Summary: Researchers have clarified the difference between feeling lonely and actually being alone, showing when and how solitude translates into loneliness—especially for older adults.
The study found that loneliness becomes likely when people spend more than 75% of their time alone. While most adults spend a large portion of their day alone without feeling lonely, older adults show a stronger link between solitude and loneliness. To measure real-world social behavior more accurately, researchers are developing SocialBit, a smartwatch app that tracks conversational minutes much like a fitness tracker counts steps.
Key Facts:
- Loneliness tends to become pronounced when individuals spend over 75% of their time in solitude.
- For adults older than about 67, there is a notably stronger relationship between time spent alone and reported loneliness, with roughly a 25% overlap in this group.
- The Electronically Activated Recorder (EAR) app captured daily social behavior in this research. A new tool, SocialBit, is being developed for smartwatches to measure social activity by tracking conversation minutes per day.
Source: University of Arizona
Background
In an era of constant connectivity, the difference between being alone and feeling lonely can be subtle. University of Arizona researchers analyzed decades of observational data to separate objective social isolation—actual time spent alone—from subjective loneliness, the emotional experience of feeling isolated.
Published in the Journal of Research in Personality, the study found that across participants the average proportion of time spent alone was 66%. People who spent more than 75% of their time alone reported the highest levels of loneliness. When the researchers compared objective and subjective measures across the full sample, aloneness and loneliness overlapped by only about 3%—indicating that for most people, solitude and loneliness are distinct.
However, that distinction narrowed among older adults. For participants aged 68 and older, the overlap between time spent alone and reported loneliness rose to around 25%, suggesting that social isolation and loneliness are closely linked in later life.
The project was led by Alex Danvers and Liliane Efinger, with senior authors David Sbarra and Matthias Mehl from the University of Arizona. Sbarra noted that social networks often shrink with age and that opportunities for social interaction frequently decline, increasing the risk that solitude becomes loneliness for older people.
“We are learning more about how social connections affect health, and it appears that loneliness and isolation are related but distinct,” Sbarra said. The 2023 U.S. Surgeon General’s advisory on loneliness has further highlighted the importance of understanding these relationships for public health.
Methods: EAR and the development of SocialBit
To measure everyday social behavior, the researchers relied on a method developed over many years by Matthias Mehl. The Electronically Activated Recorder (EAR) is a smartphone app that, with participants’ consent, records 30-second sound snippets every 12 minutes. These audio samples let researchers classify whether someone is alone, talking on the phone, watching TV, driving, or interacting with another person.
EAR provides rich, objective information about daily social life but requires substantial manual coding of audio files. To scale measurement and make it more practical for clinical settings, Mehl and colleagues are building SocialBit, a smartwatch app designed to detect and quantify minutes of conversation each day. Like fitness trackers that count steps, SocialBit aims to produce a simple, actionable metric of social activity.
The team plans to pilot SocialBit within clinical populations where social isolation is common, such as stroke survivors during recovery. By offering timely feedback—“you’ve been solitary for too long”—the device could encourage people to reconnect and help clinicians monitor social engagement as part of recovery and prevention strategies.
Findings and implications
Key findings from the pooled archival data (over 400 participants collected across studies spanning roughly two decades) include:
- Most adults spend substantial parts of their day alone without reporting loneliness.
- When alone time exceeds about 75% of waking hours, the likelihood of experiencing loneliness rises sharply.
- Older adults show a stronger association between solitude and loneliness, suggesting interventions to increase social contact may be especially important in later life.
These results underscore the need for precise, scalable measures of social behavior. Accurate measurement can inform interventions and public health policies aimed at reducing loneliness—a factor increasingly recognized as important for mental and physical health.
About this social neuroscience and loneliness research news
Author: Niranjana Sahasranamam Rajalakshmi
Source: University of Arizona
Contact: Niranjana Sahasranamam Rajalakshmi – University of Arizona
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Loneliness and time alone in everyday life: A descriptive-exploratory study of subjective and objective social isolation” by David Sbarra et al. Journal of Research in Personality
Abstract
Loneliness and time alone in everyday life: A descriptive-exploratory study of subjective and objective social isolation
Social relationships and affiliation exert major influences on physical and mental health, yet terminology in this field—social networks, social ties, social integration—is often used inconsistently. This paper clarifies these concepts within a unified framework, outlines major assessment tools, and proposes an integrative model linking macro-social context to psychobiological processes.
Drawing on foundational theories from Durkheim, Bowlby, and contemporary network science, the authors present a cascading model in which upstream social and cultural forces shape network structure. Network structure and function then influence behavior through four primary pathways: provision of social support, social influence, social engagement and attachment, and access to resources and goods. The paper argues for greater attention to the broader social context when studying how networks affect health.