Table 1.

Examples of n-of-1 trials for various use cases

	Clinical question	Design features	Treatment periods	Use of washout	Analytic approach	Digital tools	Outcome assessment
Pharmacologic treatment effectiveness	Evaluate individual responses to stimulants among children with attention-deficit/hyperactivity disorder [35]	Double-blind, placebo-controlled design: stimulant vs placebo or alternative stimulant	One week per condition, 2 conditions tested (each 3x) over total 6 weeks	No washout periods	None described Responder status categorized based on symptom scores	None	Parent, teacher, and self-rating of ADHD symptoms: assessed during and at the end of each treatment period
Assess harms	Verify perceived side effects of statin tablets [36]	Double-blind, placebo-controlled design: statin vs placebo vs no tablet	One month per condition, 3 conditions tested (each 4x) over total 12 months	No washout periods	Mixed (multilevel) linear models, multiple imputation for missing data	Smartphone application to collect daily symptom scores	Self-report of side effects: assessed daily
Rare disease	Assess effects of dietary cholesterol supplementation on behavior among children with Smith-Lemli-Opitz syndrome [37]	Double-blind, placebo-controlled design: liquid egg yolks vs egg substitute (placebo)	Two weeks per condition, 2 conditions tested (each 1x) over total 10 weeks including washout periods	2-week washout with baseline cholesterol therapy between each treatment period	Paired t-test	None	Parent report of hyperactivity: assessed at the end of each 2-week treatment period
Nonpharmacological intervention	Assess the effect of bright white light therapy for depressive symptoms in cancer survivors [38]	Single-blind, sham-controlled design: bright white light vs dim red (sham)	Three weeks per condition, 2 conditions tested (each 2x) over total 12 weeks	No washout periods	Autoregressive model: treatment arm as main exposure, adjusted for time and accounting for autocorrelations of the order 1	Smartphone application to collect daily symptom scores, aggregate data by treatment period, and deliver trial results to participants	Self-reported pain, physical performance score, body weight, step count: assessed daily
Lifestyle changes	Evaluate presumed patient-selected triggers for atrial fibrillation [15]	No blinding Six 1-week periods of trigger exposure or non-exposure. Trigger examples: alcohol, caffeine, lack of sleep	One week per condition, 2 conditions tested (each 3x) over total 6 weeks	No washout periods	Bayesian generalized linear model	Smartphone application to deliver reminders on triggers, collect daily AF self-report, and deliver trial results to participants Mobile electrocardiogram device which paired with smartphone	Self-report of AF episode assessed daily, instructed to use mobile ECG device to record when they suspected an abnormal rhythm