Mental health problems are not readily assessable by objective means. Research instead relies on self-report scales, structured clinical interviews or clinician assessments to determine whether an individual is experiencing a mental health problem. Clinical assessment takes significant time and is rarely feasible in a population setting, while self-report measures may have modest precision. Reporting burden is further exacerbated by the breadth of potential mental health problems that an individual may experience. New self-report approaches to assessment have promise in delivering rapid, precise indications of mental health status. Two large population-based study (N>3000 each) have tested new methods to assess a range of mental health problems. Drawing from items in existing measures, item banks for eight mental health domains were developed (panic, social anxiety, post-traumatic stress, obsessive-compulsive, adult attention-deficit hyperactivity, psychosis, drug use, suicidality) with another four existing item banks (depression, anxiety, anger, alcohol use) also tested. After elimination of items that displayed lack of fit, local dependence or measurement non-invariance, validation of the item banks using item response theory demonstrated high precision across all item banks. Subsequently, brief measures for each mental health dimension and screeners for individual disorder have been developed and revalidated, showing greater accuracy across each mental health dimension than existing mental health measures. In addition, multidimensional scales and screeners to rapidly identify a spectrum of mental health problems are being developed and tested. A new 5-item distress screener developed through this process (the DQ-5) has been shown to be more accurate than existing screeners (K6, K10) in identifying a range of mental disorders, with significantly greater AUC, sensitivity and specificity than the K6 across six mental disorders. This new approach to mental health assessment shows great promise in reducing reporting burden while maintaining high precision.