Achieving a comprehensive understanding of a particular phenomenon is a key concern of science. However, the inherent complexity of real-world phenomena can rarely be captured by a single theory, study, or assessment method. Therefore, it is necessary to approach a particular phenomenon from different perspectives to make robust and reliable assumptions about it (5, 16). Such an approach, which combines evidence from different sources to address the same phenomenon/research question, is widely referred to as triangulation (7, 25).

What is Triangulation?

The term and approach of triangulation, which is rooted in geometry and has been primarily applied in the field of navigation and land surveying, characterizes the process of forming triangles from typically two known points at the end of a baseline to determine the location of a third, commonly difficult to measure, point with high precision (7, 11, 25). Metaphorically, the fundamental principles of triangulation, particularly the integration of information from different sources, have been transferred to scientific research. Applying this approach offers several key benefits for researchers. Firstly, it allows researchers to gain a more comprehensive understanding of a particular phenomenon (19, 21, 25). Secondly, it can strengthen the credibility of research, which is typically conceptualized as the level of trustworthiness of the study findings (19, 21, 25). Thirdly, it can improve the research’s validity, which, depending on the type of validity, refers to how well a concept, instrument, or assessment reflects what it intends to measure or can be generalized to real-world settings (19, 21, 25). Moreover, there is the opinion in the literature that triangulation is a promising approach for addressing contemporary scientific challenges (e.g., ‘replication crisis’), which have received growing attention in sports science and sports medicine research in recent years (13).

In this context, it is worth noting that using triangulation provides advantages that go beyond those of strict replication studies (6, 16). While current efforts to improve the reproducibility of research are commendable, a strict replication of a previous study’s procedure will neither foster a more comprehensive understanding of a phenomenon nor protect against avoiding the failings of the to-be-replicated research (e.g., bias in study design, methods, and analysis) (6, 16). In the worst-case scenario, in which the observations of methodologically flawed studies are consistently reproduced, such findings might achieve a status of ‘confirmed truth’ instead of being rejected (16). This may ultimately harm rather than benefit scientific credibility and progress.

Application in Sports Science and Sports Medicine

Multi-, inter-, and transdisciplinary research work is not uncommon in the broader fields of sports science and sports medicine, including but not limited to multicentre observation and intervention studies. Here, notable examples are an observational study on the prevalence of health-related symptoms of a Coronavirus Disease-19 infection in athletes (28). Other examples are intervention studies investigating the health effects of physical training in individuals with heart failure and preserved ejection fraction (2). Further studies address coronary heart diseases and type 2 diabetes mellitus (15). These projects were conducted by investigator teams with diverse professional backgrounds in sports science, sports medicine, and related disciplines such as cardiology or neurology. Such multi-, inter-, and transdisciplinary research, which can be interpreted as forms of triangulation (e.g., data source and investigator triangulation), often occurs ‘naturally’ without direct reference to the theoretical concept of triangulation (see examples above).

The systematic use of triangulation has received considerably less attention than replication in current research practice in nearly all scientific fields, including sports science and sports medicine (6, 16). However, integrating information from different key sources, which typically have biases unrelated to each other (11), provides several advantages, especially for enhancing the credibility and validity of research findings (19, 21, 25). Thus, its application is considered promising for advancing knowledge generation, such as improving mechanistic research (1). Based on these advantages, we suggest that triangulation deserves a more systematic and widespread application in the multi-, inter-, and transdisciplinary fields of sports science and sports medicine. To make triangulation more accessible to the reader, this editorial article discusses and defines different types of triangulation (for schematic illustration see figure 1, and for definition see table 1), based on relevant scientific articles (7, 10, 14, 19, 21, 25). Furthermore, it provides examples for selected application scenarios within sports science and sports medicine (see figure 1 and table 1).

Limitations and Future Remarks

Despite triangulation providing various advantages, this approach has some limitations that need to be considered. Typically, triangulation can be more resource-consuming (e.g., due to the use of additional assessment methods), adds complexity to research (e.g., from dealing with a higher amount of data, or from requiring a relatively high level of coordination/communication between investigators and staff members with complementary expertise to enable a successful interdisciplinary and interprofessional work), and does not protect from inconclusive findings (e.g., in case observations from different sources are conflicting) (7, 19, 25). Although such inconclusive findings can be challenging to interpret and may not allow for firm conclusions, such inconclusiveness can be an important impetus for further research to elucidate the role of specific sources of bias or moderators causing nonconvergent findings (17).

The explicit application of the triangulation approach in sports science and sports medicine research is rare, although there are noteworthy exceptions (23, 26). To foster a more frequent use of triangulation in future research practice in sports science and sports medicine, progress in theoretical direction, including but not limited to the development of best-practice guidelines for designing, conducting, and reporting findings of triangulation studies in this research field, as well as conceptual re-framing of relevant terms, might be required. For example, ‘between-method triangulation’ is traditionally interpreted as the combination of quantitative and qualitative methods (7, 10, 14). As an alternative, less narrow approach, yet not established, one may consider interpreting the term ‘between-method triangulation’ more intuitively and inclusively as the application of different qualitative and/or quantitative methods (e.g., functional near-infrared spectroscopy and electroencephalography to assess neural activation via changes in cortical hemodynamic and event-related potentials).

In this context, the term ‘within-method triangulation’ may be reserved to characterize the usage of different outcomes of the same method to operationalize a particular phenomenon (e.g., event-related potentials and spontaneous activity to assess neural activation). In addition to a conceptual re-framing of terms related to triangulation, the use of artificial intelligence (AI), which has gained popularity in the fields of sports science and sports medicine in recent years (18, 20, 24), can provide several advantages for triangulation studies. In particular, applying AI technology has huge potential to advance research practice, for example, by saving resources through automation in various applications (e.g., data analysis). However, when using AI technology, challenges, such as ethical and legal concerns related to data privacy and security, or other issues, including the transparency and reliability of data sources and selection of AI models, should be carefully considered (18, 20, 24). Given this context, future efforts are needed to explore how artificial intelligence can be effectively used as a tool to support triangulation (e.g., in data collection, handling, and analysis).

Finally, to support a systematic and more widespread application of information-rich, yet resource-consuming triangulation studies in sports science and sports medicine, which are likely to generate more robust, credible, and comprehensive evidence, different key stakeholders (e.g., funding agencies) may need to value such efforts to a greater extent (e.g., by providing appropriate funding opportunities) (16).

Conclusions

Triangulation, when appropriately used, is a promising approach to gain a more comprehensive understanding and tackle challenges (e.g., credibility and validity) relevant to sports science and sports medicine research and practice. Thus, this editorial advocates for a more systematic and widespread application of triangulation in this research field, often dealing with highly complex real-world phenomena.

■ Herold F, Gronwald T, Rahlf L, Hollander K, Patejdl R