All good things come in threes: A systematic review and Delphi study on the advances and challenges of ambulatory assessments, network analyses, and single-case experimental designs.

Abstract

This article reviewed 47 methodological publications critically evaluating ambulatory assessments (AA), network analyses (NA), and single-case experimental designs (SCED) for psychotherapy research and practice. To develop a consensus about the most essential advances and challenges, we invited methodological and clinical experts to participate in a subsequent Delphi study. The experts agreed upon 17 essential advances (e.g., AA particularly disentangles within-and between-psychological processes; NA improves the conceptualization of interacting symptoms, and SCED provides a promising tool for initial proof-of-principle studies). They agreed upon 10 major challenges (e.g., to provide standardized, clear-cut recommendations and userfriendly tools). We discuss how future research could combine rigorous sampling schemes (AA) with a more holistic view on interacting symptoms (NA) and/or a systematic experimental manipulation (SCED). Public Health Significance StatementWe reviewed and evaluated major advancements and challenges of new research methods for psychotherapy research and practice: Ambulatory assessments disentangle within-and between-psychological processes; network analyses are valuable for conceptualizing interacting symptoms; singlecase experimental designs are a promising tool for providing initial proof of principles. Future research urgently needs to provide clear-cut recommendations and user-friendly tools to contribute to the further dissemination of these methods.

On the need for theory-building and robust causal inference in idiographic network analysis.

“…Because the introduction of the network theory of mental disorders (Borsboom, 2017), the statistical methods underlying it have been enthusiastically embraced by researchers. In the present study, the top consensus statement on network analysis was as follows: “The major advantage of the network analysis approach is that symptoms are conceptualized as mutually interacting, often reciprocally reinforcing elements of a complex network” (Schemer et al, 2022, p. 38). This statement points to an issue that Fried (2020) has already laid out very comprehensively, namely the need to distinguish between theoretical and statistical models.…”

“…More than 18 years ago, Molenaar (2004) published his manifesto on psychology as an idiographic science. In this issue, Schemer et al (2022) report the results of a Delphi survey on three important methodological contributions that could accelerate the uptake of idiographic research in clinical psychology: ambulatory assessment, network analysis and single-case experimental designs (SCED). The results provide a useful insight into the current state of practice in idiographic clinical-psychological research, as they reflected a general enthusiasm about the opportunities idiographic research offers.…”

“…The second consensus statement on the clinical implications of the centrality of symptoms: “The network perspective contributes to the identification of central symptom patterns which are risk or protective factors for developing a full-blown episode” (Schemer et al, 2022, p. 38). As Fried (2020) noted, the use of centrality values for clinical-level inference requires strong assumptions about the causal structure of the underlying data-generating process.…”

Leveraging single-case experimental designs to promote personalized psychological treatment: Step-by-step implementation protocol with stakeholder involvement for a single-case outpatient clinic

“…Single-case experimental designs (SCEDs 1 ) are time-and cost-efficient, yet methodologically sound, prospective idiographic research designs (Nikles et al, 2021) that could be particularly promising to be implemented in routine clinical care (Schemer et al, 2022). Per definition, SCEDs have the following key features: (1) One entity (e.g., a person) that serves as its own control, (2) is observed repeatedly during a certain period of time (for example via experience sampling methodology, ESM 2 ), and (3) under systematic manipulation (e.g., introduction of a psychological treatment) (Vlaeyen et al, 2022).…”

“…SCEDs seek to estimate meaningful treatment effects for individual patients while safeguarding internal validity and causal inference (Kazdin, 2019;Tanious & Onghena, 2019;Vlaeyen et al, 2020). In combination with experience sampling methods (ESM), the methodological rigor of SCEDs can be further increased (Schemer et al, 2022).…”