Over the last 5 years there has been a tremendous rise in interest in personalized medicine and patient-centred healthcare. This has resulted in an expanding focus on the value of single-case research methods (also known as N-of-1 or Single-Case Designs (SCDs)). SCDs use repeated measures, frequent data collection and patient-reported outcome measures to draw conclusions about an individual.

We use “SCD” as a broad term that includes all SCD sub-designs, encompassing Single-Case Experimental Designs (SCEDs), N-of-1 randomised controlled trials (N-of-1 trials) and Single-Case Observational Designs (SCODs)—all with specific features (see Box 1).

SCDs can complement RCTs in a wide range of clinical research and practice contexts (Gabler et al., 2011; Smith, 2012; Punja et al., 2016; McDonald et al., 2017; Shaffer et al., 2018; Hekler et al., 2019). Since 2015, the number of SCD articles published yearly has rapidly increased. High profile articles have recently been featured in Nature (Schork, 2015) and JAMA (Stunneneberg et al., 2018). Guidelines have been published to improve SCD conduct and reporting quality, including CENT (N-of-1 trials) (Vohra et al., 2016), CENT for TCM (N-of-1 trials for traditional Chinese medicine) (Li et al., 2019), SCRIBE (SCDs in behavioral sciences) (Tate et al., 2017), and SPENT (N-of-1 protocol design) (Porcino et al., 2019).

N-of-1 randomised controlled trials (RCTs) provide an opportunity to evaluate individual-person response to interventions, by randomly allocating different time periods within an individual to repeated intervention and control conditions and then comparing responses across these periods.

N-of-1 observational studies involve the repeated measurement of an outcome (e.g., pain) in a person over time, but with no intervention implemented, in order to draw conclusions about naturally occurring patterns and predictors of outcomes over time.

Both N-of-1 RCTs and observational studies can have a ‘self-study’ design, where an individual conducts the study on themselves, to answer research questions they have generated themselves.

N-of-1 RCTs and observational studies provide individualized findings that can be aggregated to produce results equivalent to those found in traditional group-based RCTs and population-level epidemiological studies, respectively, but may require fewer people for the same statistical power.

Because of their patient-centricity, individualized results, and amenability for use by doctors to tailor therapies to individuals, SCDs are ideally placed to complement, strengthen, and generate advances in precision medicine, patient-centred healthcare, personalized health and digital health (Schork, 2015; Hekler et al., 2020).

Digital health is an exploding field, with over 1,000 relevant studies registered on clinicaltrials.gov in November 2020. Digital health includes digital therapeutics (i.e., actual interventions implemented on a digital device), patient-reported outcomes (e.g., survey responses administered via phone or web app), mobile health tools, such as wearable devices (e.g., worn sensors, implants) that can be used to monitor various aspects of an individual’s health in SCDs, along with telehealth, electronic health record systems, and data analytics tools. Digital health data can potentially be monitored continuously during the SCD, and used to help tailor a treatment to the needs and preferences of each patient. Collecting data digitally can be very convenient for participants, especially if they do not have to actively record data. SCDs can be of longer duration than group-based RCTs, so they are well suited to data collection using digital health devices and related technologies.

SCDs can be ‘self-study’ designs, wherein an individual conducts the study on themselves, to answer research questions important to them. In addition, both use techniques such as meta-analysis to aggregate individual-level findings. This can produce results equivalent to those found in traditional group-based RCTs and population-level epidemiological studies, but may require fewer people to obtain the same statistical power as a larger, group-based study. It is common for a series of SCDs to be conducted, and the results to be pooled to address issues of, e.g., generalisability and population response rate.

To acknowledge the emerging field of digital N-of-1 and SCD research, a team of experts recently completed editing a Frontiers Research Topic entitled ‘Creating Evidence from Real World Patient Digital Data’. This Frontiers Research Topic covered digital health applications, delivery, and analysis of SCDs (including self-studies) in any health discipline. It focused on mobile health (mHealth), smart phone applications (apps), wearable devices, sensors and implants, real-time tracking, data analytics, patient experience of digital health and mobile health, patients as collaborators in personalized medicine, and self-tracking efforts in the “citizen science” community.

The articles covered a selection of original research, methodology pieces, opinion pieces, and study protocols, discussing important themes including the significance of technology, emergence of the “self-scientist”, and the value of using diverse N-of-1 and SCD designs. The 13 articles written by 60 authors have already generated over 37,000 views to January 2021, reflecting the strong interest in these methods globally. The topic has had viewers from all over the world, particularly from the United States, United Kingdom, Germany, France, and China.