German translation and validation of the International Olympic Committee (IOC) Sport Mental Health Assessment Tool 1 (SMHAT-1) and Sport Mental Health Recognition Tool 1 (SMHRT-1)

Abstract

Mental health, particularly the early detection of psychological distress among elite athletes, is of critical importance. To make the Sport Mental Health Assessment Tool 1 (SMHAT-1) and the Sport Mental Health Recognition Tool 1 (SMHRT-1) available for German-speaking populations, this study aimed to translate and validate the screening instruments of the SMHAT-1 and the SMHRT-1 into German, as well as to evaluate the psychometric properties of the screening instruments. The SMHAT-1 screening instruments and the SMHRT-1 handout were translated using a systematic seven-step process. Forward translations were performed by native speakers of the target language (German) fluent in the source language (English), followed by back-translations by native speakers of English fluent in German. Validation occurred in three phases: a pilot test with 30 athletes to assess clarity, preliminary psychometric testing with 177 bilingual participants to evaluate criterion equivalence, and full psychometric testing with 235 athletes from regional to Olympic levels. Reliability, construct, and criterion validity were assessed. Internal consistency was acceptable to good for most tools, and all instruments demonstrated strong equivalence with their original versions. The Athlete Psychological Strain Questionnaire (APSQ) exhibited strong convergent validity with the Kessler Psychological Distress Scale (K-10; r = 0.81) and all participants with a self-reported professionally diagnosed mental disorder had APSQ scores above the screening threshold. Prevalence rates highlighted common mental health concerns in athletes, including anxiety (17.0%), depression (23.8%), and disordered eating (36.1%). The German SMHAT-1 demonstrated robust psychometric properties and is a reliable tool for assessing mental health in athletes.

The German and English versions of the SMHAT-1 and SMHRT-1 are available for download here:

SMHAT-1 German:

https://img.olympics.com/images/image/private/w_auto/primary/hr8i8nfbwf8gldsthqgd

SMHAT-1 English:

https://img.olympics.com/images/image/private/w_auto/primary/ttpbrdzvhofmabszbynq

SMHRT-1 German:

https://www.olympics.com/athlete365/app/uploads/2021/06/SMHRT-1_german.pdf

SMHRT-1 English:

https://www.olympics.com/athlete365/app/uploads/2021/06/BJSM-SMHRT-1-Athlete365-2020-102411.pdf

Keywords

Anxiety depression disordered eating gambling post-traumatic stress disorder sleep

Introduction

Mental health in elite athletes has gained increasing recognition as a crucial component of overall well-being and performance.^1–3 However, athletes are often perceived as “mentally tough” individuals who are immune to psychological challenges – a stereotype reinforced by society and even by athletes themselves.^4,5 These assumptions have historically led to the neglect of mental health in sports science, leaving many athletes without adequate support.⁴

Contrary to these assumptions, recent studies suggest that the prevalence of mental health disorders among athletes is comparable to that of the general population.¹ Anxiety, depression, and eating disorders are particularly prominent, with elite athletes facing additional stressors unique to their high-performance environments.⁶ Stressors include intense public scrutiny, career instability, and performance pressures, which are compounded by barriers to help-seeking. Athletes are often reluctant to seek mental health support due to stigma, fear of appearing weak, concerns regarding confidentiality, and limited access to specialized care.^2,7,8

Left unrecognized and unaddressed, mental health issues tend to persist and intensify.^9–11 The combination of high-performance pressure, insufficient mental health literacy, and (perceived) limited access to tailored support perpetuates maladaptive coping strategies and other dysfunctional patterns and increases psychological distress.^8,10 This may prolong the course of mental disorders, increase the risk of chronicity, and ultimately impair both the athlete's long-term health and competitive performance.¹⁰ Thus, early recognition of mental health issues in athletes is critical to enable targeted prevention and intervention.¹⁰ Ideally, this requires tools that are broadly applicable and can be used not only by mental health professionals but also by practitioners across athletic contexts, as “frontline staff” – such as sports medicine physicians, physiotherapists, and coaches – are regular key contacts for athletes and interact with them frequently, placing them in a suitable position to observe even subtle symptoms and changes.^10,12

In response to these challenges and needs, the International Olympic Committee (IOC) introduced the Sport Mental Health Assessment Tool 1 (SMHAT-1) and Sport Mental Health Recognition Tool 1 (SMHRT-1).¹² These tools aim to identify mental health symptoms and disorders in athletes early, enabling timely intervention. The SMHAT-1 was developed for sports medicine physicians and other health professionals and comprises a structured three-step screening process. Step 1 uses the Athlete Psychological Strain Questionnaire (APSQ)¹³ to screen for psychological distress as an initial triage. Athletes flagged in step 1 proceed to step 2, which involves further evaluation using validated instruments tailored to specific mental health concerns, including anxiety, depression, disordered eating behaviors, sleep disturbances, and substance use.¹² Step 3 involves various specific screening tools designed to provide additional diagnostic clarity when needed, ensuring a comprehensive assessment across a broad spectrum of mental health challenges. The SMHRT-1 is designed as a complementary educational handout to raise awareness among the athlete's support network, including coaches, trainers, and family members, as well as athletes themselves, in recognizing and addressing potential mental health concerns.¹² Together, the SMHAT-1 and SMHRT-1 provide a comprehensive and structured transdisciplinary approach to promoting mental health awareness, early detection, and timely intervention for elite athletes who are at risk of, or currently experiencing, psychological strain.

Mental health in high-performance sport cannot be adequately captured by general dichotomous classifications of “healthy” versus “ill”.^6,14 Athletes may experience varying degrees of psychological strain or distress that do not necessarily meet diagnostic criteria, yet may still affect well-being, functioning, and help-seeking behavior. Contemporary perspectives therefore conceptualize mental health as existing along a continuum rather than as a binary state, with subclinical symptoms and early warning signs representing relevant states of risk.^14,15 This view is consistent with dual-continua models of mental health, which conceptualize positive mental health and mental disorder as related but distinct dimensions, thereby acknowledging that the absence of a diagnosable disorder does not necessarily indicate high psychological well-being.¹⁵ From this perspective, mental health screening in sport is intended to support early detection of psychological strain and informed decision-making rather than pure diagnostic classification.¹ Accordingly, the SMHAT-1 is designed as a structured, multi-domain screening approach that integrates symptom domains relevant to athletes’ mental health and guides subsequent support or referral pathways.¹²

While the SMHAT-1 has demonstrated robust psychometric properties in its original English version,¹² cross-cultural adaptations are necessary for its implementation in non-English speaking populations, as the use of unvalidated translations or the application to individuals with insufficient English proficiency risks compromising the instrument's linguistic fidelity and conceptual equivalence, potentially leading to misinterpretation of item meaning and inaccurate assessment of psychological constructs.^16,17 High-quality translations ensure that the tool retains its validity and reliability across diverse cultural contexts.¹⁸

German speaking populations (e.g., Germany, Austria, and Switzerland) constitute a substantial proportion of European professional athletes, and their relevance is not limited to their mere numerical representation.¹⁹ International comparative analyses, for example, indicate that athletes from these countries frequently achieve performance outcomes that exceed expected benchmarks, underscoring their prominent role within the global elite sport landscape.^19–21 To make the SMHAT-1 and SMHRT-1 available for German-speaking populations, this study aimed to translate and validate these tools into German, as well as to evaluate the psychometric properties of the SMHAT-1 screening instruments. As the SMHRT-1 functions as an educational and informational resource, it was not subject to psychometric testing but was translated alongside the SMHAT-1 to ensure availability of the complete IOC mental health screening framework as an integrated package in German. By enabling early detection of psychological distress, the German SMHAT-1 and SMHRT-1 could help bridge the gap between athletes and mental health services in German-speaking regions, fostering a healthier and more supportive sports culture.

Methods

Ethical considerations and data collection

Ethical approval was granted by the Ethics Committee of the German Sport University Cologne (020/2022). Participants provided informed consent via an online platform before starting the surveys. All analyses were conducted using IBM SPSS Version 28. Only complete datasets were included in the analyses, as the survey software was configured to export fully completed questionnaires only. Accordingly, there were no missing values in the analysed dataset. This approach ensured complete data for all analysed variables but precluded a detailed analysis of response rates and attrition patterns.

Translation and adaptation

To create a high-quality German version of the SMHAT-1, a systematic seven-step guideline¹⁸ was followed for translation and validation (see Figure 1). The process involved two translators who were native in the target language (German) and fluent in the source language (English). They independently created two separate translations, which were synthesized into a joint version. This joint version was then independently back-translated into English by two back-translators who were native in the source language and fluent in the target language. The SMHRT-1 was translated using the same methodology.

Figure 1.

Steps in the translation, adaptation, and validation process (adapted from Sousa and Rojjanasrirat, 2011).¹⁶

Screening instruments of the SMHAT-1 not previously available in German were fully translated, while validated German versions of instruments were adopted after obtaining permission from their authors. Minor exceptions applied to instruments for which partial German versions were already available: the CAGE-AID required only a terminology adaptation based on the existing German CAGE version (replacement of “alcohol” with “drugs”), and for the PC-PTSD-5, the existing 4-item German version was adopted while the DSM-5 item was newly translated. An overview of all screening instruments included in the SMHAT-1, including scoring procedures, cut-offs, and reported psychometric properties of the original instruments, is provided in Table 1.

Table 1.

Screening instruments included in the SMHAT-1.

Instrument	Target construct	German version previously available ^a)	Scoring / cut-off	Sensitivity / specificity (original) ^b)
Athlete Psychological Strain Questionnaire (APSQ)²²	General psychological distress	No	Sum score (10–50); cut-off ≥ 17	93% / 79%²³
9-item Patient Health Questionnaire (PHQ-9)²⁴	Depressive symptoms	Yes²⁵	Sum score (0–27); cut-off ≥ 10	88% / 88%
7-item Generalized Anxiety Disorder Scale (GAD-7)²⁶	Anxiety symptoms	Yes²⁷	Sum score (0–21); cut-off ≥ 10	89% / 82%
Alcohol Use Disorders Identification Test - Consumption (AUDIT-C)²⁸	Alcohol misuse	Yes²⁹	Sum score (0–12); cut-off ≥ 3 (women) / ≥ 4 (men)	86% / 72%
CAGE (Cut-Annoyed-Guilty-Eye) Questionnaire Adapted to Include Drugs (CAGE-AID)³⁰	Substance misuse	No ^c)	Number of endorsed items (0–4); cut-off ≥ 2	79% / 77%
Athlete Sleep Screening Questionnaire (ASSQ)³¹	Sleep disturbance	No	Sum score (0–17); severity categories; no validated cut-off	Not reported / Not reported
Brief Eating Disorder in Athletes Questionnaire (BEDA-Q)³²	Disordered eating	No	Sum score of 6 items (0–18), plus 3 items on weight loss; no validated cut-off	Not reported / Not reported
16-item Prodromal Questionnaire (PQ-16)³³	Psychotic-like experiences	Yes ^d)	Sum score (0–16); cut-off ≥ 6	87% / 54%
Mood Disorder Questionnaire (MDQ)³⁴	Bipolar symptoms	Yes³⁵ ^d)	Number of endorsed items (0–13); cut-off ≥ 6, plus indicating that symptoms clustered in the same time period and caused moderate or serious problems	73% / 90%
Adult ADHD Self-Report Scale (ASRS-v1.1)³⁶	ADHD symptoms	Yes³⁷	Sum score (0–6); cut-off ≥ 4	69% / 100%
Problem Gambling Severity Index (PGSI)³⁸	Problem gambling	No	Sum score (0–27); severity categories	Not reported / Not reported
Primary Care Post-Traumatic Stress Disorder Screen for DSM-5 (PC-PTSD-5)³⁹	PTSD symptoms	Yes⁴⁰ ^e)	Number of endorsed items (0–5), cut-off ≥ 3, plus reported exposure to a traumatic event	95% / 85%⁴¹

Note. a) Screening instruments that were not previously available in German (APSQ, ASSQ, BEDA-Q, PGSI) were translated and psychometrically evaluated as part of the present study. b) Sensitivity and specificity values refer to the original validation studies of the respective instruments and do not represent estimates from the present sample or from the German versions. For some instruments, sensitivity and specificity values are not reported in the original literature, as they were not primarily developed for ROC-based diagnostic classification. c) Minor wording adaptation based on existing German CAGE version; full forward-backward translation procedure not applied. d) German version available but not formally validated. e) Existing 4-item German version (not formally validated) was adopted; DSM-5 item 5 was newly translated in the present study.

Validation

Pilot testing

The pilot phase aimed to assess the comprehensibility, functionality, clarity, and phrasing of the translated instruments. Comprehensibility was evaluated using a dichotomous scale for clarity, with a predefined threshold of 80% interrater agreement for all items. Participants for this phase were recruited through amateur sports clubs, as it was sufficient that they were engaged in sports rather than being elite athletes. This approach ensured a diverse sample and provided valuable feedback on the usability and practical application of the tools before advancing to the subsequent testing phases

Preliminary psychometric testing

The second phase aimed to evaluate the criterion equivalence of the translated instruments by comparing participant responses on the English and German versions. Participants were bilingual in English and German, with fluency in one language as a native speaker and at least B2 proficiency in the other. As the focus was on the accuracy of the translation and a large sample size was intended, being engaged in a sport, especially on an elite level, was not a requirement to participate. Consequently, a major proportion of participants in this phase were sport-related university students (German Sport University Cologne) who participated within course-related research participation requirements. These participants contributed exclusively to the bilingual criterion-equivalence testing in Phase 2 and were not part of the subsequent full psychometric testing sample used to evaluate internal consistency and validity in athletes. Participants first completed the English version of the instruments, followed by the German version in a randomized order to minimize repetition effects. Correlations were calculated using Pearson's and Spearman's coefficients to establish criterion equivalence (Pearson's correlation coefficients were used for tools with Likert scales, while Spearman's coefficients were applied for dichotomous scales).

Full psychometric testing

The final phase aimed to evaluate the psychometric properties of the SMHAT-1 instruments. Reliability metrics, such as Cronbach's alpha and item-total correlations, were used to assess internal consistency across all screening instruments in steps 1 to 3 of the SMHAT-1. Construct validity was analyzed by examining prevalence rates of mental health symptoms and patterns relevant to elite athlete populations. Convergent validity was assessed by correlating the APSQ with the Kessler Psychological Distress Scale (K-10)⁴² to confirm alignment with an established measure of psychological distress. Criterion validity was further explored by examining the descriptive agreement between APSQ scores and participants’ self-reported mental health status, including professionally diagnosed and suspected but undiagnosed conditions. In addition, exploratory known-groups analyses were conducted comparing currently injured and non-injured athletes across SMHAT-1 step 1 and step 2 screening instruments. Differences in categorical screening outcomes (threshold exceeded vs. not exceeded) were examined using χ² tests or Fisher's exact test where appropriate. Differences in continuous screening scores were examined using Mann–Whitney U tests. In line with the primary psychometric focus of the present study, these exploratory analyses were limited to the core screening instruments included in steps 1 and 2 of the SMHAT-1.

Participants were recruited through an email campaign targeting German sports clubs competing in the top two to three leagues, identified via an online search. German Olympic bases were also contacted directly. Athletes were also recruited through the Department of Sports Medicine at Charité – Universitätsmedizin Berlin. Additionally, elite athletes from Austria were recruited through collaborations with the University Hospital/Tirol Kliniken Innsbruck and the UMIT TIROL Private University for Health Sciences and Health Technology. No systematic recruitment was conducted in Switzerland, as no collaborations with Swiss institutions had been established during the recruitment period.

Participant characteristics for each testing phase, including age, gender distribution, and competitive level, are reported in the Results section.

Results

Pilot testing

The comprehensibility of the translated screening tools was evaluated in a pilot study with 30 participants, including 13 females and 17 males, with a mean age of 35.30 years (SD = 11.88; range = 22–56). All participants were active in sports, with an average of 11.38 years of experience (SD = 8.62; range = 2–25), and 47.0% were engaged in ball sports such as soccer or handball. Interrater agreement on item clarity ranged from 96.6% to 100.0%, surpassing the predefined threshold of 80.0%. One item from the APSQ was flagged as ambiguous, with a participant noting that it could be interpreted as a physical or psychological challenge. To clarify its psychological focus, the item was revised for subsequent testing.

Preliminary psychometric testing

In the next phase, a sample of 177 bilingual participants (119 females, 57 males, and 1 non-binary individual) with a mean age of 28.31 years (SD = 9.12; range = 18–66) completed both the original English and the translated German version of the screening tools. Correlations between paired items were calculated, with Pearson's coefficients ranging from 0.59 to 1.00 across the instruments (Table 2). These results demonstrated moderate to strong criterion equivalence, confirming that the German translations preserved the constructs and content of the original tools.

Table 2.

Correlation coefficients calculated during step 2 of the translation and validation process, comparing the English and German versions of the SMHAT-1 screening instruments (n = 177).

Screening-tool	Correlation coefficients
APSQ (Athlete Psychological Strain Questionnaire)	r(175) = .59 – .84
ASSQ (Athlete Sleep Screening Questionnaire)	r(175) = .92 – .99
BEDA-Q (Brief Eating Disorder in Athletes Questionnaire)	r(175) = .63 – .92
PGSI (Problem Gambling Severity Index)	r(175) = .73 – 1.00
PC-PTSD-5 (Primary Care Post-Traumatic Stress Disorder Screen for DSM-5)	r(175) = .81 – .85

Note. Pearson's correlation coefficients were used for tools with Likert scales, while Spearman's coefficients were applied for dichotomous scales, such as the PC-PTSD-5.

Full psychometric testing

Full psychometric testing was conducted with 235 participants, comprising 58.7% females, 40.4% males, and 0.9% identifying as diverse, with a mean age of 24.34 years (SD = 6.06; range = 18–49) (see Table 3 for detailed demographic information). This group represented athletes from a broad variety of sports (see Table 4) and various levels of competition, including 14.5% at the Olympic level and 46.4% at the international level.

Table 3.

Demographic information of the participants of the full psychometric testing (n = 235).

Variable	Expression	n	%
Gender	Female	138	58.7
	Male	95	40.4
	Diverse	2	0.9
Place of residence	Germany	151	64.3
	Austria	79	33.6
	Other	5	2.1
Level of education	No degree	2	0.9
	Secondary education	22	9.4
	Higher school certificate (A level)	132	56.2
	Finished apprenticeship	19	8.1
	Polytechnic degree	16	6.8
	University degree	44	18.7
Relationship status	Single	132	56.2
Relationship status	In a relationship	103	43.8
Level of competition	Olympic	34	14.5
	Paralympic	7	3.0
	International	109	46.4
	National	68	28.9
	Regional	8	3.4
	Squad athlete (Austria)	9	3.8
Current injury	Yes	37	15.7
Current injury	No	198	84.3
Season status	Season	82	34.9
	Off-season	51	21.7
	Pre-season	85	36.2
	Injury-break	17	7.2

Table 4.

Gender distribution of participants across sports (n = 235^a)).

Sport (n = 28)	n_Female	n_Male	n_Total
Alpine Skiing	10	2	12
Alpine Skiing (Para)	1	0	1
Archery	2	2	4
Artistic Roller Skating	1	0	1
Artistic Swimming	0	1	1
Badminton	1	3	4
Badminton (Para)	0	1	1
Baseball	0	2	2
Basketball	3	0	3
Beach Volleyball	1	1	2
Biathlon	6	3	9
Bobsleigh/Luge/Skeleton	6	4	10
Boxing	1	0	1
Canoeing	2	1	3
Cross-Country Skiing	2	3	5
Cycling	0	4	4
Diving	1	2	3
Field Hockey	2	4	6
Figure Skating	0	1	1
Golf	1	0	1
Gymnastics	6	7	13
Handball	15	5	20
Ice Hockey	0	5	5
Judo	6	3	9
Kickboxing	2	1	3
Long-distance running	1	0	1
Modern Pentathlon	1	0	1
Nordic Combined	2	4	6
Padel Tennis	4	0	4
Rowing	7	1	8
Sailing	1	0	1
Ski Cross	2	7	9
Ski Jump	3	5	8
Ski Mountaineering	0	1	1
Snowboard	4	2	6
Soccer	18	2	20
Softball	5	0	5
Speed Skating	2	1	3
Sport Shooting	0	1	1
Swimming	2	0	2
Table Tennis	2	2	4
Taekwondo	0	1	1
Tennis	1	3	4
Track and Field	5	5	10
Triple Jump	1	0	1
Volleyball	6	1	7
Volleyball (Sitting)	0	1	1
Water Polo	1	1	2
Wheelchair Basketball	0	2	2
Wrestling	1	0	1
Total	138	95	233

Note. a) Participants per sport were recorded during the full psychometric testing (n = 235); two participants who reported a diverse gender were not included in this table to ensure anonymity.

Internal consistency, assessed using Cronbach's alpha (α), indicated acceptable to good reliability for the majority of tools. The APSQ achieved an α of 0.81, while the Generalized Anxiety Disorder Scale-7^26,43 (GAD-7) and Patient Health Questionnaire-9^24,25 (PHQ-9) recorded values of 0.87 and 0.84, respectively. The Brief Eating Disorder in Athletes Questionnaire³² (BEDA-Q) showed acceptable internal consistency with an α of 0.77, which is comparable to or slightly higher than internal consistency estimates reported in previous studies for this tool.³² Acceptable internal consistency was also observed for the Problem Gambling Severity Index^38,44 (PGSI; α = 0.76), the Prodromal Questionnaire-16³³ (PQ-16; α = 0.79), the Primary Care Post-Traumatic Stress Disorder Screen for DSM-5³⁹ (PC-PTSD-5; α = 0.77), and the Mood Disorder Questionnaire³⁴ (MDQ; α = 0.77). The Athlete Sleep Screening Questionnaire (ASSQ) yielded an α of 0.64, which is comparable to values reported in the original validation study³¹ and may reflect the multidimensional nature of the instrument. Lower internal consistency estimates were also observed for the Alcohol Use Disorders Identification Test-Concise^28,29 (AUDIT-C; α = 0.64), the Cut-Annoyed-Guilty-Eye Adapted to Include Drugs³⁰ (CAGE-AID; α = 0.61), and the Adult ADHD Self-Report Scale^36,37 (ASRS-v1.1; α = .62). This is consistent with methodological considerations, as Cronbach's alpha estimates are partly determined by scale length and therefore tend to be lower in brief screening measures.⁴⁵

The prevalence rates varied across the screening tools. The APSQ,¹³ used as the initial triage tool in step 1, yielded scores above the screening threshold in 72.8% of participants. In step 2, 17.0% of participants exceeded the cutoff score for moderate anxiety (≥ 10) on the GAD-7.^26,27 On the PHQ-9,^24,25 23.8% of participants exceeded the screening threshold for depressive symptoms, with 8.7% reporting suicidal ideation on item 9, necessitating immediate clinical attention. The ASSQ indicated that 22.6% of participants experienced moderate to severe sleep disturbances. On the AUDIT-C,^28,29 45.1% of the sample exceeded the screening threshold for problematic alcohol use. On the CAGE-AID,³⁰ 7.2% of participants exceeded the screening threshold for problematic drug use. Disordered eating behaviors, assessed using the BEDA-Q,³² were reported by 36.1% of the sample. In step 3, additional screeners provided further insights into specific mental health concerns. On the ASRS-v1.1,³⁶ 11.0% of participants exceeded the screening threshold for symptoms consistent with ADHD. On the MDQ,³⁴ 3.0% of participants exceeded the screening threshold for bipolar symptoms. On the PC-PTSD-5,³⁹ 5.1% of participants exceeded the screening threshold for post-traumatic stress symptoms, while 0.8% of participants showed gambling problem scores on the PGSI.⁴⁴ Finally, psychotic-like experiences, assessed with the PQ-16,³³ were reported by 20.9% of participants.

Notably, some cases were missed by the APSQ but exceeded the thresholds of specific screening tools in step 2 or 3. The percentage of missed cases ranged from 0.0% (e.g., MDQ, PGSI) to 21.9% (AUDIT-C). For instance, 15.3% of disordered eating cases (BEDA-Q) and 11.8% of problematic drug or alcohol use cases (CAGE-AID) were not flagged by the APSQ. Full details of (mis-)classified cases are provided in Table 5.

Table 5.

(Mis-)classified cases of the APSQ and prevalence rates.

Screener	Positive cases detected at step 1 and step 2 / step 3	Positive cases not detected at step 1 but detected at step 2 / step 3	Misclassified cases	Prevalence
GAD-7	n = 40 (17.0%)	n = 0 (0.0%)	0.0%	17.0%
PHQ-9	n = 55 (23.4%)	n = 1 (0.4%)	1.8%	23.8%
ASSQ	n = 47 (20%)	n = 6 (2.6%)	11.3%	22.6%
AUDIT-C	n = 82 (35.2%)	n = 23 (9.9%)	21.9%	45.1%
CAGE-AID	n = 15 (6.4%)	n = 2 (0.8%)	11.8%	7.2%
BEDA-Q	n = 72 (30.6%)	n = 13 (5.5%)	15.3%	36.1%
ASRS-v.1.1	n = 25 (10.6%)	n = 1 (0.4%)	3.8%	11.0%
MDQ	n = 7 (3.0%)	n = 0 (0.0%)	0.0%	3.0%
PC-PTSD-5	n = 11 (4.7%)	n = 1 (0.4%)	8.3%	5.1%
PGSI	n = 2 (0.8%)	n = 0 (0.0%)	0.0%	0.8%
PQ-16	n = 46 (19.6%)	n = 3 (1.3%)	6.1%	20.9%

Note. Misclassified cases and prevalence rates were calculated for the full psychometric testing (n = 235). Cases exceeding the threshold for the APSQ and the subsequent screening instruments were calculated. Additionally, cases not exceeding the threshold for the APSQ but identified by a subsequent screening instrument are included. Prevalence rates represent the proportion of participants exceeding the threshold of each screening instrument.

The APSQ demonstrated strong convergent validity with the K-10, achieving a correlation coefficient of 0.81. Regarding criterion validity, all participants who reported a professionally diagnosed mental disorder (e.g., depression, anxiety disorders, or eating disorders) had APSQ scores above the screening threshold. Among participants who reported assuming they might have an undiagnosed mental health condition, 85.7% also had APSQ scores above the screening threshold (see Table 6). These findings reflect descriptive alignment between self-reported mental health status and screening results but do not constitute evidence of diagnostic accuracy.

Table 6.

Comparison of self-reported mental health conditions and corresponding screening results.

Disorder	n	APSQ score above threshold	Corresponding screening tool score above threshold
Professional diagnosis
Anxiety disorders	3
Social phobia	1	✓	X (GAD-7)
Panic disorder	1	✓	✓ (GAD-7)
PTSD	1	✓	✓ (PC-PTSD-5)
Depression	4	✓	✓ (PHQ-9)
Eating disorders	4
Bulimia nervosa	1	✓	✓ (BEDA-Q)
Anorexia nervosa	1	✓	✓ (BEDA-Q)
Unspecified	2	✓	✓ (BEDA-Q)
ADHS	1	✓	✓ (ASRS-v.1.1)
Self-reported assumption to have a mental disorder
Anxiety disorders	1
Competition anxiety	1	X	X (GAD-7)
Depression	7	✓	6 x ✓ (PHQ-9)
Eating disorders	6
Anorexia nervosa	1	✓	(BEDA-Q)
Unspecified	5	✓	(BEDA-Q)
ADS	1	✓	(ASRS-v1.1)
Burnout	2	✓

Note. Self-reported and professionally diagnosed mental health conditions were assessed within the full psychometric testing (n = 235). The table describes whether APSQ scores and corresponding screening tool scores exceeded predefined screening thresholds in participants who reported a professionally diagnosed mental health condition or assumed they might have a mental health condition. These descriptive comparisons are not intended to reflect diagnostic accuracy or screening performance.

Exploratory known-groups comparisons (Table 7) showed that injured compared to non-injured athletes more frequently exceeded the screening thresholds for APSQ (86.5% vs. 70.2%), PHQ-9 (40.5% vs. 20.7%), and GAD-7 (29.7% vs. 14.7%), with all p < .05. No significant differences were observed for BEDA-Q, ASSQ, AUDIT-C, or CAGE-AID. Analyses of continuous scores showed a consistent pattern, with injured athletes reporting higher APSQ, PHQ-9, and GAD-7 scores than non-injured athletes. A difference in the same direction was also observed for BEDA-Q.

Table 7.

Exploratory known-groups comparisons between injured and non-injured athletes across SMHAT-1 step 1 and step 2 screening instruments.

Panel A. threshold exceedance analyses
Instrument	Injured n/N (%)	Non-injured n/N (%)	Test statistic	p	Effect size
APSQ	32/37 (86.5)	139/198 (70.2)	χ²(1) = 4.17	.041	V = .13
PHQ-9	15/37 (40.5)	41/198 (20.7)	χ²(1) = 6.76	.009	V = .17
GAD-7	11/37 (29.7)	29/198 (14.7)	χ²(1) = 5.02	.025	V = .15
BEDA-Q	17/37 (46.0)	68/198 (34.3)	χ²(1) = 1.82	.178	V = .09
CAGE-AID	4/37 (10.8)	13/198 (6.6)	-	.318	V = .06
ASSQ	10/37 (27.0)	43/198 (21.7)	χ²(1) = 0.50	.478	V = .05
AUDIT-C (women)	6/23 (26.1)	50/115 (43.5)	χ²(1) = 2.40	.121	V = .13
AUDIT-C (men)	7/13 (53.9)	42/82 (51.2)	χ²(1) = 0.03	.860	V = .02

Panel B. Continuous score analyses
Instrument	Injured median [Q1–Q3]	Non-injured median [Q1–Q3]	Mann–Whitney U	p
APSQ	24 [21–29]	20 [16–23]	5293	< .001
PHQ-9	6 [4–12]	5 [3–9]	4625	.011
GAD-7	6 [4–11]	4 [2–7]	4635	.010
BEDA-Q	3 [1–8]	2 [1–5]	4416	.045
CAGE-AID	0 [0–1]	0 [0–0]	4019	.168
ASSQ	6 [4–8]	5 [3–7]	4372	.060
AUDIT-C	2 [1–3]	3 [1–4]	3276	.302

Note. Categorical comparisons refer to threshold exceedance (yes/no) and were examined using χ² tests, except for CAGE-AID, for which Fisher's exact test was used because of small expected cell counts. Continuous score comparisons were examined using Mann–Whitney U tests. For AUDIT-C, threshold analyses were conducted separately for women and men because sex-specific cut-offs were applied; the continuous score analysis is reported for the total sample.

Evaluation of the SMHRT-1

The translated SMHRT-1 handout was perceived as clearly understandable by participants. Respondents indicated that the wording, structure, instructions, and layout were accessible and easy to follow. It was evaluated as suitable for lay audiences from athletes’ environments, including athletes themselves, coaches, family members, and others.

Discussion

Evaluation of the German adaption

This study aimed to translate and validate the SMHAT-1 and SMHRT-1 tools for German-speaking populations while evaluating the psychometric properties of the SMHAT-1 screening instruments. The findings demonstrated that the German SMHAT-1 maintains robust psychometric properties and is a reliable tool for assessing mental health in athletes.

The translation and adaptation process followed a rigorous seven-step approach, ensuring linguistic accuracy and cultural appropriateness. The high interrater agreement during the pilot phase confirmed the comprehensibility of the tools, with only one ambiguous item being revised to clarify its psychological focus. This highlights the effectiveness of the systematic translation methodology and its ability to preserve the constructs of the original instruments.

The results from the second phase further established the criterion equivalence of the German versions. Correlation coefficients between the English and German versions of the screening instruments ranged from moderate to strong, confirming that the translation process did not compromise the validity of the tools. These findings align with previous research emphasizing the importance of bilingual validation in cross-cultural adaptation of mental health instruments.¹⁸

In the final phase, the psychometric properties of the SMHAT-1 were evaluated in a larger, diverse sample of athletes. Internal consistency was acceptable to good for most screening instruments, with Cronbach's alpha values comparable to the original versions. The APSQ demonstrated strong convergent validity with the K-10 and showed substantial descriptive agreement between APSQ scores above the screening threshold and both professionally diagnosed mental health conditions and self-reported suspected but undiagnosed cases. The prevalence rates of mental health concerns, such as anxiety, depression, and disordered eating, were consistent with findings from previous studies on elite athletes.¹ These comparisons are intended to provide descriptive context and should not be interpreted as evidence of psychometric validity, measurement quality, or equivalence.

In addition, exploratory known-groups comparisons between injured and non-injured athletes showed differences for APSQ, PHQ-9, and GAD-7, with injured athletes more frequently exceeding screening thresholds and reporting higher scores on these instruments. This pattern is plausible, as injury represents a relevant sport-specific stressor and previous research has linked sport injury to increased psychological strain, depressive symptoms, and symptoms of common mental disorders in athletes.^46,47 Accordingly, these findings provide additional, exploratory support for the construct validity of the German screening instruments by showing that they differentiate between groups in theoretically expected directions. These results should, however, be interpreted as exploratory supportive rather than confirmatory evidence.

The findings of this study closely align with those of the original SMHAT-1 publication,¹² particularly regarding the reliability of the screening instruments. Internal consistency metrics (Cronbach's alpha) for the German versions were comparable to those reported in the original validation study.¹² For example, the APSQ demonstrated a Cronbach's alpha of 0.81 in this study, mirroring the values of 0.81 (male athletes) and 0.84 (female athletes) reported in the original study.¹² Similar consistency was observed for tools such as the GAD-7 and PHQ-9, confirming that the psychometric properties of the original instruments were preserved during the translation process. These findings underscore the reliability and validity of the SMHAT-1 across different linguistic and cultural contexts, reinforcing its applicability in elite sports settings.^12,48

Limitations and future directions

Despite these strengths, several limitations and considerations related to the study design and the instruments themselves warrant consideration. First, response rates and attrition could not be examined in detail, as only fully completed questionnaires were retained for analysis. Consequently, potential differences between participants who completed the survey and those who discontinued participation could not be assessed. Second, a substantial proportion of participants in the preliminary bilingual criterion-equivalence phase were sport-related university students. While this group shares relevant characteristics with the broader athletic context, it does not fully represent the target population of high-performance athletes; however, these participants were not involved in the subsequent full psychometric testing sample. Third, no systematic recruitment was conducted in Switzerland; although the German-language version of the SMHAT-1 is intended for use across German-speaking contexts, the present validation is primarily based on data from Germany (and Austria), thereby potentially constraining the generalisability to other German-speaking countries. Fourth, while the selection of screening instruments followed the structure of the IOC SMHAT-1 framework,¹² several cut-offs were originally derived from general population samples or specific subgroups and may not be equally calibrated for all athlete populations. This is particularly relevant for the Brief Eating Disorder in Athletes Questionnaire (BEDA-Q), which was developed and validated in a young (all 16 years old), exclusively female athlete sample,³² potentially limiting its generalizability to male or older athletes. Future studies may prioritize validating this instrument within more diverse groups to ensure its reliability across different demographics. Although other instruments included in the SMHAT-1 (e.g., PHQ-9, GAD-7, AUDIT-C) have been widely used in athletic contexts,¹ their cut-offs were not specifically established for elite athlete samples. Consequently, screening results should be interpreted cautiously and as indicators of potential mental health concerns rather than diagnostic thresholds.

Fifth, measurement invariance of the SMHAT-1 screening instruments across subgroups (e.g., gender, performance level, or country) was not examined as formal invariance testing typically requires substantially larger and more balanced subgroup sample sizes and is particularly challenging within a multi-instrument screening framework that combines conceptually distinct tools and heterogeneous item formats.⁴⁹ As the present study did not aim to compare mental health outcomes between subgroups, and no inferential subgroup comparisons were conducted, the absence of measurement invariance testing does not compromise the interpretation of the reported psychometric findings, which pertain to the total sample only; however, it should be considered when interpreting or applying the instruments across different subgroups. Sixth, exploratory known-groups comparisons were conducted for current injury status (as a clearly definable and theoretically relevant variable), but these analyses were limited to a single subgroup variable and were based on a relatively small and unbalanced injured group. Other potentially relevant subgroup comparisons (e.g., by gender, performance level, or country) were not examined. While such additional analyses may yield informative and potentially relevant insights, the present study was not designed or powered for systematic, hypothesis-driven subgroup testing across multiple grouping variables and instruments. Given the broad range of possible subgroup-instrument combinations, conducting selected additional comparisons would have exceeded the scope of the study and would also have increased the risk of selective reporting and inflation due to multiple testing. Future studies specifically designed and adequately powered for subgroup analyses may further extend this aspect of construct validity.

Seventh, the high prevalence rate of positive screenings for alcohol misuse observed in this sample is notable but consistent with findings from other studies using the AUDIT-C in elite athlete settings – mostly in US college samples and team sports, with substantial variation across disciplines.^48,50 For example, a study analyzing the SMHAT-1 in Team USA athletes found that 30–35% of participants exceeded the threshold for alcohol misuse.⁴⁸ Similarly, a study of elite athletes in Ireland reported that 93% of participants engaged in binge drinking behaviors.⁵⁰ Future studies should investigate the use of the AUDIT-C in this population to further validate its applicability and determine whether it may overestimate prevalence rates in elite athletes. However, the possibility of self-selection bias must also be considered, as individuals experiencing alcohol-related issues or mental health concerns may have been more likely to participate in this study.

Eight, the comparatively high proportion of individuals exceeding the cut-off for psychotic symptoms likely reflects the instrument's emphasis on sensitivity and its focus on subclinical psychotic-like experiences.^33,51 The PQ-16 was originally developed to identify individuals at increased risk for psychosis and is typically applied in help-seeking or clinically enriched populations. Its limited specificity, combined with items overlapping with broader symptoms (e.g., depression, anxiety), may contribute to elevated screen-positive rates in non-clinical athletic samples. Accordingly, positive PQ-16 results in this context should not be directly interpreted as evidence of manifest psychotic disorders.

Ninth, the lack of clinical interviews as the gold standard for validation limits the conclusions that can be drawn regarding the diagnostic accuracy of the screening tools.¹⁷ Consequently, future research may lay a focus on validating these instruments against structured clinical interviews. Nevertheless, it is relevant to acknowledge that the SMHAT-1 is intended as a screening aid that supports a stepped-care approach and is not designed to replace a comprehensive clinical interview.¹² Its purpose lies in the early, efficient, and easily accessible identification of athletes who may benefit from further psychological assessment, while keeping the procedure feasible within performance sport environments. As the SMHAT-1 is intended for use by sports medicine physicians and other licensed or registered health professionals, these professionals can follow up the screening results with a structured diagnostic interview when additional evaluation is indicated. This may occur either through an interview conducted by the administering professional or through referral to appropriately qualified mental health specialists, ensuring that athletes receive further assessment and care as needed.

Future research may explore how the SMHAT-1 and the SMHRT-1 can be further established and optimized within German speaking athlete populations. This may include examining their integration into existing support structures and evaluating strategies that facilitate their effective use. One avenue for further advancement may involve developing training resources that foster sensitive, stigma free communication when administering the instruments and responding to elevated scores, whether by sports medicine or other professionals (SMHAT-1) or coaches, family members, or other individuals in athletes’ environments (SMHRT-1). Such efforts may strengthen the practical utility of the tools and enhance their contribution to mental health support in athletic contexts.

Conclusions

Overall, our study demonstrates that the German SMHAT-1 closely resembles the psychometric properties of the original English version and serves as a reliable and valid tool for assessing mental health in athletes. In addition, the translated SMHRT-1 handout was evaluated as clearly understandable and suitable for lay and transdisciplinary audiences, including athletes, coaches, family members, and other key supporters. This broad comprehensibility enhances the potential for early and low threshold detection of mental health issues within applied sport settings.

In summary, our findings contribute to the growing recognition of the importance of mental health in competitive sports. By integrating the SMHAT-1 and the SMHRT-1 into routine assessments, sports organizations and healthcare providers can take a proactive approach to safeguarding the mental well-being of athletes. Considering future research, both the original English version and the German translation of the SMHAT-1 and the SMHRT-1 should be revisited and refined to integrate new developments and ensure their continued suitability for use in elite sports settings.

Footnotes

ORCID iD

Antonia Bendau

Ethical considerations

This study was performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Ethical approval was granted by the Ethics Committee of the German Sport University Cologne (020/2022).

Consent to participate

Written informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Author contributions

Jan Kaminski, Antonia Bendau, and Andreas Ströhle contributed to the conception and design of the study and the data collection. Cornelia Blank and Wolfgang Schobersberger supported the recruitment of participants. Material preparation and formal analysis were carried out by Jan Kaminski. Antonia Bendau, Andreas Ströhle, and Alexandra Pizzera provided supervision throughout the research process. The first draft of the manuscript was written by Jan Kaminski, and all authors provided critical feedback on previous versions. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

All data, analysis code, and materials are available upon reasonable request from the corresponding author.

Declaration of generative AI and AI-assisted technologies in the writing process

Generative AI and AI-assisted technologies (e.g., ChatGPT) were used solely to improve the readability and language of the manuscript. No AI tools were employed to generate content, develop ideas, perform analysis, or contribute to the interpretation of findings. The authors take full responsibility for the content.

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