When we fall prey to perfectionism, we think we’re honorably aspiring to be our very best, but often we’re really just setting ourselves up for failure, as perfection is impossible and its pursuit inevitably backfires. 
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Updated December 24, 2024 Reviewed by Abigail Fagan
With the global population aging, and rising concerns about mental health, loneliness, and social isolation, understanding and enhancing later-life satisfaction has become increasingly crucial for both individual and global health and productivity. The World Health Organization1 reports that by 2030, one out of six people will be 60 years or older, comprising 1.4 billion people, with those over 80 approaching half a billion.
Given the vast scope of this issue, it’s surprising that we have a limited understanding of what preserves and enhances generativity in our later years, as research to date is still early-on. Along similar lines, increased generativity would be expected to enhance well-being, and protect against many of the negative outcomes currently associated with aging. With the global population getting older and the average human lifespan increasing, it is imperative to work out how to extend healthspan and productivity, meaning, purpose and community.
A recent study by Mohsen Joshanloo, Ph.D., published in the Journals of Gerontology (2024), took a novel approach using machine learning to extract key variables from the Midlife in the United States (MIDUS) dataset. This study included a wide range of psychological and demographic variables and measured generativity using the Loyola Generativity Scale. Participants ranged from 39 to 93 years old, with an average age of 63.64. Using maching learning allows us to make sense out of complicated data sets where standard statistical approaches may falter.
From a broad perspective, a few key concepts help us understand aging across the lifespan. These include Erik Erikson’s developmental model, especially Middle and Older Adulthood (below); the balance of stability and plasticity (contributing to consistency and change); and the two major forms of well-being—eudaimonic (meaning) and hedonic (pleasure), which need to be in harmony. Personality traits, measured by the Big Five (Five Factor Model, or FFM), play a role in this process, with some contributing to stability or plasticity. For example, openness to experience is linked with plasticity, while neuroticism, because of an anxious reluctance to take risks, is often associated with stability.
The study used a “Random Forest Analysis” machine learning technique. This method builds multiple decision trees to sift through large datasets, identifying non-linear relationships and dynamic interactions. The model was trained on a subset of data and then tested against the rest to minimize prediction error and enhance accuracy. It analyzed 34 variables for 2,830 participants, after removing those with missing data and reducing the original 70 variables to a set of non-redundant measures.
The final model predicted 40% of the variance in generativity, revealing five key factors as the strongest predictors, ranked by significance:
Additional important factors include a sense of purpose in life and self-acceptance, which highlight the importance of living a meaningful life (eudaimonia) and having a coherent life narrative. Generativity is influenced by how we view ourselves against the backdrop of our life story. Spiritual experiences also emerged as a relevant factor, pointing to the role of transcending quotidian concerns to see ourselves within a broader context.
Factors that were not significant in this model included demographic and health factors such as gender, health status, and socioeconomic variables. While these factors have been important predictors of well-being and life satisfaction in other studies, the machine learning analysis suggests they may not be the most crucial drivers of generativity, though they likely influence the key factors mentioned above. They may be necessary but not sufficient for generativity, perhaps accomplishments from earlier stages of life and provision of basic needs, providing stability and an all-important springboard for generativity into later life.
Because the dataset is cross-sectional, the results are correlational rather than causal. Future research using machine learning approaches such as Random Forest Analysis, and others, could look at longitudinal data sets to determine causality and further explore additional variables that may influence generativity. Hybrid intelligence, synergizing human and artificial minds to go beyond the capacity of either alone, holds promise for addressing knotty problems.
While the jury is still out, this study identifies important factors which, beyond their statistical significance, make a certain intuitive sense when contemplating how to flourish and increase generativity as we grow older. Rather than fading away, focusing on social factors including both leadership and belonging emerges as important. Cultivating mental flexibility and openness to experience are core. Stability is important, but in excess may lead to stagnation, and failure to take necessary risks.
Plasticity factors dovetail with personal growth orientation, flowing together into Erikson’s last two developmental tasks: Middle Adulthood Generativity vs. Stagnation, and Late Adulthood Integrity vs. Despair. It’s important to maintain ambition as part of the story, but not to an extreme, understand who we are and where we fit into a broader sense of purpose and meaning, and at the same time enjoy ourselves along the way.
References
1. World Health Organization (WHO) Ageing and Health
2. One Personality Trait Distinguishes Gifted People
Mohsen Joshanloo, Key Predictors of Generativity in Adulthood: A Machine Learning Analysis, The Journals of Gerontology: Series B, 2024;, gbae204, https://doi.org/10.1093/geronb/gbae204
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Grant Hilary Brenner, M.D., a psychiatrist and psychoanalyst, helps adults with mood and anxiety conditions, and works on many levels to help unleash their full capacities and live and love well.
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When we fall prey to perfectionism, we think we’re honorably aspiring to be our very best, but often we’re really just setting ourselves up for failure, as perfection is impossible and its pursuit inevitably backfires.
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