Understanding the complexity of individual developmental pathways: A primer on metaphors, models, and methods to study resilience in development

Temporal Dynamics of Depressive Symptoms, Apathy, Daily Activities, and Cognitive Decline in Older People From the General Population: A Network Analysis

BACKGROUND

The prevalence of depressive symptoms, apathy, and cognitive decline increases with age. Understanding the temporal dynamics of these symptoms could provide valuable insights into the early stages of cognitive decline, allowing for more timely and effective treatment and management.

METHODS

Participants from the Prevention of Dementia by Intensive Vascular Care (preDIVA) trial cohort with baseline and ≥3 follow-up measurements were included, with a median of 7.8 (0.68) years of follow-up. Dynamic Time Warping (DTW) analysis was used to model temporal dynamics of cognition using the Mini Mental State Exam (MMSE), activities of daily living (ADL) using the Amsterdam Linear Disability Scale (ALDS), and apathy and depressive symptoms using the 15-item Geriatric Depression Scale (GDS-15) at the individual and group level.

RESULTS

The 1,537 participants were aged 74 (2.0) years at baseline, 56.5% were female, and 19.9% had finished higher education. A decline in ADL and increase in apathy tended to precede most indicators of cognitive decline, with all apathy items (i.e. being 'dropped activities/interests', 'not feeling energetic' and 'not doing new things') and ADL showing significant outstrength (all p's < 0.001). Many mood-related symptoms other than apathy, and the MMSE items 'immediate memory', 'verbal comprehension' and 'naming objects' tended to be the last to deteriorate, showing significant instrength (all p's < 0.001).

CONCLUSION

An increase apathy and a decline in ADL tended to precede mood-related symptoms and cognitive impairment in older adults from the general population. These changes may thus serve as potential early warning signs of both depression and dementia, and may allow for timely intervention.

Emergence and evolution of developmental resilience science over half a century

This reflection on the history and future of developmental resilience science (DRS) highlights its co-emergence with developmental psychopathology (DP), as well as the roles of this journal and its founding editor, Dante Cicchetti, in the evolution of these intertwined domains of scholarship. A remarkable constellation of scholars at the University of Minnesota shaped the course of both conceptual frameworks and their dissemination. I describe fundamental assumptions common to DP and DRS frameworks that reflect their common roots and the pervasive influence of systems theory on developmental science. I describe four waves of DRS and key principles of DRS at the present time. In conclusion, I consider the possibility that a fifth wave of DRS is emerging with a focus on understanding patterns of multisystem, multilevel processes of resilience and their implications for interventions in the context of interacting, interdependent, and complex adaptive systems. I close this commentary with questions for future research and a hopeful outlook on the future of human resilience.

Re-politicizing the WHO's social determinants of health framework

Although the World Health Organization's (WHO's) framework on social and structural determinants of health and health inequities (SSDHHI) has done much to raise awareness of these determinants, it does not go far enough in considerations of politics and power. The framework has become more de-politicized since its publication, with the definition of social determinants shifting toward downstream and individualized factors. In the meantime, new research fields on legal, commercial and political determinants of health and health inequities have emerged; however, these have not become integrated adequately into broader SSDHHI frameworks. To address these challenges, we argue for a re-politicization and an expansion of the WHO's framework by including the agents who have power over shaping structural determinants and the ways they use power to shape these determinants. We also provide a more detailed conceptualization of structural determinants to facilitate research. We propose a guideline for evaluating studies according to the extent to which they point upstream versus downstream and incorporate agents and considerations of power. We then use this framework to encourage more research on associations among agents, mechanisms of power, and structural determinants; how changes in structural determinants affect power dynamics among agents; and a wider focus on structural determinants beyond laws and policies, such as broad economic and sociopolitical systems. We also urge researchers to consider societal and institutional forces shaping their research with respect to SSDHHI. Research based on this framework can be used to provide evidence for advocacy for structural changes and to build more just systems that respect the fundamental human right to a healthy life.

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.

Risk and resilience models in child development

This chapter provides the most comprehensive review of risk and resilience models for child development thus far, synthesizing these interdisciplinary frameworks for ease of use in research and practice. This review specifically focuses on process models with broader conceptualizations of risk and resilience that have effects across multiple developmental domains. Risk and resilience models alike agree that alleviating risk factors is beneficial for children's development, including risks ranging from proximal issues with households (e.g., instability) and caregivers (e.g., insecure attachment, abuse) to relatively distal influences like structural racism and socioeconomic status. Resilience models further add that children who experience risks are not inherently doomed to poorer outcomes, but can draw upon positive factors in development to combat negative effects from risk, which cannot always be avoided. Major positive factors include loving relationships, educational resources, and cultural assets. Risk and resilience are highly multidisciplinary fields that have contributed much to our understanding of human development, with ample room for continued growth. Understanding of risk and resilience processes, especially during sensitive developmental periods like early childhood, provides valuable insight for prevention and intervention research and practices. Risk and resilience models share an interest in deciphering the developmental processes that hinder and help children across domains so that kids can live their best lives, resulting in a better off society for all.

Temporal dynamics of depressive symptoms and cognitive decline in the oldest old: dynamic time warp analysis of the Leiden 85-plus study

BACKGROUND

The prevalence of depressive symptoms and cognitive decline increases with age. We investigated their temporal dynamics in individuals aged 85 and older across a 5-year follow-up period.

METHODS

Participants were selected from the Leiden 85-plus study and were eligible if at least three follow-up measurements were available (325 of 599 participants). Depressive symptoms were assessed at baseline and at yearly assessments during a follow-up period of up to 5 years, using the 15-item Geriatric Depression Scale (GDS-15). Cognitive decline was measured through various tests, including the Mini Mental State Exam, Stroop test, Letter Digit Coding test and immediate and delayed recall. A novel method, dynamic time warping analysis, was employed to model their temporal dynamics within individuals, in undirected and directed time-lag analyses, to ascertain whether depressive symptoms precede cognitive decline in group-level aggregated results or vice versa.

RESULTS

The 325 participants were all 85 years of age at baseline; 68% were female, and 45% received intermediate to higher education. Depressive symptoms and cognitive functioning significantly covaried in time, and directed analyses showed that depressive symptoms preceded most of the constituents of cognitive impairment in the oldest old. Of the GDS-15 symptoms, those with the strongest outstrength, indicating changes in these symptoms preceded subsequent changes in other symptoms, were worthlessness, hopelessness, low happiness, dropping activities/interests, and low satisfaction with life (all P's < 0.01).

CONCLUSION

Depressive symptoms preceded cognitive impairment in a population based sample of the oldest old.

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.