Ecological Factors Influencing Decision-Making Among Middle-Aged and Older Adults: A Neurocognitive Approach

Area of Science:

• Gerontology
• Neuroscience
• Sociology

Background:

• Decision-making capacity (DMC) is crucial for autonomy in middle-aged and older adults.
• Research on cognitive factors influencing DMC is extensive, but ecological factors, especially in non-Western settings, are understudied.
• This study investigates ecological influences on decision-making competence in older adults in Pakistan.

Purpose of the Study:

• To assess the impact of social environment, emotional states, and stress on decision-making competence in older adults in Pakistan.
• To explore cultural variations in decision-making capacity by examining ecological factors.
• To apply a neurocognitive approach to understand decision-making in a diverse population.

Main Methods:

• A quantitative, cross-sectional study involving 100 adults aged ≥45 years in Rawalpindi and Islamabad.
• Participants completed questionnaires on demographics, Adult Decision-Making Competence (A-DMC), life satisfaction, depression, and ecological/cognitive factors.
• Data analysis included descriptive statistics, correlations, t-tests, ANOVA, and regression using IBM SPSS.

Main Results:

• Marital status and living arrangements significantly affected social environment perceptions, stress, and cognitive engagement (p < 0.05).
• Married individuals and those living with family reported better social environments, lower stress, and higher well-being.
• Ecological factors showed minimal predictive value for decision-making competence (R²=0.014, p=0.711), with older age groups scoring lower.

Conclusions:

• Marital status and living arrangements play significant roles in psychological well-being, social interactions, and stress among middle-aged and older adults.
• Decision-making competence appears resilient to direct ecological influences, possibly due to accumulated life experience.
• Future research should utilize longitudinal designs and larger, diverse samples for enhanced understanding and generalizability.