany	2012–2013	1	590	Mean (SD): 21.1 (3.9)	177 (29.9)	PHQ-9 >10
Jurkat et al,¹⁰⁰ 2011	Germany	NR	1, 4	651	NR	252 (38.7)	BDI ≥11
Kohls et al,¹⁰⁵ 2012	Germany	NR	NR	419	NR	122 (29.1)	ADS-K >17
Nasioudis et al,¹²⁶ 2015	Greece	2013	1–3	146	Mean (SD): 19.8 (1)	91 (62.3)	Zung-SDS >45
Chan,⁵⁷ 1992	Hong Kong	NR	1	95	Mean (range): 19.6 (18–29)	64 (67.4)	BDI ≥19
Chan,⁵⁶ 1991	Hong Kong	NR	1–4	335	Mean (SD): 20.1 (1.6)	239 (71.3)	BDI ≥10
Kumar et al,²⁶ 2012	India	2008	1–4	400	NR	217 (54.3)	BDI ≥10
Gupta and Basak,⁸² 2013	India	2008	1–5	150	Range: 18–26	104 (69.3)	BDI ≥10
David and Hamid Hashmi,⁶⁴ 2013	India	2012	1	128	Mean (range): 17.9 (17–21)	46 (35.9)	BDI ≥17
Vankar et al,¹⁷⁰ 2014	India	2012	1–4	331	Mean (SD): 19.8 (1.4)	178 (53.8)	PHQ-9 ≥10
Iqbal et al,⁹⁵ 2015	India	2012	1–5	353	Mean (SD): 20.8 (1.5)	145 (41.1)	DASS-42 ≥10
Ali and Vankar,³⁷ 1994	India	NR	1–3	215	Mean (range): 19.6 (17–25)	132 (61.4)	Zung-SDS ≥50
Supe,³ 1998	India	NR	1–3	238	NR	128 (53.8)	Zung-SDS ≥40
Sidana et al,¹⁵⁶ 2012	India	NR	1–5	237	NR	126 (53.2)	PHQ-9 ≥10
Bayati et al,⁹ 2009	Iran	2008	NR	172	NR	NR	GHQ-28 ≥23
Akbari et al,³¹ 2014	Iran	2011	NR	138	NR	NR	GHQ-28 >6
Farahangiz et al,⁷⁶ 2016	Iran	2014	1–4	208	Mean (SD): 20.7 (1.1)	82 (39.4)	GHQ-28 ≥23
Vahdat Shariatpanaahi et al,¹⁵⁰ 2007	Iran	2004–2005	NR	192	Mean (SD): 24.5 (1.6)	0	BDI ≥10
Aghakhani et al,²⁹ 2011	Iran	NR	NR	628	Mean (SD): 22 (0.3)	334 (53.2)	BDI ≥10
Ashor,⁴³ 2012	Iraq	2010–2011	1–6	269	NR	147 (54.6)	Zung-SDS ≥50
Lupo and Strous,¹¹¹ 2011	Israel	NR	1–6	119	Mean (SD): 25.1 (2.8)	NR	BDI-II ≥10
Peleg-Sagy and Shahar,¹³¹ 2012	Israel	NR	1–7	60	Mean (SD): 27 (2.9)	0	CES-D ≥16
Peleg-Sagy and Shahar,²⁰⁵ 2013	Israel	NR	1, 4, 7	192	Mean (SD): 26.6 (2.6)	0	CES-D ≥16
Yoon et al,¹⁷⁹ 2014	Korea	NR	2, 3, 5	174	Mean (SD): 23.3 (2.8)	96 (55.2)	PHQ-9 ≥10
Naja et al,¹²⁵ 2016	Lebanon	2014	2–5	340	NR	145 (42.6)	PHQ-9 ≥10
Mehanna and Richa,¹¹⁹ 2006	Lebanon	2003–2004	1–6	356	NR	NR	BDI ≥8
Bunevicius et al,⁵³ 2008	Lithuania	2005	NR	338	Mean (SD): 21 (1)	73 (21.6)	HADS-D ≥8
Mancevska et al,¹¹⁴ 2008	Macedonia	2007–2008	1–2	354	NR	120 (33.9)	BDI ≥17
Sherina et al,¹⁵² 2004	Malaysia	2002	1–5	396	Mean (range): 21.6 (18–29)	152 (38.4)	GHQ-12 ≥4
Tan et al,¹⁶⁷ 2015	Malaysia	2013	1–5	537	NR	188 (35)	PHQ-9 ≥10
Yusoff et al,⁴⁶ 2011	Malaysia	2008	5	92	NR	25 (27.2)	BDI ≥9
Yusoff,¹⁸¹ 2013	Malaysia	2009–2010	1	194	NR	66 (34)	DASS-21 ≥14
Yusoff et al,²¹⁰ 2013	Malaysia	2010–2011	1	170	NR	57 (32.8)	DASS-21 ≥10
Saravanan and Wilks,¹⁴⁵ 2014	Malaysia	NR	1–5	358	NR	177 (49.4)	DASS-21 ≥10
Manaf et al,¹¹³ 2016	Malaysia	NR	2–5	206	Mean (SD): 19.5 (2.6)	0	PHQ-9 ≥5
Guerrero López et al,⁷ 2013	Mexico	2007	1	455	Mean (SD): 18.3 (1.2)	139 (30.5)	CES-D ≥16
Romo-Nava et al,¹⁴² 2016	Mexico	2011	1–5	1068	NR	421 (39.4)	PHQ-9 ≥10
Melo-Carrillo et al,¹²⁰ 2012	Mexico	2006–2007	1–4	302	NR	NR	BDI ≥10
Nava et al,¹²⁷ 2013	Mexico	2010–2011	1, 5	1871	NR	707 (37.9)	PHQ-9 ≥10
El-Gilany et al,⁷⁵ 2008	Multiple	2007	1–6	588	Mean: 20.8	588 (100)	HADS-D ≥12
Seweryn et al,¹⁴⁸ 2015	Multiple	2015	1–6	1262	Median: 22	345 (27.3)	BDI ≥10
Sreeramareddy et al,¹⁶¹ 2007	Nepal	2005–2006	NR	407	Mean (SD): 20.7 (1.8)	227 (55.8)	GHQ-12 ≥4
Basnet et al,⁴⁸ 2012	Nepal	2008–2009	1, 3	94	Mean (SD): 21.2 (1.7)	57 (60.6)	Zung-SDS ≥50
Borst et al,¹⁹⁷ 2015	Netherlands	2010–2011	1–6	951	Mean (SD): 23 (2.6)	279 (29)	BSI-DEP >0.41
Carter et al,⁵⁴ 2014	New Zealand	2010	4–6	198	Mean (SD): 23.5 (2.1)	75 (38.1)	DASS-21 ≥14
Samaranayake and Fernando,¹⁴⁴ 2011	New Zealand	2008–2009	3	255	Median (range): 20 (18–36)	123 (48.2)	PHQ-9 ≥10
Oku et al,¹²⁸ 2015	Nigeria	2010	1, 2, 4, 5	451	Mean (SD): 23.4 (4.4)	288 (63.8)	GHQ-12 ≥4
Aniebue and Onyema,⁴² 2008	Nigeria	2008–2009	NR	262	Mean (SD): 23.7 (2.7)	133 (50.8)	Zung-SDS ≥50
Rab et al,¹³⁸ 2008	Pakistan	2002	1–5	87	Mean (SD): 20.7 (1.9)	0	HADS-D ≥8
Jadoon et al,⁹⁷ 2010	Pakistan	2008	1–5	482	Mean (SD): 20.7 (1.8)	257 (53.3)	AKUADS ≥19
Marwat,¹¹⁶ 2013	Pakistan	2011	3	166	NR	73 (28.7)	Zung-SDS ≥50
Imran et al,⁹² 2016	Pakistan	2013	NR	527	Mean (SD): 20.2 (2.3)	282 (53.5)	GHQ-12 >15
Khan et al,¹⁰³ 2015	Pakistan	2014	3	110	Mean: 21	55 (50)	HADS-D ≥8
Ali et al,³⁶ 2015	Pakistan	2014	1–2	182	NR	114 (62.6)	AKUADS >19
Rizvi et al,¹⁴⁰ 2015	Pakistan	2014	1–5	66	Mean (SD): 22.2 (1.3)	28 (40)	DASS-42 ≥10
Alvi et al,³⁸ 2010	Pakistan	2007–2008	2–5	279	Mean (SD): 21.4 (1.4)	77 (27.6)	BDI-II ≥14
Waqas et al,¹⁷³ 2015	Pakistan	2014–2015	1–5	409	Mean (SD): 19.9 (1.3)	123 (30)	HADS-D ≥8
Inam et al,⁹³ 2003	Pakistan	NR	1–4	189	NR	60 (31.7)	AKUADS ≥19
Khan et al,¹¹ 2006	Pakistan	NR	1–5	142	Mean (SD): 21.3 (1.9)	59 (41.5)	AKUADS ≥19
Perveen et al,¹³³ 2016	Pakistan	NR	1,5	1000	NR	431 (43.1)	QIDS ≥9
Mojs et al,¹²² 2015	Pakistan	NR	NR	477	NR	NR	KADS ≥6
Phillips et al,¹³⁴ 2006	Panama	2005	1–6	122	NR	63 (51.6)	Zung-SDS ≥50
Pereyra-Elías et al,¹³² 2010	Peru	2010	1–4	590	Mean (SD): 19 (2.5)	184 (28.9)	Zung SF ≥22
Valle et al,¹⁶⁹ 2013	Peru	2010	1–6	615	Mean (SD): 22 (4.5)	357 (58)	Zung-SDS ≥50
Walkiewicz et al,²⁰⁹ 2012	Poland	1999–2005	2	178	NR	NR (69)	MMPI-D >70
Adamiak et al,²⁸ 2004	Poland	NR	2, 4	263	Mean: 22.3	NR	BDI ≥12
Inam,⁹⁴ 2007	Saudi Arabia	2002	1–3	226	NR	149 (65.9)	AKUADS ≥19
Aziz et al,⁴⁵ 2011	Saudi Arabia	2010	1–5	295	Mean (SD): 21.6 (1.7)	0	BDI-II ≥20
AlFaris et al,³⁵ 2014	Saudi Arabia	2011	1–2	543	NR	340 (62.6)	BDI-II ≥14
Ibrahim et al,⁹¹ 2013	Saudi Arabia	2012	2–6	558	Mean (SD): 21.7 (1.8)	300 (50.3)	HADS-D ≥11
Ibrahim et al,⁹⁰ 2013	Saudi Arabia	2010–2011	2–6	450	Mean (SD): 21.1 (1.4)	0	HADS-D ≥11
Kulsoom and Afsar,¹⁰⁸ 2015	Saudi Arabia	2012–2013	1–5	442	NR	274 (62)	DASS-21 ≥14
Al-Faris et al,⁸ 2012	Saudi Arabia	NR	1–5	797	Mean (SD): 21.6 (1.6)	590 (74)	BDI ≥10
Saeed et al,¹⁴³ 2016	Saudi Arabia	NR	NR	80	Mean (SD): 25.9 (1.5)	55 (68.8)	K-10 ≥20
Ristić-Ignjatović et al,¹³⁹ 2013	Serbia	2002–2012	4	615	Mean (SD): 23.6 (1.5)	239 (36.8)	BDI ≥10
Miletic et al,¹²¹ 2015	Serbia	2012–2013	1, 3, 6	1294	Mean (SD): 21.9 (2.8)	500 (38.6)	PHQ-9 ≥10
Pillay et al,¹³⁶ 2016	South Africa	NR	1–5	230	Mean: 21	66 (28.7)	Zung-SDS >30
Jeong et al,⁹⁹ 2010	South Korea	2008	1–2	89	NR	0	CES-D ≥16
Kim and Roh,¹⁰⁴ 2014	South Korea	2011	1–2	122	NR	92 (75.4)	BDI ≥10
Choi et al,⁶⁰ 2015	South Korea	2013	1–4	534	NR	308 (57.7)	BDI-II ≥17
Roh et al,¹⁴¹ 2009	South Korea	2006–2007	1–4	7357	NR	NR	BDI ≥16
Dahlin et al,⁶³ 2011	Sweden	2006	NR	408	Median (range): 24 (22–27)	157 (36.5)	MDI >27
Dahlin et al,⁶² 2005	Sweden	2001–2002	1, 3, 6	309	Mean (range): 26.1 (18–44)	126 (39.8)	DSM-IV criteria A and C
Kongsomboon,¹⁰⁶ 2010	Thailand	2008	1–6	593	Mean (range): 20.7 (15–27)	243 (41)	HRSRS ≥25
Angkurawaranon et al,⁴¹ 2016	Thailand	2013	2–6	1014	Mean (SD): 20.8 (1.5)	476 (46.9)	PHQ-9 ≥9
N Wongpakaran and T Wongpakaran,¹⁷⁷ 2010	Thailand	NR	1–5	368	Mean (SD): 20.8 (1)	155 (42)	TDI >35
Youssef,¹⁸⁰ 2016	Trinidad and Tobago	NR	1–3	381	Mean (SD): 22.4 (3)	126 (0.3)	PHQ-9 ≥10
Güleç et al,⁸¹ 2005	Turkey	1993	1–6	668	Mean (SD): 21.1 (2)	658 (96.2)	BDI ≥17
Akvardar et al,³² 2003	Turkey	2002	1, 6	447	Mean (SD): 21 (1.2)	272 (39.1)	HADS-D ≥7
Marakoğlu et al,¹¹⁵ 2006	Turkey	2006	1–2	331	Mean (SD): 19.5 (1.4)	186 (56.2)	BDI ≥10
Mayda et al,¹¹⁸ 2010	Turkey	2009	1–5	202	Mean (SD): 20.5 (2.2)	85 (40.1)	BDI ≥17
Yilmaz et al,¹⁷⁸ 2014	Turkey	2010	1–6	995	Mean (SD): 21.1 (1.9)	517 (52)	BDI ≥10
Aktekin et al,¹⁹⁶ 2001	Turkey	1996–2002	1–2	119	NR	NR	GHQ-12 ≥4
Karaoğlu and Şeker,¹⁰¹ 2011	Turkey	2008–2009	1–3	485	Mean (SD): 19.5 (1.5)	272 (56.1)	HADS-D ≥8
Baykan et al,⁵⁰ 2012	Turkey	NR	6	193	Mean (SD): 24.5 (1.5)	107 (55.4)	DASS-42 ≥10
Akvardar et al,³³ 2004	Turkey	NR	1, 6	166	NR	NR	HADS-D ≥7
Kaya et al,¹⁰² 2007	Turkey	NR	NR	352	NR	226 (64.2)	BDI ≥17
Ahmed et al,³⁰ 2009	UAE	2008	1–5	165	NR	0	BDI ≥10
James et al,⁹⁸ 2013	UK	2007	1	324	NR	194 (60)	GHQ-12 ≥4
Honney et al,⁸⁸ 2010	UK	2008	NR	553	Mean (SD): 21.6 (3)	220 (39.8)	PHQ-9 ≥10
Ashton and Kamali,⁴⁴ 1995	UK	1993–1994	2	186	Mean (SD): 20.4 (1.8)	77 (40.7)	HADS-D ≥8
Newbury-Birch et al,²⁰⁴ 2001	UK	1995, 1998	5	114	NR	38 (33.3)	HADS-D ≥8
Quince et al,²⁰⁶ 2012	UK	2007–2010	1–6	2155	NR	122 (43.2)	HADS-D ≥8
Guthrie et al,²⁰¹ 1998	UK	NR	1	172	NR	88 (51.2)	GHQ-12 ≥4
Pickard et al,¹³⁵ 2000	UK	NR	2	136	NR	46 (33.8)	HADS-D ≥8
Herzog et al,⁸⁶ 1987	US	1985	1–2	200	Mean (range): 23.1 (19–31)	NR	BDI ≥10
Hendryx et al,⁸⁵ 1991	US	1988	1	110	Mean (SD): 24.1 (3.1)	70 (63.6)	BDI ≥10
Givens and Tjia,⁷⁸ 2002	US	1994	1–2	194	NR	83 (43)	BDI-SF ≥8
Thomas et al,¹⁶⁴ 2007	US	2004	1–4	535	NR	248 (45.4)	PRIME-MD
Dyrbye et al,⁷² 2006	US	2004	NR	545	NR	245 (45)	PRIME-MD
Shah et al,¹⁴⁹ 2009	US	2005	1–4	2683	Mean (SD): 26 (3.2)	1076 (40)	CES-D ≥19
Dyrbye et al,⁷¹ 2007	US	2006	1–4	1691	NR	777 (46)	PRIME-MD
Smith et al,¹⁵⁹ 2011	US	2008	1–5	480	Mean (range): 26.3 (18–51)	480 (100)	CES-D ≥16
Smith et al,¹⁵⁸ 2010	US	2008	1–5	844	Mean (SD): 25.7 (4.1)	844 (100)	CES-D ≥16
Shindel et al,¹⁵⁵ 2011	US	2008	1–5	1241	Mean (SD): 25.4 (3.4)	0	CES-D ≥16
Schwenk et al,¹⁴⁶ 2010	US	2009	1–4	504	NR	210 (41.6)	PHQ-9 ≥10
Wimsatt et al,¹⁷⁵ 2015	US	2009	1–4	505	NR	210 (41.6)	PHQ-9 ≥10
Dyrbye et al,⁶⁹ 2010	US	2009	1–4	2661	NR	1352 (51.4)	PRIME-MD
Chang et al,⁵⁹ 2012	US	2010	1–3	364	NR	160 (44)	PRIME-MD
Jackson et al,⁹⁶ 2016	US	2012	1–4	4354	Median (range): 25 (22–32)	1957 (45.3)	PRIME-MD
Dyrbye et al,⁶⁸ 2015	US	2012	2–4	870	NR	442 (50.9)	PRIME-MD
Thompson et al,¹⁶⁶ 2016	US	2013	1–4	153	NR	75 (46.6)	PHQ-9 ≥10
Gold et al,⁸⁰ 2015	US	2013	1–5	183	NR	79 (43.2)	PRIME-MD
Lapinski et al,¹⁰⁹ 2016	US	2014	1–4	1294	NR	681 (52.6)	PHQ-9 ≥5
Zoccolillo et al,¹⁸³ 1986	US	1982–1984	1–2	304	NR	NR	BDI ≥10
Vitaliano et al,²⁰⁸ 1988	US	1984–1985	1	312	Mean (SD): 25.6 (3.5)	196 (63)	BDI ≥5
Rosal et al,²⁰⁷ 1997	US	1987–1993	2	171	NR	140 (51)	CES-D ≥80th percentile
Camp et al,¹⁹⁸ 1994	US	1991–1993	1	232	NR	153 (65.9)	Zung-SDS ≥50
Mosley et al,¹²³ 1994	US	1992–1993	3	69	Mean (range): 26 (24–37)	47 (68)	CES-D ≥16
Levine et al,²⁰² 2006	US	2000–2003	2	330	NR	NR	BDI ≥8
Tjia et al,¹⁶⁸ 2005	US	2001–2002	1–4	322	Mean (SD): 25.3 (2.6)	175 (54.4)	BDI-SF ≥8
Thompson et al,¹⁶⁵ 2010	US	2002–2003	3	44	NR	NR	CES-D ≥16
Goebert et al,⁷⁹ 2009	US	2003–2004	1–4	1184	NR	NR	CES-D ≥16
Dyrbye et al,⁷⁰ 2011	US	2006, 2007, 2009	4	1428	NR	NR	PRIME-MD
Haglund et al,¹⁰ 2009	US	2006–2007	3	101	Mean (SD): 25.4 (2.2)	47 (47)	BDI-II ≥14
Dyrbye et al,⁷³ 2008	US	2006–2007	1–4	2228	NR	1159 (51.6)	PRIME-MD
Ghodasara et al,⁷⁷ 2011	US	2008–2009	1–3	301	NR	154 (51)	BDI-II ≥14
Hardeman et al,⁸³ 2015	US	2010–2011	1	3149	NR	1592 (49.4)	PROMIS-T >60
Ludwig et al,²⁰³ 2015	US	2010–2014	3	336	NR	NR	CES-D >16
Dyrbye et al,⁷⁴ 2014	US	2011–2012	1–4	4402	Median: 25	1972 (45.1)	PRIME-MD
Wolf and Rosenstock,¹⁷⁶ 2016	US	2012–2013	1–4	130	NR	NR	PRIME-MD
Mousa et al,¹²⁴ 2016	US	2013–2014	1–4	336	NR	NR	PRIME-MD
Clark and Zeldow,¹⁹⁹ 1988	US	NR	2	110	Mean (SD): 23.6 (2.9)	80 (73)	BDI ≥8
MacLean et al,¹¹² 2016	US	NR	1–4	385	NR	NR	PRIME-MD
Chandavarkar et al,⁵⁸ 2007	US	NR	1–4	427	NR	145 (34)	BDI-II ≥21
Zeldow et al,¹⁸² 1987	US	NR	NR	99	Mean: 25.4	67 (67.7)	BDI-II ≥14
Smith et al,¹⁵⁷ 2007	US	NR	NR	438	Mean (SD): 24.8 (2.8)	318 (72.6)	BDI ≥10

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Abbreviations: ADS-K, General Depression Scale Short Form (in German); AKUADS, Aga Khan University Anxiety and Depression Scale; BDI, Beck Depression Inventory; BDI-SF, BDI Short Form; BSI-DEP, Brief Symptom Inventory Depression; CES-D, Center for Epidemiological Studies Depression Scale; DASS, Depression Anxiety Stress Scale; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; DSP, Derogatis Stress Profile; EST-Q, Emotional State Questionnaire; GHQ, General Health Questionnaire; HADS-D, Hospital Anxiety and Depression Scale; HRSRS, Health-Related Self-Reported Scale; K-10, Kessler Psychological Distress Scale; KADS, Kutcher Adolescent Depression Scale; MDI, Major Depression Inventory; MINI, Mini International Neuropsychiatric Interview; MMPI-D, Minnesota Multiphasic Personality Inventory-Depression Scale; NR, not reported; PHQ-9, 9-item Patient Health Questionnaire; PRIME-MD, Primary Care Evaluation of Mental Disorders; PROMIS-T, Patient-Reported Outcomes Measurement Information System; QIDS, Quick Inventory of Depressive Symptomatology; SCL-90, 90-item Symptom Checklist; TDI, Thai Depression Inventory; UAE, United Arab Emirates; UK, United Kingdom; US, United States; Zung-SDS, Zung Self-Rating Depression Scale; Zung-SF, Zung-SDS Short Form.

Studies are ordered alphabetically by country and then by year of survey.

Table 2.

Selected Characteristics of the 24 Studies of Suicidal Ideation^a

Source	Country	Survey Years	Year of Training	No. of Students	Age, y	Men, No. (%)	Instrument and Cutoff Score or Description^b
de Melo Cavestro and Rocha,⁶⁵ 2006	Brazil	2003	1–6	213	Mean (SD): 23.1 (2.3)	109 (51.2)	MINI
Alexandrino-Silva et al,³⁴ 2009	Brazil	2006–2007	1–6	336	Mean (SD): 22.4 (2.5)	105 (31)	BSI >0
Chen et al,¹⁸⁸ 2004	China	2002	2–3	892	Mean (SD): 17.5 (0.4)	0	Suicidal ideation over past 12 mo
Wan et al,⁴ 2012	China	2010	1–5	4063	Mean (SD): 20.5 (1.1)	1895 (46.6)	Suicidal ideation over past 12 mo
Sobowale et al,¹⁶⁰ 2014	China	2012	2–3	348	NR	NR	Suicidal ideation over past 2 wk (PHQ-9)
Ahmed et al,¹⁸⁵ 2016	Egypt	2016	NR	612	Mean (SD): 21.2 (1.6)	190 (31)	BSI >24
Okasha et al,¹⁹² 1981	Egypt	1978–1979	5	516	NR	NR	Suicidal ideation over past 12 mo
Alem et al,¹⁸⁶ 2005	Ethiopia	2001	NR	273	NR	227 (83.2)	Suicidal ideation over past 1 mo
Wege et al,¹⁷⁴ 2016	Germany	2012–2013	1	590	Mean (SD): 21.1 (3.9)	177 (29.9)	Suicidal ideation over past 2 wk (PHQ-9)
Tin et al,¹⁶⁷ 2015	Malaysia	2013	1–5	517	NR	188 (35)	SBQ-R ≥7
Eskin et al,¹⁸⁹ 2011	Multiple	NR	1–6	646	Mean: 21.4	353 (54.6)	Suicidal ideation over past 12 mo
Menezes et al,¹⁹¹ 2012	Nepal	2010	2–3	206	Mean (SD): 21 (1.7)	112 (54.4)	Suicidal ideation over past 12 mo (GHQ-28)
Tyssen et al,¹⁹⁴ 2001	Norway	1993–1994	6	522	Mean (SD): 28 (2.8)	224 (43)	Suicidal ideation over past 12 mo (Paykel Inventory)
Osama et al,⁵ 2014	Pakistan	2013	1–5	331	Mean (SD): 20.7 (1.7)	135 (41.2)	Suicidal ideation over past 12 mo (GHQ-28)
Khokher and Khan,¹⁹⁰ 2005	Pakistan	NR	1–5	217	Mean: 22.6	96 (44.2)	Suicidal ideation over past 12 mo (GHQ-28)
Wallin and Runeson,¹⁹⁵ 2003	Sweden	1998	1, 5	305	Mean: 27.4	127 (41.6)	Suicidal ideation over past 12 mo
Dahlin et al,⁶² 2005	Sweden	2001–2002	1, 3, 6	296	Mean (range): 26.1 (18–44)	126 (39.8)	Suicidal ideation over past 12 mo (Meehan Inventory)
Amiri et al,¹⁸⁷ 2013	United Arab Emirates	NR	1–6	115	Mean (SD): 20.7 (2.1)	47 (40.9)	Suicidal ideation over past 12 mo
Thompson et al,¹⁶⁵ 2010	US	2002–2003	3	43	NR	NR	Suicidal ideation over past 2 wk (PRIME-MD)
Goebert et al,⁷⁹ 2009	US	2003–2004	1–4	1215	NR	NR	Suicidal ideation over past 2 wk (PRIME-MD)
Dyrbye et al,⁷³ 2008	US	2006–2007	1–4	2230	NR	1159 (51.6)	Suicidal ideation over past 12 mo (Meehan Inventory)
Dyrbye et al,⁷⁴ 2014	US	2011–2012	1–4	4032	Median: 25	1972 (45.1)	Suicidal ideation over past 12 mo (Meehan Inventory)
MacLean et al,¹¹² 2016	US	NR	1–4	385	NR	NR	Suicidal ideation over past 12 mo (Meehan Inventory)
Tran et al,¹⁹³ 2015	Vietnam	2009	1, 3, 5	2099	Mean (range): 21.5 (18–30)	1052 (50.1)	Suicidal ideation over past 12 mo

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Abbreviations: BSI, Beck Scale for Suicidal Ideation; GHQ, General Health Questionnaire; MINI, Mini International Neuropsychiatric Interview; NR, not reported; PHQ-9, 9-item Patient Health Questionnaire; PRIME-MD, Primary Care Evaluation of Mental Disorders; SBQ-R, Revised Suicidal Behaviors Questionnaire; US, United States.

Studies are ordered alphabetically by country and then by year of survey.

Studies for which a specific instrument is not specified used variably worded short form screening instruments.

Medical student training level, continent or region, country, diagnostic criteria or screening instrument cutoff, and total Newcastle-Ottawa scores for the studies appear in eTable 1 in the Supplement. Newcastle-Ottawa score components for all 195 individual studies appear in eTable 2 in the Supplement.

Prevalence of Depression or Depressive Symptoms Among Medical Students

Meta-analytic pooling of the prevalence estimates of depression or depressive symptoms reported by 183 studies yielded a crude summary prevalence of 27.2% (37 933/122 356 individuals; 95% CI, 24.7%–29.9%), with significant evidence of between-study heterogeneity (Q = 16721.1, τ² = 0.78, I² = 98.9%, P < .001) (Figures 2, 3, 4, 5, and 6). The prevalence estimates reported by the individual studies ranged from 1.4% to 73.5%. Sensitivity analysis, in which the meta-analysis was serially repeated after exclusion of each study, demonstrated that no individual study affected the overall prevalence estimate by more than 0.3% (eTable 3 in the Supplement).

The vertical dashed lines indicate the pooled summary estimate (95% CI) for all studies in Figures 2–6: 27.2% (37 933/122 356 individuals); 95% CI, 24.7%–29.9%; I² = 98.9%, τ² = 0.78, P < .001. The area of each square is proportional to the inverse variance of the estimate. Horizontal lines indicate 95% confidence intervals of the estimate. The studies in Figures 2–6 are ordered alphabetically by screening instrument and then sorted by increasing sample size within each instrument.

To further characterize the range of depression or depressive symptom prevalence estimates identified by these methodologically diverse studies, meta-analyses stratified by screening instrument and cutoff score were conducted (Figure 7). Summary prevalence estimates ranged from 9.3% (157/1234 individuals [95% CI, 5.3%–15.7%]; Q = 19.7, τ² = 0.24, I² = 84.8%) for the Hospital Anxiety and Depression Scale with a cutoff score of 11 or greater to 55.9% (540/1039 individuals [95% CI, 45.1%–66.2%]; Q = 32.9, τ² = 0.18, I² = 90.9%) for the Aga Khan University Anxiety and Depression Scale with a cutoff score of 19 or greater. The median summary prevalence was 32.4% (5042/19 160 individuals [95% CI, 25.8%–39.7%]; Q = 1665.3, τ² = 0.62, I² = 98.6%) for the Beck Depression Inventory (BDI) with a cutoff score of 10 or greater.

Pooled summary estimates are ordered alphabetically by screening instrument. The individual studies contributing to each summary estimate are reported in Figures 2 through 6. The area of each diamond is proportional to the inverse variance of the estimate. Horizontal extremes of the diamonds indicate 95% CIs of the estimate.

Among medical students who screened positive for depression,15.7%(110/954 individuals [95%CI,10.2%–23.4%]; Q = 20.1, τ² = 0.26, I² = 70.1%) reportedly sought psychiatric or other mental health treatment as assessed by a subset of 7 studies reporting this information (eFigure 1 in the Supplement).

Prevalence of Depression or Depressive Symptoms by Study-Level Characteristics

No statistically significant differences in prevalence estimates were noted between cross-sectional studies (36 632/116 628 [27.3%; 95%CI, 24.7%–30.1%]) and longitudinal studies (1301/5728 [26.7%; 95%CI, 19.1%–36.1%]) (test for subgroup differences, Q = 0.02, P = .90) or studies performed in the United States (14 356/36 249 [26.7%; 95% CI, 22.5%–31.3%]) compared with those performed outside the United States (23 577/86 107 [27.4%; 95% CI, 24.5%–30.6%]) (Q = 0.08, P = .78). Studies were further stratified by continent or region in Figure 8. Prevalence estimates from studies limited to preclinical students (4866/25 462 [23.7%; 95% CI, 19.5%–28.5%]) did not significantly differ from estimates from studies limited to clinical students (2917/13 172 [22.4%; 95% CI, 17.6%–28.2%]) (Q = 0.13, P = .72).

The area of each diamond is proportional to the inverse variance of the estimate. Horizontal extremes of the diamonds indicate 95% CIs of the estimate.

^aComparison of studies reporting only on preclinical students with those studies reporting only on clinical students.

Prevalence estimates did not significantly vary with baseline survey year (survey year range, 1982–2015; slope = 0.2% 1-year increase [95%CI, −0.2%to0.7%]; Q = 1.17, P = .28). There Were no significant associations between prevalence and mean or median age (slope = 0.2%per 1-year increase [95%CI, −1.4% to 1.8%]; Q = 0.07, P = .79) or sex (slope = −1.1% per percentage increase in male study participants [95% CI, −15.9% to 13.7%]; Q = 0.02, P = .88).

When evaluated by Newcastle-Ottawa criteria, higher prevalence estimates were found among studies with more representative participant populations (24 366/68 693; 36.3% [95%CI, 29.9%–43.3%]) compared with those with less representative participant populations (13 567/53 663; 25.4% [95% CI, 22.8%–28.2%]) (Q = 9.6, P = .002; Figure 9). There were no statistically significant differences in prevalence estimates when studies were stratified by sample size, respondent and nonrespondent comparability, validity of ascertainment of depression or depressive symptoms (details regarding determination of screening instrument validity appear in eMethods 2 in the Supplement), thoroughness of descriptive statistics reporting, or total Newcastle-Ottawa score (P > .05 for all comparisons).

Full details regarding Newcastle-Ottawa risk of bias scoring are provided in eMethods 2 in the Supplement. Component scores for all individual studies are presented in eTable 2 in the Supplement. The area of each diamond is proportional to the inverse variance of the estimate. Horizontal extremes of the diamonds indicate 95% CIs of the estimate.

Heterogeneity Within Depression Screening Instruments

To identify potential sources of heterogeneity independent of assessment modality, heterogeneity was examined within subgroups of studies using common instruments when at least 6 studies were available (complete results appear in eTable 4 in the Supplement). No significant differences between cross-sectional and longitudinal studies were observed within any instruments when at least 3 studies were in each comparator subgroup.

Heterogeneity was partially accounted for by country with US studies yielding lower depression or depressive symptom prevalence estimates than non-US studies among the 24 studies using the BDI and a cutoff score of 10 or greater (13.0% vs 37.5%, respectively; Q = 12.7, P < .001) and the 13 studies using the Center for Epidemiological Studies Depression Scale (CES-D) and a cutoff score of 16 or greater (34.4% vs 50.3%; Q = 3.8, P = .05). However, this difference was not seen among other instruments.

Level of training did not significantly contribute to between study heterogeneity among any of the examined instruments. Year of baseline survey significantly contributed to observed statistical heterogeneity among 3 instruments, although the results were inconsistent (ie, 2 analyses suggested that depression was increasing with time, whereas a third suggested it was decreasing). Age and sex were not significantly associated with depression prevalence among any instruments.

Analysis of Longitudinal Studies

The temporal relationship between exposure to medical school and depressive symptoms was assessed in an analysis of 9 longitudinal studies that measured depressive symptoms before and during medical school (Table 3). Because studies used different assessment instruments, the relative change in depressive symptoms was calculated for each study individually (ie, follow-up prevalence divided by baseline prevalence) and then the relative changes derived from the individual studies were examined. Overall, the median absolute increase in depressive symptoms was 13.5% (range, 0.6%–35.3%) following the onset of medical training.

Table 3.

Secondary Analysis of 9 Longitudinal Studies Reporting Depression or Depressive Symptom Prevalence Estimates Both Before and During Medical School

Source^a	Screening Instrument	Cutoff Score	Follow-up, mo	Baseline			Follow-up			Comparison
Source^a	Screening Instrument	Cutoff Score	Follow-up, mo	No. Depressed	Sample Size	Prevalence, % (95% CI)	No. Depressed	Sample Size	Prevalence, % (95% CI)	Absolute Increase, % (95% CI)	Relative Increase, Ratio (95% CI)
Walkiewicz et al,²⁰⁹ 2012	MMPI-D	>70	12	31	178	17.4 (11.8 to 23.0)	32	178	18.0 (12.4 to 23.6)	0.6 (−7.4 to 8.5)	1.0 (0.6 to 1.8)

Quince et al,²⁰⁶ 2012	HADS-D	≥8	12	38	665	5.7 (3.9 to 7.5)	36	429	8.4 (5.8 to 11.0)	2.7 (−0.4 to 6.1)	1.5 (0.9 to 2.4)

Levine et al,²⁰² 2006	21-Item BDI	≥8	20	64	376	17.0 (13.2 to 20.8)	80	330	24.2 (19.6 to 28.8)	7.2 (1.3 to 13.2)	1.4 (1.0 to 2.0)

Camp et al,¹⁹⁸ 1994	Zung-SDS	≥50	3	14	232	6.0 (2.9 to 9.1)	42	232	18.1 (13.2 to 23.1)	12.1 (6.2 to 18.0)	3.0 (1.6 to 5.6)

Vitaliano et al,²⁰⁸ 1988	BDI	≥5	8	36	312	11.5 (8.0 to 15.0)	78	312	25.0 (20.2 to 29.8)	13.5 (7.4 to 19.4)	2.2 (1.4 to 3.3)

Clark and Zeldow,¹⁹⁹ 1988	21-item BDI	≥8	14	11	116	9.5 (4.2 to 14.8)	24	88	27.3 (18.0 to 36.6)	17.8 (7.2 to 28.7)	2.9 (1.3 to 6.2)

Rosal et al,²⁰⁷ 1997	CES-D	≥80th^b	18	48	264	18.2 (13.6 to 22.9)	67	171	39.2 (31.9 to 46.5)	21.0 (12.3 to 29.6)	2.2 (1.4 to 3.3)

Aktekin et al,¹⁹⁶ 2001	GHQ	≥4	12	21	119	17.6 (10.8 to 24.4)	57	119	47.9 (38.9 to 56.9)	30.3 (18.5 to 40.9)	2.7 (1.5 to 4.8)

Yusoff et al,²¹⁰ 2013	DASS-21	≥10	12	10	170	5.9 (2.4 to 9.4)	70	170	41.2 (33.8 to 48.6)	35.3 (26.8 to 43.3)	7.0 (3.5 to 14.0)

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Abbreviations: BDI, Beck Depression Inventory; CES-D, Center for Epidemiological Studies Depression Scale; DASS-21, 21-item Depression Anxiety Stress Scale; GHQ, General Health Questionnaire; HADS-D, Hospital Anxiety and Depression Scale; MMPI-D, Minnesota Multiphasic Personality Inventory-Depression Scale; Zung-SDS, Zung Self-Rating Depression Scale

Studies are sorted by the percentage increase in depressive symptoms from baseline to the follow-up survey. The median percentage increase among the studies was 13.5%.

Indicates 80^th percentile.

Prevalence of Suicidal Ideation Among Medical Students

In an analysis of 24 studies, the crude summary prevalence of suicidal ideation, variably reported as having occurred over the past 2 weeks to the past 12 months, was 11.1% (2043/21 002 individuals; 95%CI, 9.0%–13.7%), with significant evidence of between-study heterogeneity (Q = 547.1, τ² = 0.32, I² = 95.8%, P < .001) (Figure 10). The prevalence estimates reported by the individual studies ranged from 4.9% to 35.6%. Sensitivity analysis showed that no individual study affected the overall pooled estimate by more than 1.9%(eTable 5 in the Supplement).

Contributing studies are stratified by screening modality and sorted by increasing sample size. The dotted line marks the overall summary estimate for all studies, 11.1% (2043/21 002 individuals; 95% CI, 9.0%–13.7%; Q = 547.1, τ² = 0.32, I² = 95.8%, P < .001). The area of each square is proportional to the inverse variance of the estimate. Horizontal lines indicate 95% CIs of the estimate.

To further characterize the range of the suicidal ideation prevalence estimates identified, stratified meta-analyses were performed by screening instrument and cutoff score. Summary prevalence estimates ranged from 7.4% (69/938 individuals [95% CI, 5.9%–9.2%]; Q = 0.01, τ² = 0, I² = 0%) over the past 2 weeks for studies using the 9-item Patient Health Questionnaire (PHQ-9) to 24.2% (208/754 individuals [95% CI, 13.0%–40.5%]; Q = 37.2, τ² = 0.42, I² = 94.6%) over the past 12 months for studies using the 28-item General Health Questionnaire.

The median prevalence of suicidal ideation over the past 12 months reported by 7 studies using variably worded short-form screening instruments was 10.2% (723/8636 individuals [95% CI, 6.8%–15.0%]; Q = 176.5, τ² = 0.33, I² = 96.6%). Among the full set of studies, no statistically significant differences in prevalence estimates were noted by country (United States vs other countries), continent or region, level of training, baseline survey year, average age, proportion of male study participants, or total Newcastle-Ottawa score (P > .05 for all comparisons). Within-instrument heterogeneity was not examined because there were not enough studies using identical screening instruments (≤4 for each assessment modality), precluding meaningful analysis.

Assessment of Publication Bias

Visual inspection of the funnel plot of studies reporting on depression or depressive symptoms revealed significant asymmetry (eFigure 2 in the Supplement). There was evidence of publication bias, with smaller studies yielding more extreme prevalence estimates (P = .001 using the Egger test). The funnel plot of studies reporting on suicidal ideation revealed minimal asymmetry (eFigure 3 in the Supplement), suggesting the absence of significant publication bias (P = .49 using the Egger test).

Discussion

This systematic review and meta-analysis of 195 studies involving 129 123 medical students in 47 countries demonstrated that 27.2% (range, 9.3%–55.9%) of students screened positive for depression and that 11.1% (range, 7.4%–24.2%) reported suicidal ideation during medical school. Only 15.7% of students who screened positive for depression reportedly sought treatment. These findings are concerning given that the development of depression and suicidality has been linked to an increased short-term risk of suicide as well as a higher long-term risk of future depressive episodes and morbidity.^211,212

The present analysis builds on recent work demonstrating a high prevalence of depression among resident physicians, and the concordance between the summary prevalence estimates (27.2% in students vs 28.8% in residents) suggests that depression is a problem affecting all levels of medical training.^13,213 Taken together, these data suggest that depressive and suicidal symptoms in medical trainees may adversely affect the long-term health of physicians as well as the quality of care delivered in academic medical centers.^214–216

When interpreting these findings, it is important to recognize that the data synthesized in this study were almost exclusively derived from self-report inventories of depressive symptoms that varied substantially in their sensitivity and specificity for diagnosing major depressive disorder (eTable 6 in the Supplement).²¹⁷ Instruments such as the PHQ-9 have high sensitivity and specificity for diagnosing major depression, whereas others such as the Primary Care Evaluation of Mental Disorders (PRIME-MD) have low specificity and should be viewed as screening tools. Although these self-report measures of depressive symptoms have limitations, they are essential tools for accurately measuring depression in medical trainees because they protect anonymity in a manner that is not possible through formal diagnostic interviews.²¹⁸ To control for the differences in these inventories, we stratified our analyses by survey instrument and cutoff score, identifying a range of estimates not captured in another evidence synthesis.²¹⁹

The prevalence of depressive symptoms among medical students in this study was higher than that reported in the general population.^220–222 For example, the National Institute of Mental Health study of behavioral health trends in the United States, including 67 500 nationally representative participants, found that the 12-month prevalence of a major depressive episode was 9.3% among 18- to 25-yearolds and 7.2% among 26- to 49-year-olds.²²⁰ In contrast, the BDI, CES-D, and PHQ-9 summary estimates obtained in the present study were between 2.2 and 5.2 times higher than these estimates. These findings suggest that depressive symptom prevalence is substantially higher among medical students than among individuals of similar age in the general population.

How depression levels in medical students compare with those in nonmedical undergraduate students and professional students is unclear. One review concluded that depressive symptom prevalence did not statistically differ between medical students and nonmedical undergraduate students.²²³ However, this conclusion may be confounded because the analysis did not control for assessment modality and did not include a comprehensive or representative set of studies (only 12 studies and 4 studies exclusively composed of medical students and nonmedical students, respectively). Two large, representative epidemiological studies have estimated that depressive symptom prevalence in nonmedical students ranges from 13.8% to 21.0%, lower than the estimates reported by many studies of medical students in the present meta-analysis.^224,225

Some professional students, such as law students, may not markedly differ from medical students in their susceptibility to depression, although firm conclusions cannot be drawn from the currently available data.^226,227 Together, these findings suggest that factors responsible for depression in medical students may also be operative in other undergraduate and professional schools. The finding in the longitudinal analysis of an increase in depressive symptom prevalence with the onset of medical school suggests that it is not just that medical students (and other students) are prone to depression, but that the school experience may be a causal factor.

This analysis identified a pooled prevalence of suicidal ideation of 11.1%. Endorsement of suicidal ideation as assessed by the PHQ-9 or other similar instruments increases the cumulative risk of a suicide attempt or completion over the next year by 10- and 100-fold, respectively.²²⁸ Combined with the finding that only 15.7%of medical students who screened positive for depression sought treatment, the high prevalence of suicidal ideation underscores the need for effective preventive efforts and increased access to care that accommodate the needs of medical students and the demands of their training.

Limitations

This study has important limitations. First, the data were derived from studies that had different designs, screening instruments, and trainee demographics. The substantial heterogeneity among the studies remained largely unexplained by the variables inspected. Second, many subgroup analyses relied on unpaired cross-sectional data collected at different medical schools, which may cause confounding. Third, because the studies were heterogeneous with respect to screening inventories and student populations, the prevalence of major depression could not be determined. Fourth, the analysis relied on aggregated published data. A multicenter, prospective study using a single validated measure of depression and suicidal ideation with structured diagnostic interviews in a random subset of participants would provide a more accurate estimate of the prevalence of depression and suicidal ideation among medical students.

Future Directions

Because of the high prevalence of depressive and suicidal symptomatology in medical students, there is a need for additional studies to identify the root causes of emotional distress in this population. To provide more relevant information, future epidemiological studies should consider adopting prospective study designs so that the same individuals can be assessed over time, use commonly used screening instruments with valid cutoffs for assessing depression in the community (eg, the BDI, CES-D, or PHQ-9), screen for comorbid anxiety disorders, and completely and accurately report their data, for example, by closely following the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.²²⁹

Possible causes of depressive and suicidal symptomatology in medical students likely include stress and anxiety secondary to the competitiveness of medical school.⁶² Restructuring medical school curricula and student evaluations (such as using a pass-fail grading schema rather than a tiered grading schema and fostering collaborative group learning through a “flipped-classroom” education model) might ameliorate these stresses.^230,231 Future research should also determine how strongly depression in medical school predicts depression during residency and whether interventions that reduce depression in medical students carry over in their effectiveness when those students transition to residency.²³² Furthermore, efforts are continually needed to reduce barriers to mental health services, including addressing the stigma of depression.^146,233

Conclusions

In this systematic review, the summary estimate of the prevalence of depression or depressive symptoms among medical studentswas27.2%andthatof suicidal ideationwas11.1%. Further research is needed to identify strategies for preventing and treating these disorders in this population.

Supplementary Material

Supplemental

NIHMS875825-supplement-Supplemental.pdf^{(600.5KB, pdf)}

Key Points.

Question

Are medical students at high risk for depression and suicidal ideation?

Findings

In this meta-analysis, the overall prevalence of depression or depressive symptoms among medical students was 27.2%, and the overall prevalence of suicidal ideation was 11.1%. Among medical students who screened positive for depression, 15.7% sought psychiatric treatment.

Meaning

The overall prevalence of depressive symptoms among medical students in this study was higher than that reported in the general population, which underscores the need for effective preventive efforts and increased access to care for medical students.

Acknowledgments

Funding/Support: Funding was provided by the National Institutes of Health (MSTP TG 2T32GM07205 awarded to Mr Ramos and grant R01MH101459 awarded to Dr Sen) and the US Department of State (Fulbright Scholarship awarded to Dr Mata).

Footnotes

Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Role of the Funder/Sponsor: The National Institutes of Health and the US Department of State had no role in the design and conduct of the study; the collection, management, analysis, or interpretation of the data; the preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.

Disclaimer: The opinions, results, and conclusions reported in this article are those of the authors and are independent from the National Institutes of Health and the US Department of State.

Author Contributions: Dr Mata had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the analysis. Ms Rotenstein, Messrs Ramos and Segal, and Dr Torre are equal contributors.

Concept and design: Mata.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Mata.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Mata.

Obtained funding: Guille, Sen, Mata.

Administrative, technical, or material support: Guille, Sen, Mata.

Study supervision: Guille, Sen, Mata.

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PERMALINK

Prevalence of Depression, Depressive Symptoms, and Suicidal Ideation Among Medical Students

Lisa S Rotenstein, BA

Marco A Ramos, MPhil

Matthew Torre, MD

J Bradley Segal, BA, BS

Michael J Peluso, MD, MPhil

Constance Guille, MD, MS

Srijan Sen, MD, PhD

Douglas A Mata, MD, MPH

Abstract

IMPORTANCE

OBJECTIVE

DATA SOURCES AND STUDY SELECTION

DATA EXTRACTION AND SYNTHESIS

MAIN OUTCOMES AND MEASURES

RESULTS

CONCLUSIONS AND RELEVANCE

Methods

Search Strategy and Study Eligibility

Data Extraction and Quality Assessment

Data Synthesis and Analysis

Results

Study Characteristics

Figure 1.

Table 1.

Table 2.

Prevalence of Depression or Depressive Symptoms Among Medical Students

Figure 2. Meta-analysis by Scores on the Aga Khan University Anxiety and Depression Scale and the Beck Depression Inventory.

Figure 3. Meta-analysis by Scores on the First, Second, and Short Form Versions of the Beck Depression Inventory, Brief Symptom Inventory Depression Scale, and the Center for Epidemiological Studies Depression Scale.

Figure 5. Meta-analysis by Scores on Several Scales.

Figure 6. Meta-analysis by Scores on the Patient-Reported Outcomes Measurement Information System, Quick Inventory of Depressive Symptomatology, 90-Item Symptom Checklist, Thai Depression Inventory, and the Zung Self-Rating Depression Scale.

Figure 7. Meta-analyses of the Prevalence of Depression or Depressive Symptoms Among Medical Students Stratified by Screening Instrument and Cutoff Score.

Prevalence of Depression or Depressive Symptoms by Study-Level Characteristics

Figure 8. Meta-analyses of the Prevalence of Depression or Depressive Symptoms Among Medical Students Stratified by Study-Level Characteristics.

Figure 9. Meta-analyses of the Prevalence of Depression or Depressive Symptoms Among Medical Students Stratified by Newcastle-Ottawa Scale Components and Total Score.

Heterogeneity Within Depression Screening Instruments

Analysis of Longitudinal Studies

Table 3.

Prevalence of Suicidal Ideation Among Medical Students

Figure 10. Meta-analysis of the Prevalence of Suicidal Ideation Among Medical Students.

Assessment of Publication Bias

Discussion

Limitations

Future Directions

Conclusions

Supplementary Material

Key Points.

Question

Findings

Meaning

Acknowledgments

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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