Psychotic disorders represent the most substantial causes of disability worldwide and affect about 3% of the general population (Perälä et al., 2007). Their development is often preceded by the emergence of subclinical phenomena that do not have sufficient severity and the impact on general functioning to meet the criteria of psychotic disorders. To date, a variety of approaches have been developed to conceptualize psychosis risk states. One of them posits the existence of a categorical construct of at-risk mental state (ARMS), also known as clinical– or ultra–high risk (CHR or UHR) state. This construct captures three distinct groups of individuals, i.e., 1) brief limited intermittent psychotic symptoms (BLIPS) referring to overt psychotic experiences that remit within 7 days without the use of antipsychotic treatment; 2) attenuated psychotic symptoms (APS) – lasting at least one week but no more than five years; 3) genetic risk and/or the deterioration (GRD) syndrome – characterized by deterioration in general functioning lasting at least one month but no more than five years, and having the 1st degree relative with a history of psychosis episode or meeting the criteria for the diagnosis of schizotypal disorder (Mak et al., 2019). Another approach is related to the detection of psychotic-like experiences (PLEs) – involving hallucination-like and delusion-like phenomena that do not meet commonly accepted criteria for the diagnosis of mental disorders. They are highly prevalent affecting 5–8% of the general population (Moritz et al., 2019). However, it is important to note that PLEs are also associated with a variety of mental disorders beyond the psychosis spectrum (Healy and Cannon, 2020).

It has been shown that the risk of overt psychosis in CHR individuals is 16% within the first two years and reaches 36% at 10–11 years (Salazar de Pablo et al., 2022). Specific mechanisms underlying the development and progression of psychosis risk states remain largely unknown. Studies investigating clinical and etiological aspects of psychosis risk states often neglect the fact that they emerge in the context of routine daily activities. In this regard, understanding their dynamics and underlying mechanisms using single timepoint or retrospective assessments might be insufficient. These approaches do not provide thorough insights into real–world functioning and might serve as the source of a recall bias. Consequently, a variety of research paradigms, based on the experience sampling method (ESM), also called the ecological momentary assessment (EMA), have been proposed (Bell et al., 2023). The ESM refers to a range of techniques that aim to collect structured data within the subject's natural environment. Unlike classic assessment techniques, it provides measurements over a short period of time, thereby capturing how symptoms and levels of functioning change throughout the day (Collip et al., 2011). Most often, study participants are given a mobile device programmed to signal them repeatedly throughout the day to answer brief questions about their feelings, concerns, and thoughts (Steen et al., 2017).

It has been shown that the ESM can be used in mental health research, but the quality of the data collected depends on factors related to the design of the ESM study, the sample studied, and the protocol used. Several studies in the field have applied the ESM to understand symptom dynamics, underlying mechanisms, and the role of psychosocial stress in people with psychotic disorders or those at the preclinical stage of psychosis. It is now clearly apparent that psychotic disorders are characterized by multidimensional psychopathology that includes positive and negative symptoms, mood symptoms, and cognitive impairment (Sheffield et al., 2018). Moreover, there is evidence that psychosocial stress plays an important role in the development and progression of psychotic disorders (Krkovic et al., 2018a). The ESM provides opportunities to understand symptom dynamics taking into consideration social experiences. Numerous studies confirm that the ESM can detect differences in daily functioning (Hermans et al., 2020a; Husky et al., 2004). Apart from insights into the mechanisms of psychosis proneness, the ESM can be applied to monitor the trajectories of symptoms that might predict the development of psychosis and the efficacy of therapeutic interventions (Myin-Germeys et al., 2003).

Due to accumulating body of studies approaching the ESM to understand various aspects of psychosis risk states, it is needed to synthesize the most important findings. A recent systematic review and meta-analysis of ESM studies performed in people with mental disorders focused specifically on methodological aspects (Vachon et al., 2019). The authors found that lower compliance and retention rates in studies of male participants and those with a diagnosis of psychotic disorders. A greater compliance was associated with a fixed sampling scheme, higher incentives, longer time intervals between successive evaluations, and a lower number of evaluations per day. Additionally, no association was observed regarding the average age of the sample, study duration, or other design characteristics. However, main findings were not synthesized by this systematic review. In this regard, the present systematic review aimed to provide a qualitative synthesis of findings provided by the ESM studies conducted in people with psychosis risk states. We decided to focus a systematic review on individuals at risk of psychosis due to several reasons. First, assessment of psychological mechanisms in real-life environments of individuals at risk of psychosis might provide insights into the mechanisms underlying psychosis proneness. Second, the analysis of ESM data from individuals at risk of psychosis allows to limit potential confounding effects of therapeutic interventions that are difficult to be controlled for in patients with an established diagnosis of psychosis. Third, the analysis of real-world dynamics of symptoms and behaviors in the preclinical stage of psychosis provides opportunities to better understand the process of transition to full expression of psychotic symptoms. Therefore, the implications for interventions that aim to reduce the likelihood of transition to psychosis can be indicated.