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Background: Detecting early signs of Alzheimer’s disease (AD) and mild cognitive impairment (MCI) during the pre-symptomatic phase is becoming increasingly important for costeffective clinical trials and also for deriving maximum benefit from currently available treatment strategies. However, distinguishing early signs of MCI from normal cognitive aging is difficult. Biomarkers have been extensively examined as early indicators of the pathological process for AD, but assessing these biomarkers is expensive and challenging to apply widely among pre-symptomatic community dwelling older adults. Here we propose assessment of social markers, which could provide an alternative or complementary and ecologically valid strategy for identifying the pre-symptomatic phase leading to MCI and AD. Methods: The data came from a larger randomized controlled clinical trial (RCT), where we examined whether daily conversational interactions using remote video telecommunications software could improve cognitive functions of older adult participants. We assessed the proportion of words generated by participants out of total words produced by both participants and staff interviewers using transcribed conversations during the intervention trial as an indicator of how two people (participants and interviewers) interact with each other in one-on-one conversations. We examined whether the proportion differed between those with intact cognition and MCI, using first, generalized estimating equations with the proportion as outcome, and second, logistic regression models with cognitive status as outcome in order to estimate the area under ROC curve (ROC AUC). Results: Compared to those with normal cognitive function, MCI participants generated a greater proportion of words out of the total number of words during the timed conversation sessions (p=0.01). This difference remained after controlling for participant age, gender, interviewer and time of assessment (p=0.03). The logistic regression models showed the ROC AUC of identifying MCI (vs. normals) was 0.71 (95% Confidence Interval: 0.54 – 0.89) when average proportion of word counts spoken by subjects was included univariately into the model. Conclusion: An ecologically valid social marker such as the proportion of spoken words produced during spontaneous conversations may be sensitive to transitions from normal cognition to MCI.

Increasing social interaction could be a promising intervention for improving cognitive function. We examined the feasibility of a randomized controlled trial to assess whether conversation-based cognitive stimulation through personal computers, webcams, and a user-friendly interactive Internet interface had high adherence and a positive effect on cognitive function among older adults without dementia.

Recent findings indicate interventions can boost executive functions—mental processes that have long been thought to be static and not open to change. The authors examined whether and how short-term social interactions could create such cognitive benefits. Study 1 found that basic get-to-know-you interactions (with or without an explicit cooperative goal) boosted executive function relative to controls and as much as nonsocial intellective activities. In contrast, interactions involving a competitive goal resulted in no boosts. Studies 2 and 3 tested a proposed mechanism for the results—that people need to engage with others and take their perspective to realize cognitive boosts. The findings show that competitive interactions, if structured to allow for interpersonal engagement, can boost executive functions. The results highlight how social functioning can enhance core mental capacities.

Psychological research has devoted much attention to how people judge and predict others. However, a full understanding of social perception necessitates incorporating the responses of the targets, who may have little interest in being predicted. The authors argue that whether people want to be predicted depends on the interpersonal context—in particular, competitive or cooperative ones. Study 1 used a unique behavioral measure and showed that competition participants, when asked to draw the flight path of a moth in a separate study, produced significantly more variable and significantly less predictable trajectories than did cooperation participants. Study 2 examined participants' self-assessments and showed that participants expecting a competitive interaction indicated that they were more difficult to predict, less willing to open up, and more willing to mislead. Together, the findings suggest that people are not always open to being predicted and that the form of these tendencies depends on features of the situation.