What is quality in long covid care? Lessons from a national quality improvement collaborative and multi-site ethnography.

BACKGROUND: Long covid (post covid-19 condition) is a complex condition with diverse manifestations, uncertain prognosis and wide variation in current approaches to management. There have been calls for formal quality standards to reduce a so-called "postcode lottery" of care. The original aim of this study-to examine the nature of quality in long covid care and reduce unwarranted variation in services-evolved to focus on examining the reasons why standardizing care was so challenging in this condition. METHODS: In 2021-2023, we ran a quality improvement collaborative across 10 UK sites. The dataset reported here was mostly but not entirely qualitative. It included data on the origins and current context of each clinic, interviews with staff and patients, and ethnographic observations at 13 clinics (50 consultations) and 45 multidisciplinary team (MDT) meetings (244 patient cases). Data collection and analysis were informed by relevant lenses from clinical care (e.g. evidence-based guidelines), improvement science (e.g. quality improvement cycles) and philosophy of knowledge. RESULTS: Participating clinics made progress towards standardizing assessment and management in some topics; some variation remained but this could usually be explained. Clinics had different histories and path dependencies, occupied a different place in their healthcare ecosystem and served a varied caseload including a high proportion of patients with comorbidities. A key mechanism for achieving high-quality long covid care was when local MDTs deliberated on unusual, complex or challenging cases for which evidence-based guidelines provided no easy answers. In such cases, collective learning occurred through idiographic (case-based) reasoning, in which practitioners build lessons from the particular to the general. This contrasts with the nomothetic reasoning implicit in evidence-based guidelines, in which reasoning is assumed to go from the general (e.g. findings of clinical trials) to the particular (management of individual patients). CONCLUSION: Not all variation in long covid services is unwarranted. Largely because long covid's manifestations are so varied and comorbidities common, generic "evidence-based" standards require much individual adaptation. In this complex condition, quality improvement resources may be productively spent supporting MDTs to optimise their case-based learning through interdisciplinary discussion. Quality assessment of a long covid service should include review of a sample of individual cases to assess how guidelines have been interpreted and personalized to meet patients' unique needs. STUDY REGISTRATION: NCT05057260, ISRCTN15022307.

Rise of single-case experimental designs: A historical overview of the necessity of single-case methodology.

ABSTRACTWindelband ([1894]1980) advocated that two approaches are used for accumulating scientific knowledge. The first is the idiographic approach that derives knowledge from a single unit, and the second is the nomothetic approach that accumulates knowledge of a group. Given these two approaches, the former matches case studies while the latter is more appropriate with experimental group studies. Scientists have criticized both methodologies for their various limitations. Later, the single-case methodology emerged as an alternative that potentially allays these limitations. In this context, this narrative review aims to describe the historical roots of single-case experimental designs (SCEDs) that have emerged to eliminate the tension of nomothetic and idiographic approaches over time. First, the review focuses on the emergence of SCEDs. Second, the strengths and challenges of SCEDs are reviewed, including those to address the limitations of group experimental and case studies. Third, the use and analyses of SCEDs are outlined, considering their current status. Fourth, this narrative review continues to delineate the dissemination of SCEDs in the modern scientific world. As a result, SCEDs can be evaluated as a method that has the potential to overcome the issues encountered in case description and group experimental research. Thus, that helps accumulate nomothetic and idiographic knowledge in determining evidence-based practices.

Temporal Directionality Between Symptoms During Treatment of Depressed Inpatients: A Dynamic Time Warp Network Analysis.

BACKGROUND: Depression is generally perceived from the perspective of the common-cause disease model. However, the network perspective assumes mutual influence of individual symptoms and stresses the importance of investigating symptom dynamics. Gaining a better understanding of symptom dynamics within individuals might contribute to more effective treatments. METHODS: Current exploratory longitudinal research studied the associations and directionality between 43 symptoms from the generic questionnaire Symptom Questionnaire-48 (SQ-48) using dynamic time warp (DTW) analyses, in which trajectories with similar time-dependent patterns can be identified. Data from individuals were analysed first, yielding distance matrices for all symptom trajectories, after which the data were aggregated. RESULTS: The 148 included patients were all admitted for the treatment of their clinical depression. Undirected DTW analyses of three patients with longer time series but otherwise randomly chosen showed large variability among individuals. Group-level undirected DTW analyses showed numerous significant edges between symptoms, largely clustering symptoms according to the eight pre-existing subscales of the SQ-48. Group-level directed DTW analyses showed five symptoms with significant outstrength: 'hopeless', 'restless', 'down/depressed', 'feeling tense' and 'no enjoyment', meaning that change in these key symptoms preceded change in other symptoms. LIMITATIONS: The 43 included symptoms of the SQ-48 primarily focus on internalizing problems in severely depressed inpatients, potentially limiting generalizability. CONCLUSIONS: DTW networks provided us with five key symptoms based on the dynamics of symptom scores. Future studies could explore whether process-based therapy targeted at symptoms with high outstrength might result in more effectivity as part of personalized treatment.

Assessing current concerns and goals idiographically: A review of the Motivational Structure Questionnaire family of instruments.

BACKGROUND: There have been two kinds of methods for assessing individuals' motivation and their goal-striving behavior. The idiographic method obtains respondents' individual descriptions of their behavior or inner experiences. The nomothetic approach uses a standardized questionnaire in which respondents select from a set of alternatives. Idiographic responses provide rich, individualized information, but they make comparisons across different individuals difficult. By contrast, the nomothetic approach loses valuable individualized information, but it readily lends itself to cross-individual comparisons. OBJECTIVE: The present authors have developed a family of motivational assessment instruments within the framework of the Goal Theory of Current Concerns and individuals' goal pursuits. Each of these instruments is a hybrid version of the idiographic and nomothetic methods. Each one obtains individualized information about each respondent at the start of the assessment, but it then utilizes rating scales that allow comparisons across different individuals to be made. The objective of the present article is to present this family of hybridized instruments for potential use in routine outcome monitoring. METHOD: The method used in this article was to review the development of this family of hybrid assessments instruments over the preceding decades and the research on their psychometric properties and clinical applications. These hybrid tools include the Interview Questionnaire, Work Concerns Inventory, Motivational Structure Questionnaire, and Personal Concerns Inventory and their variants. The review includes only the idiographic-nomothetic approaches that are based on the Goal Theory of Current Concerns. RESULTS: The review reveals that for each instrument, motivational indices are calculated, which have been shown to be valid and reliable. Analyses have also revealed adaptive and maladaptive motivational factors. CONCLUSIONS: The measures discussed here have proven useful in clinical applications, when, for example, they are used as components of Systematic Motivational Counseling and the Life Enhancement and Advancement Programme for helping individuals improve their motivational structure. Similarly, the measures hold promise for use in routine outcome monitoring.

A Square-Root Second-Order Extended Kalman Filtering Approach for Estimating Smoothly Time-Varying Parameters.

Researchers collecting intensive longitudinal data (ILD) are increasingly looking to model psychological processes, such as emotional dynamics, that organize and adapt across time in complex and meaningful ways. This is also the case for researchers looking to characterize the impact of an intervention on individual behavior. To be useful, statistical models must be capable of characterizing these processes as complex, time-dependent phenomenon, otherwise only a fraction of the system dynamics will be recovered. In this paper we introduce a Square-Root Second-Order Extended Kalman Filtering approach for estimating smoothly time-varying parameters. This approach is capable of handling dynamic factor models where the relations between variables underlying the processes of interest change in a manner that may be difficult to specify in advance. We examine the performance of our approach in a Monte Carlo simulation and show the proposed algorithm accurately recovers the unobserved states in the case of a bivariate dynamic factor model with time-varying dynamics and treatment effects. Furthermore, we illustrate the utility of our approach in characterizing the time-varying effect of a meditation intervention on day-to-day emotional experiences.

Within- and across-day patterns of interplay between depressive symptoms and related psychopathological processes: a dynamic network approach during the COVID-19 pandemic.

BACKGROUND: In order to understand the intricate patterns of interplay connected to the formation and maintenance of depressive symptomatology, repeated measures investigations focusing on within-person relationships between psychopathological mechanisms and depressive components are required. METHODS: This large-scale preregistered intensive longitudinal study conducted 68,240 observations of 1706 individuals in the general adult population across a 40-day period during the COVID-19 pandemic to identify the detrimental processes involved in depressive states. Daily responses were modeled using multi-level dynamic network analysis to investigate the temporal associations across days, in addition to contemporaneous relationships between depressive components within a daily window. RESULTS: Among the investigated psychopathological mechanisms, helplessness predicted the strongest across-day influence on depressive symptoms, while emotion regulation difficulties displayed more proximal interactions with symptomatology. Helplessness was further involved in the amplification of other theorized psychopathological mechanisms including rumination, the latter of which to a greater extent was susceptible toward being influenced rather than temporally influencing other components of depressive states. Distinctive symptoms of depression behaved differently, with depressed mood and anhedonia most prone to being impacted, while lethargy and worthlessness were more strongly associated with outgoing activity in the network. CONCLUSIONS: The main mechanism predicting the amplifications of detrimental symptomatology was helplessness. Lethargy and worthlessness revealed greater within-person carry-over effects across days, providing preliminary indications that these symptoms may be more strongly associated with pushing individuals toward prolonged depressive state experiences. The psychopathological processes of rumination, helplessness, and emotion regulation only exhibited interactions with the depressed mood and worthlessness component of depression, being unrelated to lethargy and anhedonia. The findings have implications for the impediment of depressive symptomatology during and beyond the pandemic period. They further outline the gaps in the literature concerning the identification of psychopathological processes intertwined with lethargy and anhedonia on the within-person level.

Network Mapping with GIMME.

Network science is booming! While the insights and images afforded by network mapping techniques are compelling, implementing the techniques is often daunting to researchers. Thus, the aim of this tutorial is to facilitate implementation in the context of GIMME, or group iterative multiple model estimation. GIMME is an automated network analysis approach for intensive longitudinal data. It creates person-specific networks that explain how variables are related in a system. The relations can signify current or future prediction that is common across people or applicable only to an individual. The tutorial begins with conceptual and mathematical descriptions of GIMME. It proceeds with a practical discussion of analysis steps, including data acquisition, preprocessing, program operation, a posteriori testing of model assumptions, and interpretation of results; throughout, a small empirical data set is analyzed to showcase the GIMME analysis pipeline. The tutorial closes with a brief overview of extensions to GIMME that may interest researchers whose questions and data sets have certain features. By the end of the tutorial, researchers will be equipped to begin analyzing the temporal dynamics of their heterogeneous time series data with GIMME.

Nesselroade and Molenaar's Measurement Concerns and Proposals: An Introduction.

In this special section Nesselroade and Molenaar (N & M) propose a provocative new approach to measurement invariance. When measures are collected repeatedly over time (e.g., daily diary studies), a potentially unique measurement model relating the items to the underlying construct can be created for each individual. If hypothesized causal paths specified between constructs (e.g., frustration → aggression) can be constrained to be equal across the individuals, a model with idiographic measurement of the constructs, but with nomothetic structural relationships can be specified. Three commentaries react to N & M's proposal. Revelle and Wilt challenge the priority given by N & M to unique individual measurement structures, arguing that between subjects differences in structural relationships are empirically important and meaningful. Markus's uses David Hume's framework to raise philosophy of science challenges for N & M's approach. Maydeu-Olivares challenges the incremental validity of N & M's approach, arguing that N & M's approach is unlikely to improve the prediction of between subjects criteria. Finally, N & M present a rejoinder to the three commentaries.

When Average Isn't Good Enough: Identifying Meaningful Subgroups in Clinical Data.

Background: Clinical data are usually analyzed with the assumption that knowledge gathered from group averages applies to the individual. Doing so potentially obscures patients with meaningfully different trajectories of therapeutic change. Needed are "idionomic" methods that first examine idiographic patterns before nomothetic generalizations are made. The objective of this paper is to test whether such an idionomic method leads to different clinical conclusions. Methods: 51 patients completed weekly process measures and symptom severity over a period of eight weeks. Change trajectories were analyzed using a nomothetic approach and an idiographic approach with bottom-up clustering of similar individuals. The outcome was patients' well-being at post-treatment. Results: Individuals differed in the extent that underlying processes were linked to symptoms. Average trend lines did not represent the intraindividual changes well. The idionomic approach readily identified subgroups of patients that differentially predicted distal outcomes (well-being). Conclusions: Relying exclusively on average results may lead to an oversight of intraindividual pathways. Characterizing data first using idiographic approaches led to more refined conclusions, which is clinically useful, scientifically rigorous, and may help advance individualized psychotherapy approaches. Supplementary Information: The online version contains supplementary material available at 10.1007/s10608-023-10453-x.

The analgesic effect of nostalgia elicited by idiographic and nomothetic approaches on thermal stimulus.

Nostalgia is shown to relieve an individual's perception of pain evoked by cold water, pressure, and thermal stimuli. However, there is no direct evidence to show the analgesic effects of different nostalgia-inducing methods on various stimulus intensities. We conducted two studies to examine the analgesic effect, at different pain intensities, after inducing nostalgia either idiographically or nomothetically. Study 1 (N = 118) induced nostalgia through an idiographic approach (i.e., event reflection task) and found that nostalgia relieved both high and low thermal pain. Study 2 (N = 66) induced nostalgia through a nomothetic approach (i.e., viewing nostalgic pictures) and found that nostalgia relieved low but not high thermal pain. The findings verify the analgesic effect of nostalgia on thermal pain and suggest the potential moderating role of the nostalgia induction approach and pain intensity. Practically, these findings have implications for using nostalgia as a nonpharmacological treatment for pain.

Pathway Phenotypes Underpinning Depression, Anxiety, and Chronic Fatigue Symptoms Due to Acute Rheumatoid Arthritis: A Precision Nomothetic Psychiatry Analysis.

Rheumatoid arthritis (RA) is a chronic inflammatory and autoimmune disorder which affects the joints in the wrists, fingers, and knees. RA is often associated with depressive and anxiety symptoms as well as chronic fatigue syndrome (CFS)-like symptoms. This paper examines the association between depressive symptoms (measured with the Beck Depression Inventory, BDI), anxiety (Hamilton Anxiety Rating Scale, HAMA), CFS-like (Fibro-fatigue Scale) symptoms and immune-inflammatory, autoimmune, and endogenous opioid system (EOS) markers, and lactosylcer-amide (CD17) in RA. The serum biomarkers were assayed in 118 RA and 50 healthy controls. Results were analyzed using the new precision nomothetic psychiatry approach. We found significant correlations between the BDI, FF, and HAMA scores and severity of RA, as assessed with the DAS28-4, clinical and disease activity indices, the number of tender and swollen joints, and patient and evaluator global assessment scores. Partial least squares analysis showed that 69.7% of the variance in this common core underpinning psychopathology and RA symptoms was explained by immune-inflammatory pathways, rheumatoid factor, anti-citrullinated protein antibodies, CD17, and mu-opioid receptor levels. We constructed a new endophenotype class comprising patients with very high immune-inflammatory markers, CD17, RA, affective and CF-like symptoms, and tobacco use disorder. We extracted a reliable and replicable latent vector (pathway phenotype) from immune data, psychopathology, and RA-severity scales. Depression, anxiety, and CFS-like symptoms due to RA are manifestations of the phenome of RA and are mediated by the effects of the same immune-inflammatory, autoimmune, and other pathways that underpin the pathophysiology of RA.

How do social factors relate to blunted facial affect in schizophrenia? A digital phenotyping study using ambulatory video recordings.

Clinical interviews and laboratory-based emotional induction paradigms provide consistent evidence that facial affect is blunted in many individuals with schizophrenia. Although it is clear that blunted facial affect is not a by-product of diminished emotional experience in schizophrenia, factors contributing to blunted affect remain unclear. The current study used a combination of ambulatory video recordings that were evaluated via computerized facial affect analysis and concurrently completed ecological momentary assessment surveys to assess whether blunted affect reflects insufficient reactivity to affective or contextual factors. Specifically, whether individuals with schizophrenia require more intense affective experiences to produce expression, or whether they are less reactive to social factors (i.e. being in the presence of others, social motivation). Participants included outpatients with schizophrenia (n = 33) and healthy controls (n = 31) who completed six days of study procedures. Multilevel linear models were evaluated using both Null-Hypothesis Statistical Testing and Bayesian analyses. Individuals with schizophrenia displayed comparable expression of positive and negative emotion to controls during daily life, and no evidence was found for a different intensity of experience required for expression in either group. However, social factors differentially influenced facial expression in schizophrenia compared to controls, such that individuals with schizophrenia did not modulate their expressions based on social motivation to the same extent as controls. These findings suggest that social motivation may play an important role in determining when blunting occurs.

False dogmas in mood disorders research: Towards a nomothetic network approach.

The current understanding of major depressive disorder (MDD) and bipolar disorder (BD) is plagued by a cacophony of controversies as evidenced by competing schools to understand MDD/BD. The DSM/ICD taxonomies have cemented their status as the gold standard for diagnosing MDD/BD. The aim of this review is to discuss the false dogmas that reign in current MDD/BD research with respect to the new, data-driven, machine learning method to model psychiatric illness, namely nomothetic network psychiatry (NNP). This review discusses many false dogmas including: MDD/BD are mind-brain disorders that are best conceptualized using a bio-psycho-social model or mind-brain interactions; mood disorders due to medical disease are attributable to psychosocial stress or chemical imbalances; DSM/ICD are the gold standards to make the MDD/BD diagnosis; severity of illness should be measured using rating scales; clinical remission should be defined using threshold values on rating scale scores; existing diagnostic BD boundaries are too restrictive; and mood disorder spectra are the rule. In contrast, our NNP models show that MDD/BD are not mind-brain or psycho-social but systemic medical disorders; the DSM/ICD taxonomies are counterproductive; a shared core, namely the reoccurrence of illness (ROI), underpins the intertwined recurrence of depressive and manic episodes and suicidal behaviors; mood disorders should be ROI-defined; ROI mediates the effects of nitro-oxidative stress pathways and early lifetime trauma on the phenome of mood disorders; severity of illness and treatment response should be delineated using the NNP-derived causome, pathway, ROI and integrated phenome scores; and MDD and BD are the same illness.

Using temporal network methods to reveal the idiographic nature of development.

Averages dominate developmental science: There are representative groups, mean trajectories, and generalizations to typical children. Nearly all parents and teachers, however, eagerly proclaim that few youth are average; each child, adolescent, and young adult is unique. Indeed, individual youth are the focus of many eminent developmental theories, yet there is a shocking paucity of developmental methods-including study designs and analysis techniques-that truly afford individual-level inferences. Thus, the goal of this chapter is to explicate the advantages of an idiographic approach to developmental science, that is, an approach that provides insight into individual youth, often by studying within-person variation in intensive longitudinal data, such as densely coded observations, repeated daily or momentary assessments, and functional neuroimages. In three domains across development, the chapter illustrates the benefits of an idiographic approach by comparing empirical conclusions offered by traditional mean-based analysis techniques versus techniques that leverage the temporal and individualized nature of intensive longitudinal data. The chapter then concentrates on group iterative multiple model estimation (GIMME), which is an analysis technique that uses intensive longitudinal data to create youth-specific temporal networks, detailing how brain regions or behaviors are directionally related across time. The promise of GIMME is exemplified by applications to three different domains across development. The chapter closes by encouraging future idiographic developmental science to consider how research questions, study designs, and data analyses can be formed, implemented, and conducted in ways that optimize inferences about individual-not average-youth.

Psychology's Status as a Science: Peculiarities and Intrinsic Challenges. Moving Beyond its Current Deadlock Towards Conceptual Integration.

Psychology holds an exceptional position among the sciences. Yet even after 140 years as an independent discipline, psychology is still struggling with its most basic foundations. Its key phenomena, mind and behaviour, are poorly defined (and their definition instead often delegated to neuroscience or philosophy) while specific terms and constructs proliferate. A unified theoretical framework has not been developed and its categorisation as a 'soft science' ascribes to psychology a lower level of scientificity. The article traces these problems to the peculiarities of psychology's study phenomena, their interrelations with and centrality to everyday knowledge and language (which may explain the proliferation and unclarity of terms and concepts), as well as to their complex relations with other study phenomena. It shows that adequate explorations of such diverse kinds of phenomena and their interrelations with the most elusive of all-immediate experience-inherently require a plurality of epistemologies, paradigms, theories, methodologies and methods that complement those developed for the natural sciences. Their systematic integration within just one discipline, made necessary by these phenomena's joint emergence in the single individual as the basic unit of analysis, makes psychology in fact the hardest science of all. But Galtonian nomothetic methodology has turned much of today's psychology into a science of populations rather than individuals, showing that blind adherence to natural-science principles has not advanced but impeded the development of psychology as a science. Finally, the article introduces paradigmatic frameworks that can provide solid foundations for conceptual integration and new developments.

Construction of an exposure-pathway-phenotype in children with depression due to transfusion-dependent thalassemia: Results of (un)supervised machine learning.

BACKGROUND: Transfusion dependent thalassemia (TDT) patients are treated with continued blood transfusions and show a higher prevalence of depression. TDT with consequent iron overload and inflammation is associated with increased severity of depressive symptoms in TDT children. AIM OF THE STUDY: To construct a pathway-phenotype which combines iron overload and neuro-immune biomarkers with depressive symptom subdomains in TDT children. METHODS: We measured iron status parameters (iron, ferritin, transferrin saturation percentage) and inflammatory (interleukin-1ß and tumour necrosis factor-α) biomarkers in TDT (n=111) and healthy (n=53) children and analyzed the results using machine learning. RESULTS: Cluster analysis separated TDT children with depression from those without depression and revealed two depressive subgroups one with low self-esteem and another with increased social-irritability scores. Exploratory factor analysis validated four depressive symptom dimensions as reliable constructs, namely key depressive, physiosomatic, lowered self-esteem and social-irritability dimensions. Partial Least Squares showed that 73.0% of the variance in a latent vector extracted from those four clinical subdomains, immune-inflammatory and iron overload biomarkers was explained by exposure variables including the number of blood transfusions and hospitalizations and use of deferoxamine. The exposure data, iron and immune biomarkers, and symptom subdomains are reflective manifestations of a single latent trait, which shows internal consistency reliability and predictive relevance. CONCLUSIONS: The nomological network combining exposure, pathways and behavioral phenome manifestations provides an index of overall severity and disease risk and, therefore, constitutes a new drug target, indicating that iron overload and immune activation should be targeted to treat depression due to TDT.

Single-Subject Research in Psychiatry: Facts and Fictions.

Scientific evidence in the field of psychiatry is mainly derived from group-based ("nomothetic") studies that yield group-aggregated results, while often the need is to answer questions that apply to individuals. Particularly in the presence of great inter-individual differences and temporal complexities, information at the individual-person level may be valuable for personalized treatment decisions, individual predictions and diagnostics. The single-subject study design can be used to make inferences about individual persons. Yet, the single-subject study is not often used in the field of psychiatry. We believe that this is because of a lack of awareness of its value rather than a lack of usefulness or feasibility. In the present paper, we aimed to resolve some common misconceptions and beliefs about single-subject studies by discussing some commonly heard "facts and fictions." We also discuss some situations in which the single-subject study is more or less appropriate, and the potential of combining single-subject and group-based study designs into one study. While not intending to plea for single-subject studies at the expense of group-based studies, we hope to increase awareness of the value of single-subject research by informing the reader about several aspects of this design, resolving misunderstanding, and providing references for further reading.

The Experiences of Homeless Youth When Using Strengths Profiling to Identify Their Character Strengths.

Individuals, particularly those considered "hard-to-reach," often engage well with assessment tools that involve active dialogue and the co-construction of knowledge. Strengths profiling is one such tool that enables a person-centered and autonomy supportive approach to the identification of character strengths. Strength profiling is an adaptation of performance profiling used in sport psychology, which has not yet been utilized in broader psychological research or clinical practice. Supporting an individual by raising awareness of their personal character strengths is an effective and growing mechanism for promoting psychological well-being. Strengths profiling involves several stages of exploring, defining, and assessing character strengths, leading to the identification of signature strengths and goals for future development. Informed by personal construct theory, the present study explored the experiences of homeless young people living in sheltered accommodation (N = 116), when using strengths profiling at the start and end of a 10-week, strengths-based intervention. Mixed-method data was obtained from the strengths profiles, questionnaires measuring resilience, self-worth, and well-being, and diary entries. Findings revealed a rich array of character strength terminology and individual meanings. Participants found strengths profiling to be highly engaging, particularly due to their active role in strength identification, which prompted interesting and meaningful reflections on character strengths that were pertinent to them. Participants felt their signature strengths were vital protective factors within their lives and strengths profiles were correlated with resilience, self-worth, and well-being. Character strengths and resilience were also significantly and meaningfully improved pre/post-intervention, providing support for the use of strengths profiling as a tool for monitoring change in character strength perceptions. Overall, this study demonstrates the utility and versatility of strengths profiling as a new method in the discipline of positive psychology and strengths-based research and applied practice.

Intentional research design in implementation science: implications for the use of nomothetic and idiographic assessment.

The advancement of implementation science is dependent on identifying assessment strategies that can address implementation and clinical outcome variables in ways that are valid, relevant to stakeholders, and scalable. This paper presents a measurement agenda for implementation science that integrates the previously disparate assessment traditions of idiographic and nomothetic approaches. Although idiographic and nomothetic approaches are both used in implementation science, a review of the literature on this topic suggests that their selection can be indiscriminate, driven by convenience, and not explicitly tied to research study design. As a result, they are not typically combined deliberately or effectively. Thoughtful integration may simultaneously enhance both the rigor and relevance of assessments across multiple levels within health service systems. Background on nomothetic and idiographic assessment is provided as well as their potential to support research in implementation science. Drawing from an existing framework, seven structures (of various sequencing and weighting options) and five functions (Convergence, Complementarity, Expansion, Development, Sampling) for integrating conceptually distinct research methods are articulated as they apply to the deliberate, design-driven integration of nomothetic and idiographic assessment approaches. Specific examples and practical guidance are provided to inform research consistent with this framework. Selection and integration of idiographic and nomothetic assessments for implementation science research designs can be improved. The current paper argues for the deliberate application of a clear framework to improve the rigor and relevance of contemporary assessment strategies.

Microaggressions and Daily Experience.

Psychologists use the term microaggressions to describe subtle forms of bias and discrimination experienced by members of marginalized groups. Lilienfeld (2017, this issue) makes an important contribution to the literature by presenting a critical review of the meaning and measurement of microaggression experiences. In this commentary, we argue that advancing the construct of microaggressions rests on research approaches that move beyond static representations of individuals to dynamic frameworks that observe people's lives as they unfold day to day. We discuss the conceptual potential of microaggressions as a bridging concept across multiple levels of analysis. We conclude that the intensive study of individuals over time can contribute to theory evaluation and offer new insights into the nature of unfolding processes that are theorized to be central to the manifestation of microaggressions in everyday life.