Editorial: Impact of apathy on aging and age-related neuropsychiatric disorders
Bibliographic record
Abstract
In this special issue focusing on the impact of apathy in older adults with neuropsychiatric disorders, we invited colleagues from around the world to share their perspectives on this understudied and under-reported syndrome. We got contributions from several countries around the world and in different areas of work. Manera et al from Université Côte d'Azur, CobTeK, Nice, France, published an application to assess apathy as a novel alternative to the clinical rating scale and showed that in their cohort of 227 older adults with mild and major neurocognitive disorders, the "interest game" has the ability to detect significant apathy with a sensitivity and specificity of 0.68 and 0.65, respectively. Innovative ways to assess apathy are critically needed to get to the core symptom of diminished interest and work of this sort is an important step in this direction. Yan et al from several universities in China conducted a thorough meta-analysis of structural neuroimaging studies in apathy across healthy and brain disorders including neurodegenerative illnesses and traumatic brain injury. They identified several brain areas that are likely involved in the mechanism of apathy. This work will likely pave the way for more work to further elucidate the basic brain mechanism of apathy and potential therapeutic targets for interventions including therapeutic brain stimulation. Indeed, the paper by Espiritu et al, with contributions from the Philippines, Japan, and Canada, presented a systematic review of the potential therapeutic benefit of repetitive transcranial magnetic stimulation in apathy across different brain disorders that are common in old age. The paper reports limited evidence but potential benefits of rTMS in Alzheimer disease, primary progressive aphasia, mild cognitive impairment, and chronic stroke. More work is being done to confirm the role of brain stimulation for apathy in neurocognitive and other brain disorders and hopefully will be reported in the near future. While there was no contribution to this special edition on the role of pharmacological interventions in apathy, some work has been published elsewhere on that topic and showed promise from several pharmacological agents as monotherapy or in combination like acetylcholine esterase inhibitors and methylphenidate, a stimulant (7) Apathy is a final common pathway of different pathologies that affect the cognitive-motivational networks in the brain. Like many illness manifestations, apathy is the product of the abnormal balance between cognitive-motivational resources, and demands of internal and external factors. Cognitive-motivational network involvement has been found to be the common underlying mechanism of many brain disorders manifesting as apathy (8). Like any other illness manifestation, it is not "all or none" but rather a spectrum of severity that is considered "illness" when the level of impairment significantly impacts the quality of life and/or function. It is important, on the other hand, to consider processes that contribute to this impairment. These factors can be external factors, like lack of opportunity to participate due to physical disability or limited support, or internal factors like competing brain network activation such as negative emotional or pain networks. The paper by Zhong et al from Chengdu University in China while didn't specifically focus on apathy, it highlighted the link between depression, which is commonly co-morbid with apathy, and sarcopenia, the hallmark of frailty in older adults. The authors utilized large cohort data and performed a Mendelian randomization methodology demonstrating a causal connection between depression and sarcopenia. This work contributes to our understanding of genetic and environmental factors that can affect the ability of older adults to engage in activities and is essential to consider when assessing and providing holistic treatment to older adults.Figure 1 outlines a model of what could be operating in the process from wanting to do something new, plan/prepare, initiate, persist in doing, getting a reward, and then wanting to do it again due to the positive reinforcement from the rewarding experience.This research topic issue is a step towards understanding the impact of apathy on the aging population worldwide, much more work is needed and we look forward to seeing more being published on the results of current and future studies including studies that improve measurements and leverage technology and data modeling (including deep learning and consumer devices), better define therapeutic targets based on better understanding of underlying brain mechanisms, and combine different interventions to address the complexity of factors that contribute to this syndrome.Figure 1: the cycle of motivation-reinforcement is depicted whereby the motivation to start an activity leads to preparation and planning, initiation, persistent in the activity, feel the reward, which ultimately result in positive reinforcement to do the activity or other activities again.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".