Modeling and estimating the feedback mechanisms among depression, rumination, and stressors in adolescents

The mediating roles of interpersonal sensitivity and rumination in the relationship between self-esteem and depression: a longitudinal study on Chinese psychiatric patients

This study examined the relationship between self-esteem, interpersonal sensitivity, rumination, and depression in psychiatric patients. Participants included 159 adults with major depressive disorder (MDD) or generalized anxiety disorder (GAD) (Age: M = 31.69, SD = 11.54; 70.4% Female). The study measured depression, self-esteem and interpersonal sensitivity at T1 and rumination and depression at T2 after 10 to 14 days. The study found that after controlling for depression at T1, age, gender, and measurement time interval, low self-esteem at T1 could impact depression at T2 through the mediation of reflection at T2, as well as through the chain mediation of interpersonal sensitivity at T1 and rumination at T2. The results indicated that for patients of MDD or GAD with low self-esteem, we could pay attention to intervening with rumination and interpersonal sensitivity, such as applying rumination-focused cognitive behavioral therapy or interpersonal psychotherapy.

Effects of physical activity on sleep quality among university students: chain mediation between rumination and depression levels

BACKGROUND

Colleges and universities are currently facing the major public health issue of poor sleep quality. Sleep quality must be taken seriously to maintain the students' emotional and physical well-being. Thus, this study sought to determine how university students' levels of physical activity related to the quality of their sleep, as well as to explore the mechanisms via which physical activity affects sleep and provide suggestions for improving it.

METHODS

A total of 883 university students from Ganzhou City, Jiangxi Province, China participated in the study. Their physical activity, sleep quality, ruminative thinking levels, and depression were assessed using various questionnaires.

RESULTS

Through the mediating effects of rumination and depression as well as the chain-mediated effects of these two factors, physical exercise changed the quality of sleep.

CONCLUSION

University students' sleep quality can be improved by increasing their physical activity and decreasing ruminative thinking and depression levels.

Dealing with soft variables and data scarcity: lessons learnt from quantification in a participatory system dynamics modelling process

System dynamics (SD) models are commonly used for structuring complex problems to support decision-making. They are used to investigate areas in which limited knowledge is available, describing nonlinear relationships and including intangible elements. Although this explorative nature is one of the key advantages, it also represents a challenge for quantifying the intangible, i.e. more qualitative aspects of an SD model, especially when it is not possible to apply conventional analytical methods due to data scarcity. Procedures to obtain and analyse information using participatory approaches are limited. First, this article outlines existing quantification methods and related open questions when dealing with soft variables and data scarcity. Secondly, it summarises the quantification process developed during a participatory SD process, describing how we dealt with data scarcity and soft variables. Lastly, we suggest a quantification framework in relation to data availability and level of stakeholder engagement.

The influence of stress on mental health among Chinese college students: The moderating role of psychological suzhi

Depending on its duration, stress can be divided into chronic and acute stress, both of which can be detrimental to an individual's mental health. Psychological suzhi may act as a protective factor that buffers the adverse effects of stress. This study aimed to explore the moderating role of psychological suzhi in the relationship between these two types of stress and mental health based on a dual-factor model of mental health. Study 1 explored the moderating role of psychological suzhi on the relationship between chronic stress and mental health using the Adolescent Self-Rating Life Events Check List, College Student Psychological Suzhi Scale Brief Mental Health Version, Satisfaction With Life Scale, and 12-item General Health Questionnaire to investigate 919 Chinese college students. A hierarchical regression model was used to examine the moderating effects. Study 2 examined the moderating role of psychological suzhi on the relationship between acute stress and mental health. Participants (N = 56) were classified into high (N = 30) and low (N = 26) psychological suzhi groups based on the Psychological Suzhi Scale. They completed the Trier Social Stress Test for Groups and a specific control condition, and their state anxiety and happiness levels were assessed. Data were analyzed using a mixed-design repeated-measures ANOVA. The results of Study 1 revealed that psychological suzhi moderated the influence of chronic stress on the negative indicator of mental health (psychological symptoms) (β = -0.18, t = -6.90, p < 0.001). The results of Study 2 showed that psychological suzhi moderated the effect of acute stress on the negative indicator of mental health (state anxiety) [F (1, 54) = 4.79, p < 0.05, η2 = 0.08]. Psychological suzhi can moderate the influence of both chronic and acute stress on the negative indicators of college students' mental health but cannot moderate the influence on the positive indicators of mental health.

The need for systems thinking to advance Alzheimer's disease research

Despite extensive research efforts to mechanistically understand late-onset Alzheimer's disease (LOAD) and other complex mental health disorders, curative treatments remain elusive. We emphasize the multiscale multicausality inherent to LOAD, highlighting the interplay between interconnected pathophysiological processes and risk factors. Systems thinking methods, such as causal loop diagrams and systems dynamic models, offer powerful means to capture and study this complexity. Recent studies developed and validated a causal loop diagram and system dynamics model using multiple longitudinal data sets, enabling the simulation of personalized interventions on various modifiable risk factors in LOAD. The results indicate that targeting factors like sleep disturbance and depressive symptoms could be promising and yield synergistic benefits. Furthermore, personalized interventions showed significant potential, with top-ranked intervention strategies differing significantly across individuals. We argue that systems thinking approaches can open new prospects for multifactorial precision medicine. In future research, systems thinking may also guide structured, model-driven data collection on the multiple interactions in LOAD's complex multicausality, facilitating theory development and possibly resulting in effective prevention and treatment options.

Emotion Regulation Predicts Depressive Symptoms in Adolescents: A Prospective Study

Emotion regulation as a proximal factor has been linked with depressive symptoms. However, studies have mainly focused on a limited number of strategies and have mostly been cross-sectional in design. This is particularly evident when examining the protective effects of adaptive strategies. This study aimed to investigate the prospective relationship between putatively adaptive and maladaptive emotion regulation strategies and depressive symptoms among adolescents. Additionally, a person-oriented approach was applied to identify latent classes of adolescents based on their depressive symptoms and compared these classes in terms of their adaptive and maladaptive strategies. Two waves of data from a prospective study, which included 1371 youth (mean age: 15.66 years; SD = 0.49 years; 55.1% girls), were analysed. The two points of data collection were spaced approximately half a year apart. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale, and putatively adaptive and maladaptive emotion regulation strategies were assessed with the Cognitive Emotion Regulation Questionnaire. Seven strategies (acceptance, positive refocusing, positive reappraisal, putting into perspective, self-blame, rumination, and catastrophizing) were categorised into adaptive and maladaptive factors using exploratory structural equation modeling. After controlling for gender, age, and depressive symptoms at Time 1, both maladaptive and adaptive emotion regulation strategies at Time 1 predicted depressive symptoms at Time 2. Three subgroups emerged based on the intensity of depressive symptoms across the waves: the stable low, stable moderate, and stable high depressive symptom groups. The use of maladaptive emotion regulation strategies (such as rumination, self-blame, and catastrophizing) at Time 1 was more pronounced in the stable moderate and high symptom groups compared to the stable low depressive symptom group. The comparable prospective associations between putatively adaptive and maladaptive strategies with symptoms suggest the need to identify factors that may mitigate the negative impact of maladaptive emotion regulation and/or promote adaptive emotion regulation to buffer the effects of everyday stressors.

Brooding and neuroticism are strongly interrelated manifestations of the phenome of depression

Introduction

We found that neuroticism may be identified as a subclinical manifestation of the phenome of depression, comprising depressive and anxiety symptoms, and suicidal behaviors. Rumination is positively associated with depression and neuroticism and may mediate the effects of neuroticism on depression. This study aimed to determine whether rumination or its components, including brooding or reflection, mediate the effects of neuroticism on depression or, alternatively, whether both neuroticism and rumination are manifestations of the phenome of depression.

Methods

This study recruited 74 depressed subjects and 44 healthy controls. The depression group was split into groups with high versus low brooding scores. We used partial least squares (PLS) to examine mediation effects.

Results

We found that brooding and reflection scores are significantly higher in depressed patients than in controls. Patients with higher brooding scores have increased severity of depression, anxiety, insomnia, neuroticism, and current suicidal ideation as compared with patients with lower brooding scores and controls. There is a strong positive association between rumination, and neuroticism, depression, anxiety, and lifetime and current suicidal behaviors. PLS analysis shows that brooding does not mediate the effects of neuroticism on the depression phenome because no discriminant validity could be established between neuroticism and brooding, or between neuroticism and brooding and the depression phenome. We were able to extract one validated latent vector from brooding and neuroticism, insomnia, depression, anxiety, and current suicidal behaviors.

Conclusion

Overall, this study supports the theory that rumination and neuroticism are reflective manifestations of the phenome of depression.

Exploring the potential impact of multi-factor precision interventions in Alzheimer's disease with system dynamics

Numerous clinical trials based on a single-cause paradigm have not resulted in efficacious treatments for Alzheimer's disease (AD). Recently, prevention trials that simultaneously intervened on multiple risk factors have shown mixed results, suggesting that careful design is necessary. Moreover, intensive pilot precision medicine (PM) trial results have been promising but may not generalize to a broader population. These observations suggest that a model-based approach to multi-factor precision medicine (PM) is warranted. We systematically developed a system dynamics model (SDM) of AD for PM using data from two longitudinal studies (N=3660). This method involved a model selection procedure in identifying interaction terms between the SDM components and estimating individualized parameters. We used the SDM to explore simulated single- and double-factor interventions on 14 modifiable risk factors. We quantified the potential impact of double-factor interventions over single-factor interventions as 1.5 [95% CI: 1.5-2.6] and of SDM-based PM over a one-size-fits-all approach as 3.5 [3.1, 3.8] ADAS-cog-13 points in 12 years. Although the model remains to be validated, we tentatively conclude that multi-factor PM could come to play an important role in AD prevention.

Understanding the dynamics emerging from the interplay among poor mental wellbeing, energy balance-related behaviors, and obesity prevalence in adolescents: A simulation-based study

Both obesity and poor mental wellbeing have a high prevalence in European youth. Adolescents in six countries identified mental wellbeing factors as main drivers of youth obesity through systems mapping. This study sought to (1) explore the dynamics of the interplay between poor mental wellbeing, energy balance-related behaviors, and adolescent overweight and obesity prevalence and (2) test the effect of intervention point scenarios to reduce adolescent obesity. Drawing on the youth-generated systems maps and a literature synthesis, we built a simulation model that represents the links from major feedback pathways for poor mental wellbeing to changes in dietary, physical activity, and sleep behaviors. The model was calibrated using survey data from Norway, expert input, and literature and shows a good fit between simulated behavior and available statistical data. The simulations indicate that adolescent mental wellbeing is harmed by socio-cultural pressures and stressors, which trigger reinforcing feedback mechanisms related to emotional/binge eating, lack of motivation to engage in physical activity, and sleep difficulty. Targeting a combination of intervention points that support a 25% reduction of pressure on body image and psychosocial stress showed potentially favorable effects on mental wellbeing-doubling on average for boys and girls and decreasing obesity prevalence by over 4%.

Simulation Models for Suicide Prevention: A Survey of the State-of-the-Art

Suicide is a leading cause of death and a global public health problem, representing more than one in every 100 deaths in 2019. Modeling and Simulation (M&S) is widely used to address public health problems, and numerous simulation models have investigated the complex, dependent, and dynamic risk factors contributing to suicide. However, no review has been dedicated to these models, which prevents modelers from effectively learning from each other and raises the risk of redundant efforts. To guide the development of future models, in this paper we perform the first scoping review of simulation models for suicide prevention. Examining ten articles, we focus on three practical questions. First, which interventions are supported by previous models? We found that four groups of models collectively support 53 interventions. We examined these interventions through the lens of global recommendations for suicide prevention, highlighting future areas for model development. Second, what are the obstacles preventing model application? We noted the absence of cost effectiveness in all models reviewed, meaning that certain simulated interventions may be infeasible. Moreover, we found that most models do not account for different effects of suicide prevention interventions across demographic groups. Third, how much confidence can we place in the models? We evaluated models according to four best practices for simulation, leading to nuanced findings that, despite their current limitations, the current simulation models are powerful tools for understanding the complexity of suicide and evaluating suicide prevention interventions.

Repetitive Negative Thinking as a Central Node Between Psychopathological Domains: a Network Analysis

Repetitive negative thinking (RNT) may be defined as a reiterative, passive and uncontrollable thinking process. RNT has been recognized as a transdiagnostic phenomenon associated with the onset and maintenance of several clinical conditions including depression, generalised anxiety, psychosis and insomnia. We aimed to estimate a network model of mutual associations between RNT and the aforementioned indicators whilst controlling for other well-established transdiagnostic factors (i.e. perceived stress, loneliness). A total of 324 participants (Mage = 25.26 years, SD = 6.89; 69.3% females) completed a cross-sectional survey of self-report questionnaires. A Gaussian graphical model was estimated using the graphical LASSO in combination with the extended Bayesian information criterion. We found a dense network in which RNT exhibited substantial connections with the majority of the psychopathological domains. The centrality indices confirmed that RNT was one of the most important nodes in the network. Moreover, the estimated network showed satisfactory accuracy and stability. Findings emphasized RNT as a potentially good therapeutic target for psychopathology prevention and treatment protocols.

Trajectories of nonsuicidal self‐injury during adolescence

OBJECTIVE

Although nonsuicidal self-injury is a public health concern, there is little information on how it changes across adolescence or what contributes to stability or change. We aimed to identify trajectories of stability and change in self-injury from ages 13 to 17 years, and to identify interpersonal and intrapersonal correlates that differentiate between trajectories of stability and change.

METHOD

We used five annual waves of cohort-sequential data, targeting 7th and 8th graders attending all public schools in three municipalities in central Sweden. The data were gathered via questionnaires, using a multi-item measure of non-suicidal self-injury and assessing negative experiences at home, in school, with peers, and in romantic settings, as well as intrapersonal issues (internalizing symptoms and difficulties with emotional, and behavioral regulation). The analytic sample was 3195 adolescents (51.7% boys, 48.3% girls; ages 12-16 years at T1, M = 13.61; SD = 0.66), most of whom were born in Sweden (88.6%) to at least one parent of Swedish origin (77.4%).

RESULTS

Latent growth curve modeling revealed three self-injury trajectories: a stable-low, a low-increasing, and an increasing-decreasing trajectory. Adolescents in the stable-low class reported the best overall adjustment at ages 13 and 16. Comparatively, adolescents in the other two classes reported similar levels of difficulty interpersonally and intrapersonally. Where they differed, the increase-decrease class fared worse than the low-increasing class.

CONCLUSIONS

This study suggests the need to frame self-injury as having multiple directions of development during adolescence and develop theory that aligns with differential patterns of self-injury development.

Exploring personalized psychotherapy for depression: A system dynamics approach

Depressive disorders are the leading contributor to medical disability, yet only 22% of depressed patients receive adequate treatment in a given year. Response to treatment varies widely among individuals with depression, and poor response to one treatment does not signal poor response to others. In fact, half of patients who do not recover from a first-line psychotherapy will recover from a second option. Attempts to personalize psychotherapy to patient characteristics have produced better outcomes than usual care, but research on personalized psychotherapy is still in its infancy. The present study explores a new method for personalizing psychotherapy for depression through simulation modeling. In this study, we developed a system dynamics simulation model of depression based on one of the major mechanisms of depression in the literature and investigated the trend of depressive symptoms under different conditions and treatments. Our simulation outputs show the importance of individualized services with appropriate timing, and reveal a new method for personalizing psychotherapy to heterogeneous individuals. Future research is needed to expand the model to include additional mechanisms of depression.

Tools for Supporting the MCH Workforce in Addressing Complex Challenges: A Scoping Review of System Dynamics Modeling in Maternal and Child Health

OBJECTIVES

System Dynamics (SD) is a promising decision support modeling approach for growing shared understanding of complex maternal and child health (MCH) trends. We sought to inventory published applications of SD to MCH topics and introduce the MCH workforce to these approaches through examples to support further iteration and use.

METHODS

We conducted a systematic search (1958-2018) for applications of SD to MCH topics and characterized identified articles, following PRISMA guidelines. Pairs of experts abstracted information on SD approach and MCH relevance.

RESULTS

We identified 101 articles describing applications of SD to MCH topics.

APPROACH

27 articles present qualitative diagrams, 10 introduce concept models that begin to quantify dynamics, and 67 present more fully tested/analyzed models.

PURPOSE

The most common purposes described were to increase understanding (n = 55) and support strategic planning (n = 26). While the majority of studies (n = 53) did not involve stakeholders, 40 included what we considered to be a high level of stakeholder engagement - a strength of SD for MCH.

TOPICS

The two Healthy People 2020 topics addressed most frequently were early and middle childhood (n = 30) and access to health services (n = 26). The most commonly addressed SDG goals were "End disease epidemics" (n = 26) and "End preventable deaths" (n = 26).

CONCLUSIONS FOR PRACTICE

While several excellent examples of the application of SD in MCH were found, SD is still underutilized in MCH. Because SD is particularly well-suited to studying and addressing complex challenges with stakeholders, its expanded use by the MCH workforce could inform an understanding of contemporary MCH challenges.

Persistence of Anxiety/Depression Symptoms in Early Adolescence: A Prospective Study of Daily Life Stress, Rumination, and Daytime Sleepiness in a Genetically Informative Cohort

In this prospective study of mental health, we examine the influence of three interrelated traits - perceived stress, rumination, and daytime sleepiness - and their association with symptoms of anxiety and depression in early adolescence. Given the known associations between these traits, an important objective is to determine the extent to which they may independently predict anxiety/depression symptoms. Twin pairs from the Queensland Twin Adolescent Brain (QTAB) project were assessed on two occasions (N = 211 pairs aged 9-14 years at baseline and 152 pairs aged 10-16 years at follow-up). Linear regression models and quantitative genetic modeling were used to analyze the data. Prospectively, perceived stress, rumination, and daytime sleepiness accounted for 8-11% of the variation in later anxiety/depression; familial influences contributed strongly to these associations. However, only perceived stress significantly predicted change in anxiety/depression, accounting for 3% of variance at follow-up after adjusting for anxiety/depression at baseline, although it did not do so independently of rumination and daytime sleepiness. Bidirectional effects were found between all traits over time. These findings suggest an underlying architecture that is shared, to some degree, by all traits, while the literature points to hypothalamic-pituitary-adrenal (HPA) axis and/or circadian systems as potential sources of overlapping influence and possible avenues for intervention.

Bidirectional associations between nightly sleep and daily happiness and negative mood in adolescents

This study examined bidirectional associations between daily happiness and negative mood and subjective and objective sleep measures. Participants were 311 adolescents (M_age = 17.37 years; 51.8% female; 59.2% White/European American, 38.6% Black/African American, 1% Hispanic/Latinx American, 1.4% multi‐racial; 19.3% below poverty line) observed over a 7‐day period (2017–2018) using sleep diaries and actigraphy. Daily negative mood was related to greater subjective sleep/wake problems, and happiness was related to lower subjective sleep/wake problems. Conversely, shorter self‐reported sleep duration was related to higher negative mood the next day. For actigraphy measures, daily negative mood was related to greater sleep duration and efficiency, whereas happiness was related to lower sleep efficiency. Differences in associations based on subjective versus objective sleep measures are discussed.

Defining and Intervening on Cumulative Environmental Neurodevelopmental Risks: Introducing a Complex Systems Approach

BACKGROUND

The combined effects of multiple environmental toxicants and social stressor exposures are widely recognized as important public health problems contributing to health inequities. However cumulative environmental health risks and impacts have received little attention from U.S. policy makers at state and federal levels to develop comprehensive strategies to reduce these exposures, mitigate cumulative risks, and prevent harm. An area for which the inherent limitations of current approaches to cumulative environmental health risks are well illustrated is children's neurodevelopment, which exhibits dynamic complexity of multiple interdependent and causally linked factors and intergenerational effects.

OBJECTIVES

We delineate how a complex systems approach, specifically system dynamics, can address shortcomings in environmental health risk assessment regarding exposures to multiple chemical and nonchemical stressors and reshape associated public policies.

DISCUSSION

Systems modeling assists in the goal of solving problems by improving the "mental models" we use to make decisions, including regulatory and policy decisions. In the context of disparities in children's cumulative exposure to neurodevelopmental stressors, we describe potential policy insights about the structure and behavior of the system and the types of system dynamics modeling that would be appropriate, from visual depiction (i.e., informal maps) to formal quantitative simulation models. A systems dynamics framework provides not only a language but also a set of methodological tools that can more easily operationalize existing multidisciplinary scientific evidence and conceptual frameworks on cumulative risks. Thus, we can arrive at more accurate diagnostic tools for children's' environmental health inequities that take into consideration the broader social and economic environment in which children live, grow, play, and learn. https://doi.org/10.1289/EHP7333.

A System Dynamics Simulation Applied to Healthcare: A Systematic Review

In recent years, there has been significant interest in developing system dynamics simulation models to analyze complex healthcare problems. However, there is a lack of studies seeking to summarize the available papers in healthcare and present evidence on the effectiveness of system dynamics simulation in this area. The present paper draws on a systematic selection of published literature from 2000 to 2019, in order to form a comprehensive view of current applications of system dynamics methodology that address complex healthcare issues. The results indicate that the application of system dynamics has attracted significant attention from healthcare researchers since 2013. To date, articles on system dynamics have focused on a variety of healthcare topics. The most popular research areas among the reviewed papers included the topics of patient flow, obesity, workforce demand, and HIV/AIDS. Finally, the quality of the included papers was assessed based on a proposed ranking system, and ways to improve the system dynamics models' quality were discussed.

A complex systems approach to the study of change in psychotherapy

BACKGROUND

A growing body of research highlights the limitations of traditional methods for studying the process of change in psychotherapy. The science of complex systems offers a useful paradigm for studying patterns of psychopathology and the development of more functional patterns in psychotherapy. Some basic principles of change are presented from subdisciplines of complexity science that are particularly relevant to psychotherapy: dynamical systems theory, synergetics, and network theory. Two early warning signs of system transition that have been identified across sciences (critical fluctuations and critical slowing) are also described. The network destabilization and transition (NDT) model of therapeutic change is presented as a conceptual framework to import these principles to psychotherapy research and to suggest future research directions.

DISCUSSION

A complex systems approach has a number of implications for psychotherapy research. We describe important design considerations, targets for research, and analytic tools that can be used to conduct this type of research.

CONCLUSIONS

A complex systems approach to psychotherapy research is both viable and necessary to more fully capture the dynamics of human change processes. Research to date suggests that the process of change in psychotherapy can be nonlinear and that periods of increased variability and critical slowing might be early warning signals of transition in psychotherapy, as they are in other systems in nature. Psychotherapy research has been limited by small samples and infrequent assessment, but ambulatory and electronic methods now allow researchers to more fully realize the potential of concepts and methods from complexity science.

The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research

The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.

Dynamics of intervention adoption, implementation, and maintenance inside organizations: The case of an obesity prevention initiative

Overall impact of public health prevention interventions relies not only on the average efficacy of an intervention, but also on the successful adoption, implementation, and maintenance (AIM) of that intervention. In this study, we aim to understand the dynamics that regulate AIM of organizational level intervention programs. We focus on two well-documented obesity prevention interventions, implemented in food carry-outs and stores in low-income urban areas of Baltimore, Maryland, which aimed to improve dietary behaviour for adults by providing access to healthier foods and point-of-purchase promotions. Building on data from field observations, in-depth interviews, and data discussed in previous publications, as well as the strategy and organizational behaviour literature, we developed a system dynamics model of the key processes of AIM. With simulation analysis, we show several reinforcing mechanisms that span stakeholder motivation, communications, and implementation quality and costs can turn small changes in the process of AIM into big difference in the overall impact of the intervention. Specifically, small changes in the allocation of resources to communication with stakeholders of intervention could have a nonlinear long-term impact if those additional resources can turn stakeholders into allies of the intervention, reducing the erosion rates and enhancing sustainability. We present how the dynamics surrounding communication, motivation, and erosion can create significant heterogeneity in the overall impact of otherwise similar interventions. Therefore, careful monitoring of how those dynamics unfold, and timely adjustments to keep the intervention on track are critical for successful implementation and maintenance.