Two Pathways to Digital Flourishing: How Meaning and Positivity Orientations Shape Online Behavior and Well-Being

Abstract

As social media becomes increasingly embedded in daily life, understanding the psychological mechanisms that shape users’ digital experiences is essential for promoting healthy, sustainable digital behavior. This study examines two motivational life-orientation strategies—prioritizing meaning and prioritizing positivity—and investigates how they are differentially associated with patterns of social media use, digital flourishing, and psychological well-being. A sample of 414 adults completed validated measures of digital and psychological outcomes, including a Hebrew adaptation of the Digital Flourishing Scale (DFS), and measures of prioritizing meaning and prioritizing positivity. Across seven regression models, prioritizing meaning was consistently associated with more adaptive digital outcomes, including lower screen time, reduced FoMO, higher digital flourishing, greater self-compassion, and lower psychopathology. In contrast, prioritizing positivity was associated with greater social media engagement and elevated social comparison but showed no associations with digital flourishing or psychological well-being. These findings support a dual-pathway framework, suggesting that meaning-oriented individuals tend to interact with digital platforms more intentionally and resiliently, whereas positivity-oriented individuals engage in more affect-driven and evaluative patterns that do not translate into well-being benefits. The study advances current understanding of digital behavior by identifying motivational factors that shape how users navigate online environments and highlights implications for designing digital well-being interventions and platform features.

1. Introduction

Social media platforms have become central spaces in which individuals work, communicate, form impressions, and construct elements of identity. As these platforms increasingly shape daily routines, scholars have devoted considerable attention to understanding their impact on psychological functioning. This body of work reveals a complex pattern: social media use can support connection, self-expression, and access to valued relationships, yet it also exposes individuals to curated social comparison targets, evaluation pressures, information overload, and emotional volatility [1,2,3]. Because these diverse experiences occur in the same digital environments, researchers increasingly argue that individual differences—rather than platform features alone—play a central role in shaping whether digital experiences support or undermine well-being. Yet much of this literature remains descriptively focused (e.g., time spent, passive vs. active use), offering limited insight into why individuals gravitate toward particular digital practices and how they make sense of them. A motivational life-orientation lens may therefore help explain heterogeneity in digital outcomes beyond platform features or exposure alone.

Simultaneously, emerging perspectives suggest that well-being in digital environments should be understood not only as risk mitigation but also through positive, flourishing-oriented experiences. Janicke-Bowles et al. [4] presented digital flourishing as a multidimensional concept encompassing authenticity, relational depth, civic engagement, positive social comparison, and online self-control. This shift mirrors broader trends in positive psychology, which focus on conditions that enable individuals to thrive rather than just avoid distress. However, despite growing interest in digital flourishing, the mechanisms explaining why some people flourish online while others do not remain insufficiently understood, as existing research often examines discrete behaviors or isolated risk factors (e.g., FoMO, depression) rather than the motivational orientations that organize digital engagement. Conceptually, digital flourishing is not reducible to ‘less screen time’ or the absence of digital harm; it captures qualitatively positive and agentic ways of being online (e.g., authenticity, relational depth, and self-control), which may be shaped by the motivations people bring into digital environments. This perspective aligns with person–context models of media effects, which argue that the same digital affordances can lead to different outcomes depending on users’ dispositional motives and interpretive processes [5]. From this view, motivational orientations are expected to shape exposure (what people seek), reactivity (how they respond), and downstream well-being.

Against this backdrop, the present study addresses a key gap in the literature by examining how motivational life-orientation strategies may help explain heterogeneity in individuals’ engagement with social media and digitally mediated experiences. Rather than focusing on isolated digital behaviors or risk factors, the study adopts a motivational perspective to investigate why individuals interact with similar digital environments in qualitatively different ways. In doing so, it brings hedonic and eudaimonic considerations into closer dialogue with research on digital flourishing and information-rich social platforms, while integrating behavioral indicators, digital experiences, and psychological outcomes within a single preregistered framework.

Importantly, these motivational orientations can also be understood through the lens of information behavior in digital environments. Social media platforms are not merely social spaces but information-rich systems that continuously expose users to streams of socially relevant cues, evaluative information, and affordances for action. From an information behavior perspective, individual motivations shape how users select, attend to, interpret, and regulate their exposure to digital information. Consistent with person–context and differential susceptibility models, motivational orientations may operate as upstream motivational filters that organize engagement with digital information, influencing not only the quantity of social media use but also how individuals navigate information flows and respond to socially salient signals [3,5]. Framing life-orientation strategies as organizing influences on digital information behavior thus provides a conceptual bridge between positive psychology and research on mediated information environments, helping explain why similar digital affordances yield divergent experiential and well-being outcomes.

One promising theoretical lens is the distinction between hedonic and eudaimonic orientations—two overarching life-orientation strategies derived from decades of research in positive psychology. Hedonic orientations prioritize the pursuit of pleasure and the avoidance of discomfort, whereas eudaimonic orientations emphasize meaning, purpose, coherence, and personal growth [6,7,8]. These orientations shape how individuals select activities, interpret their experiences, and derive well-being from daily life. Although they have been studied extensively in offline contexts, surprisingly little is known about how they function in digital environments, where emotional, cognitive, and social processes are constantly activated. In digital spaces, hedonic motives may be expressed through affect-maximizing choices (e.g., seeking uplifting content, quick social rewards), whereas eudaimonic motives may be expressed through value-congruent participation (e.g., purposeful sharing, selective engagement, and regulated self-presentation).

Two constructs that operationalize these motivational orientations in daily decision-making are prioritizing positivity [9] and prioritizing meaning [10]. Both describe strategic tendencies for organizing life, but they differ fundamentally in what individuals seek. Prioritizing positivity reflects a hedonic strategy to maximize opportunities to experience positive affect. Prioritizing meaning reflects a eudaimonic strategy to align one’s daily behaviors with purpose, values, and significance. Although both strategies have been linked to differences in well-being offline, virtually no research has examined how they shape digital experiences, such as social media engagement, digital flourishing, or emotional vulnerabilities online. This gap is especially noticeable given that social media is now a major context in which individuals pursue emotion, connection, and meaning.

Below, we outline the theoretical foundations of each life-orientation strategy and develop an integrated framework for understanding how they may differentially influence digital behaviors, digital well-being, and psychological outcomes.

1.1. Prioritizing Positivity: A Hedonic Life Strategy in Emotionally Charged Digital Environments

Prioritizing positivity reflects a hedonic life strategy [9], which in the present study is examined specifically in terms of how it manifests within emotionally charged and socially evaluative digital environments. When embedded in daily life, this strategy has been linked to broadened attention and enhanced well-being (Fredrickson’s broaden-and-build framework [11]). However, a robust literature also points to a paradox: when individuals pursue positive affect too intentionally or monitor their emotions too closely, the pursuit itself can undermine well-being [12]. Individuals who strongly value happiness often become more self-evaluative, more sensitive to discrepancies between desired and actual emotional states, and more reactive in their emotional lives [13].

Social media platforms may amplify these dynamics. They provide immediate access to emotionally stimulating content, opportunities for social sharing, and visible markers of social approval, which may be attractive to positivity-oriented individuals. At the same time, platforms are saturated with upward comparison targets and curated positive portrayals of others’ lives [14]. For individuals already oriented toward affective maximization, these environments may heighten the desire for positive emotional cues, increase the likelihood of engaging in emotionally driven posting or commenting, and amplify comparison-based evaluative processes.

Importantly, positivity orientation does not inherently promote intentionality, self-regulation, authenticity, or value-congruence—core components of digital flourishing [4]. Nor does it reliably buffer against psychological distress; in some cases, strong positivity motives can exacerbate disappointment or emotional instability when positive affect is not achieved [12,15]. In digital contexts, the implications of a positivity-oriented strategy are therefore expected to manifest primarily through specific patterns of affective and interactive engagement. Thus, theory suggests that prioritizing positivity should be associated primarily with interactive and affective digital behaviors (e.g., posting, commenting, comparing), rather than with deeper flourishing or psychological resilience. Accordingly, we expect prioritizing positivity to be associated with greater behavioral engagement (i.e., more frequent interactive use), while remaining largely unrelated to flourishing-level qualities (e.g., authenticity, self-control) that require reflective self-regulation.

1.2. Prioritizing Meaning: A Eudaimonic Strategy Promoting Coherence, Purpose, and Regulation

Prioritizing meaning reflects a eudaimonic life-orientation strategy [10], which in the present study is examined in terms of how it shapes intentional, value-congruent engagement within digital environments. Meaning-oriented individuals tend to evaluate experiences in terms of coherence, purpose, and personal relevance—an orientation that has been linked to greater psychological stability, emotional regulation, and adaptive appraisal [16,17]. Such individuals often show resilience in the face of stress and a reduced reliance on external validation. They interpret challenging or emotionally complex experiences through a lens of significance and purpose that enables benefit even in the absence of immediate pleasure [18].

When applied to digital settings, meaning orientation is likely to foster selective and intentional forms of engagement. Individuals who prioritize meaning may avoid unstructured or habitual scrolling, engage less in socially evaluative monitoring, and gravitate toward digital interactions that are authentic or value aligned. This can reduce exposure to common digital vulnerabilities such as FoMO and social comparison. Importantly, this does not imply digital disengagement; rather, it reflects purposeful selectivity; engagement that is guided by personal relevance, relational depth, and value-consistency, which may translate into higher digital flourishing. Consistent with this view, the reflective and regulated qualities associated with meaning orientation map closely onto core components of digital flourishing, including authentic self-presentation, relational depth, civil engagement, and self-control [4].

Meaning orientation is also theoretically linked to greater self-compassion [16,19] and lower psychopathology, given that meaning is a foundational buffer against depression and anxiety [20,21]. Despite this strong theoretical rationale, empirical research directly examining how prioritizing meaning manifests in digital contexts remains scarce. To date, no studies have systematically examined whether prioritizing meaning is associated with digital flourishing, online emotional vulnerabilities, or psychopathology, representing a significant gap that the present study seeks to address.

1.3. A Dual-Orientation Framework for Understanding Digital Behavior and Well-Being

Taken together, meaning and positivity represent two motivational pathways that may shape digital engagement in distinct ways. From a hedonic perspective, a positivity orientation may lead individuals toward behaviors seeking affective reward and social responsiveness, potentially increasing engagement but also amplifying comparison-based vulnerabilities. From a eudaimonic perspective, meaning orientation may promote intentional, value-congruent digital behaviors, reduce external evaluative pressures, and enhance flourishing and psychological resilience.

Notably, these orientations are not mutually exclusive; individuals may endorse both to some degree. Our aim is to test whether they show differential, incremental associations with digital outcomes when examined simultaneously.

These pathways generate theoretically grounded expectations regarding digital behaviors (screen time, engagement), digital experiences (FoMO, comparison, flourishing), and psychological outcomes (self-compassion, psychopathology). Crucially, these expectations are not deterministic; rather, they reflect tendencies rooted in motivational theory. This distinction ensures that the hypotheses do not read as trivial predictions but as extensions of a nuanced theoretical framework applied to a novel domain.

Viewed through an information-science lens, the present study conceptualizes social media platforms as information-rich systems and positions motivational life-orientation strategies as upstream filters that organize digital information engagement. From this perspective, prioritizing meaning and prioritizing positivity can be understood as motivational filters that shape how individuals select, attend to, interpret, and regulate digital information. By extending motivational life-orientation theory into the domain of information behavior, the present study contributes a person-centered account of how individual motivations organize engagement with contemporary digital information environments.

Taken together, the present study advances the literature in three key ways. First, rather than focusing on isolated digital behaviors or risk factors, it adopts a motivational life-orientation perspective to explain why individuals engage with the same digital environments in qualitatively different ways. Second, it extends hedonic–eudaimonic theory into the domain of social media and digital flourishing, a context in which these orientations have rarely been examined empirically. Third, by integrating behavioral indicators, digital experiences, and psychological outcomes within a single preregistered framework, the study offers a more coherent account of how motivational priorities are associated with both digital engagement patterns and well-being–related outcomes.

2. The Present Study

The current study extends positive psychology into the digital realm by examining how two life-orientation strategies—prioritizing meaning and prioritizing positivity—differentially predict a comprehensive set of digital and psychological outcomes. Drawing on hedonic–eudaimonic distinctions, we propose that meaning and positivity orientations function as distinct motivational pathways that shape how individuals use and experience social media. By integrating behavioral indicators (screen time, engagement), digital vulnerabilities (FoMO, social comparison), and positive digital functioning (digital flourishing) alongside broader psychological outcomes (self-compassion, psychopathology), the study offers a more comprehensive motivational account of digital well-being.

To test this framework, we examined seven outcomes central to digital well-being research: daily social media screen time, social media engagement, FoMO, social comparison, digital flourishing, self-compassion, and psychopathology. By conceptualizing prioritizing meaning and positivity as motivational antecedents of digital information engagement, the present study advances an integrative account of how individual orientations shape not only social media use but also the interpretation and experiential quality of mediated information environments. Based on the theoretical models reviewed above, we formulated the following hypotheses.

H1. 

Prioritizing meaning—but not prioritizing positivity—will be negatively associated with daily screen time on social media.

H2. 

Prioritizing positivity—but not prioritizing meaning—will be positively associated with social media engagement.

H3. 

Prioritizing meaning—but not prioritizing positivity—will be negatively associated with FoMO.

H4. 

Prioritizing positivity—but not prioritizing meaning—will be positively associated with social comparison.

H5. 

Prioritizing meaning—but not prioritizing positivity—will be positively associated with digital flourishing.

H6. 

Prioritizing meaning—but not prioritizing positivity—will be positively associated with self-compassion.

H7. 

Prioritizing meaning—but not prioritizing positivity—will be negatively associated with psychopathology.

3. Methods

All aspects of the study design, methods, and analysis plan were pre-registered at the Open Science Framework (OSF; https://doi.org/10.17605/OSF.IO/6J357).

3.1. Participants

Participants were recruited through an online panel—a survey platform recognized by the Israeli Bureau of Statistics as representative of the Israeli population. Recently, online panels have become a common way to target and reach respondents in social science research [22,23]. Participants received $10 for completing both questionnaires. The study received ethical approval from the first author’s academic institution (IRB No. 665). The final sample included 414 Israeli adults with a mean age of 33.65 years (SD = 8.81). About 73% of the participants were women, and they spent an average of 4.09 h per day on social media (SD = 2.36). Regarding marital status, 31.9% were single, 59.4% were married, and 8.7% were divorced or widowed. 93.7% of participants were Jewish, and 6.3% were Muslims. Participants’ religiosity levels were distributed as follows: 39.1% secular, 46.4% traditional, and 14.5% religious. The final sample size exceeds the threshold recommended by Cohen [24] for achieving a 0.90 statistical power (N = 257) to detect a small-to-medium effect size (f² = 0.05). Such effect sizes are typical in individual-differences research within social and positive psychology.

3.2. Measures

We used validated Hebrew versions of established psychological scales used in previous research. The only exception was the Digital Flourishing Scale, for which no Hebrew version existed; this scale was translated and adapted for the current study using standard translation and back-translation procedures. In accordance with accepted scale translation procedures [25,26,27], the scale was first translated from English to Hebrew by two translators, who subsequently agreed on a single version. The scale versions were then back-translated into English by two other translators, who reached consensus and confirmed that the Hebrew versions did not differ in meaning from the original. Next, the Hebrew questionnaire was used in a pilot study of 30 participants to obtain their feedback on the items, which were then used to edit wording in a way that, according to the translators, did not change items’ substantive meaning.

Given that this study involved the first Hebrew adaptation of the Digital Flourishing Scale (DFS), we focused on initial evidence of structural validity and reliability. Specifically, we examined the internal structure of the scale using exploratory and confirmatory factor-analytic procedures and assessed the overall internal consistency of the scale.

An exploratory factor analysis (EFA) was conducted to examine the internal structure of the Hebrew version of the Digital Flourishing Scale. The analysis used principal axis factoring with oblimin rotation, consistent with the theoretical assumption that the dimensions of digital flourishing represent interrelated facets of a broader construct. The Kaiser–Meyer–Olkin measure indicated good sampling adequacy (KMO = 0.82), and Bartlett’s test of sphericity was significant (χ²(300) = 2761.87, p < 0.001).

The EFA yielded a five-factor solution explaining 64.06% of the total variance. The resulting factor structure was largely consistent with the original multidimensional conceptualization of the scale, with items loading primarily on their theorized dimensions and showing minimal cross-loadings. A confirmatory factor analysis (CFA) was then conducted in R using the lavaan package [28] to evaluate the fit of this hypothesized structure. Model fit was assessed using commonly reported indices. The model chi-square was significant (χ²(257) = 508.04, p < 0.001), as expected given the large sample size. The relative chi-square indicated good fit (χ²/df = 1.98). Additional fit indices indicated acceptable-to-good model fit (RMSEA = 0.065, SRMR = 0.082, CFI = 0.92, TLI = 0.91). Following these analyses, the finalized questionnaire was administered online.

Because the central constructs examined in this study—motivational life-orientation strategies and perceived digital flourishing—reflect individuals’ subjective priorities, values, and experiential evaluations, self-report measures constitute a theoretically appropriate and widely accepted assessment approach. Motivational orientations are inherently introspective and concern how individuals perceive and organize their daily experiences, while digital flourishing captures perceived qualities of digitally mediated interactions that cannot be directly inferred from objective usage indicators alone.

• Daily screen time on social media. Participants were asked how many hours per day they spend on social media (minimum: 0, maximum: more than 12 h per day).

The instructions were as follows:

By social media, we mean websites and apps where you can view, post, and share photos, videos, and messages with others. You can view, receive, and send messages on these platforms. Examples of social media include social networking sites such as Instagram, Facebook, and LinkedIn, as well as apps/sites such as Twitter, WhatsApp, SMS, and Facebook Messenger (i.e., social messaging platforms).

Messaging platforms (e.g., WhatsApp, Facebook Messenger, SMS) were included insofar as they function as socially mediated information environments that involve ongoing social interaction, exposure to interpersonal cues, and opportunities for social monitoring and comparison. Although these platforms differ from public-facing social network sites in visibility and affordances, they nonetheless constitute a substantial portion of individuals’ daily digitally mediated social information exchange.

A self-reported measure of social media use was included because it captures subjective perceptions and evaluations that are theoretically relevant to well-being [29]. While objective data provides precise usage metrics, it does not account for cognitive and emotional processes or differences between active and passive engagement. Accordingly, self-reports offer complementary information that is particularly relevant for motivational and well-being-oriented research questions. Similar self-reported measures have recently been used in studies examining social media use and subjective well-being [30,31].

• Engagement in social media was measured using the previously validated social media level of participation scale [32], which includes four statements about online activities: reading, commenting, sharing, and posting. Each statement was rated on a 6-point Likert scale (1 = strongly disagree; 6 = strongly agree). Cronbach’s alpha was 0.81, and the average score was used as the composite engagement score. In the present study, this measure is conceptualized as behavioral information engagement (i.e., observable participation behaviors), rather than emotional involvement or subjective immersion.
• Social comparison, based on Chou and Edge [1], included statements about others’ lives (“Many of my friends have a better life than I do; Many of my friends are happier than I am”) and were rated on a scale from 1 (complete disagreement) to 6 (complete agreement). The correlation between these two statements was significant (r = 0.82, p < 0.001) and was similar to that reported in previous studies [33]. The average of these responses was used to create a single social comparison variable.
• Fear of Missing Out (FoMO) was assessed using the 10-item FoMO scale developed by Przybylski et al. [34] and adapted for Hebrew by Alt and Boniel-Nissim [35]. The scale measures the extent to which participants agreed or disagreed with statements concerning their fear of missing out on social events and experiences, with no relation to the outage event: for example, “I fear others have more rewarding experiences than me.” The statements were rated on a 5-point Likert scale (1 = strongest disagreement; 5 = strongest agreement). Cronbach’s alpha was α = 0.87, and the mean was calculated for the independent variable FoMO.
• Digital Flourishing. The 25-item Digital Flourishing Scale (DFS [4]) was used to assess digital flourishing, defined as positive perceptions of mediated social interactions. The scale covers five dimensions: connectedness, civil participation, positive social comparison, authentic self-presentation, and self-control. Participants rated how true these behaviors were for them in the past month on a 5-point Likert scale from 1 (not at all true of me) to 5 (very true of me), with an option for “Not applicable for me.” Cronbach’s alpha was α = 0.91, and the mean was calculated to create a total digital flourishing score. Because the DFS captures individuals’ perceived quality of digitally mediated experiences (e.g., authenticity, relational depth, and self-control), self-report is an appropriate and theoretically aligned measurement approach for this construct.
• Prioritizing positivity. The Prioritizing Positivity Scale developed by Catalino, Algoe, and Fredrickson [9] was used to assess the extent to which people seek positive emotional experiences when making decisions about how to organize their day-to-day lives. Participants indicated their agreement or disagreement on a 9-point scale (1 = strongly disagree, 9 = strongly agree) with six items, including: “I look for and nurture my positive emotions” and “A priority for me is experiencing happiness in everyday life.” (α = 0.86).
• Prioritizing meaning. The Prioritizing Meaning Scale developed by Russo-Netzer [10] was used to measure the extent to which individuals intentionally act and organize, as well as make decisions, in their day-to-day life, so that they can experience more meaning. Respondents were asked to use a 9-point scale (1 = disagree strongly, 9 = agree strongly) with 12 items, including: “I prefer to engage in activities which are related to the sense of meaning in my life” and “The manner in which I organize my day reflects values that are meaningful to me.” (α = 0.94).
• Self-compassion. Self-compassion was measured using the 12-item Self-Compassion Scale–Short Form (SCS-SF [36]), a validated short version of Neff’s original 26-item Self-Compassion Scale [19]. The SCS-SF assesses how well individuals respond to personal challenges with self-kindness instead of self-judgment, see their experiences as part of the shared human condition rather than as isolating, and approach their emotions with mindfulness rather than over-identification. Participants rated each item on a 5-point Likert scale from 1 (almost never) to 5 (almost always), with higher scores indicating greater self-compassion. The SCS-SF has demonstrated good reliability, convergent validity, and a stable underlying structure across numerous studies, including meta-analyses and cross-cultural research [37,38,39]. In this study, Cronbach’s alpha was α = 0.83, and the mean score was used to compute a total self-compassion score.
• Psychopathology. Psychopathology was assessed using the Depression, Anxiety, and Stress Scale (DASS-21 [40,41]), which includes three subscales measuring depression, anxiety, and stress. When combined, these provide a total psychopathology score. The scale comprises 21 items rated on a 4-point Likert scale (α = 0.93); the final score is obtained by summing the responses.
• Control Variables. Several sociopsychological and demographic variables that have been found to be associated with meaning and life satisfaction were controlled for in the statistical analysis. These include age [42], gender [43], marital status [44], and religiosity level [45]. Religiosity level was assessed using three culturally normative categories in Israel: secular, traditional, and religious. These categories reflect different levels of engagement with religious practices, ranging from minimal observance (secular) to selective or culturally motivated observance (traditional), to consistent observance of religious law (religious). Participants were asked to respond to the question: “In terms of religion, I consider myself…” (0 = secular, 1 = traditional, 2 = religious).

3.3. Data Analysis

A multiple linear regression analysis was conducted to examine the relationships among study variables. The control variables (age, gender, marital status, and religiosity level) were treated as covariates. Before the analyses were conducted, the data were checked for normality, and no violations were detected. All regression assumptions were examined prior to analysis.

To assess potential multicollinearity among predictors, variance inflation factors (VIFs) and tolerance values were calculated for all regression models. VIF values ranged from 1.05 to 2.00, and tolerance values exceeded 0.50 across models, indicating no evidence of problematic multicollinearity.

Although the hypotheses were theoretically directional, all statistical tests were conducted using two-tailed significance thresholds. This decision was made a priori in order to adopt a conservative testing strategy and to reduce the risk of Type I error at the level of individual tests. This approach reflects a theory-driven analytic strategy focused on a limited set of preregistered hypotheses, rather than an exploratory search across multiple outcomes.

Hypotheses were tested using separate multiple regression models for each outcome. This analytic strategy was theoretically motivated, as the dependent variables represent conceptually distinct domains—digital behavior, digital experiences, and psychological functioning—rather than indicators of a single latent construct. Modeling each outcome separately allowed for a precise examination of how prioritizing meaning and prioritizing positivity relate to specific facets of digitally mediated life, without imposing assumptions about shared variance or higher-order structural relations.

4. Results

Table 1 presents descriptive statistics and intercorrelations for all study variables.

Table 1. Descriptive statistics and intercorrelations of study variables (N = 414).

Measure	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. Prioritizing meaning	81.88	16.60
2. Prioritizing positivity	42.13	7.82	0.53 **
3. Daily screen time on social media	4.09	2.36	−0.17 *	0.01
4. Social media engagement	4.65	1.26	0.01	0.20 **	0.31 **
5. Fear of missing out	2.41	0.91	−0.14 *	−0.02	0.11	0.24 **
6. Social comparison	2.10	1.13	−0.21 **	0.25 **	−0.03	−0.02	0.32 **
7. Digital flourishing	3.68	0.65	0.28 **	0.13	−0.03	0.01	−0.09	−0.03
8. Self-compassion	3.53	0.66	0.33 **	0.17 *	−0.13	−0.14 *	−0.45 **	−0.36 **	0.09
9. Psychopathology	11.04	9.41	−0.37 **	−0.19 *	0.09	0.03	0.39 **	0.34 **	−0.04	−0.49 **
10. Age, in years	33.65	8.81	−0.06	−0.13	−0.23 **	−0.20 **	−0.11	0.00	−0.10	0.01	−0.12
11. Gender	-	-	0.01	−0.06	−0.13	−0.09	0.02	−0.04	0.04	0.05	−0.04	0.04
12. Marital status	-	-	−0.13	−0.11	−0.17 *	−0.15 *	−0.02	−0.12	−0.04	0.08	−0.01	0.42 **	0.01
13. Religiosity level	1.75	0.69	0.02	−0.07	0.06	0.02	0.03	0.04	0.13	−0.07	0.10	−0.17 *	−0.12	−0.10

Note. M = Mean; SD = Standard Deviation. * p < 0.05, ** p < 0.01.

The regression analyses examining associations between prioritizing meaning, prioritizing positivity, and the seven outcome variables are reported below. Effect sizes across models ranged from small to medium, consistent with expectations for individual-differences research on digital behavior and well-being.

4.1. Daily Screen Time on Social Media

The overall model was statistically significant, F(6,407) = 4.64, p < 0.001, with an R² of 0.12, and an adjusted R² of 0.10. The corresponding effect size (f² = 0.14) indicates a small to medium effect size, approaching the medium threshold [24]. Prioritizing meaning was negatively associated with daily social media screen time (β = −0.255, p = 0.001), whereas prioritizing positivity was not significantly associated with daily social media screen time (β = 0.105, p = 0.191) (for complete regression results, see Table 2). These findings support Hypothesis 1.

Table 2. Regression coefficients for daily screen time on social media.

Variable	B	95% CI	β	t	p
Age	−0.048	[−0.087, −0.009]	−0.18	−2.40	0.017
Gender	−0.668	[−1.45, 0.113]	−0.11	−1.69	0.093
Marital status	−0.203	[−0.462, 0.055]	−0.11	−1.55	0.122
Religiosity level	0.049	[−0.412, 0.509]	0.01	0.21	0.836
Prioritizing meaning	−0.036	[−0.059, −0.014]	−0.25	−3.23	0.001
Prioritizing positivity	0.032	[−0.016, 0.079]	0.10	1.31	0.191

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

The results also indicate that age significantly predicted daily social media screen time (β = −0.18, p = 0.017).

4.2. Social Media Engagement

The overall model was statistically significant, F(6,407) = 3.47, p = 0.003, with an R² of 0.09, and an adjusted R² of 0.07. The corresponding effect size was f² = 0.10. Prioritizing positivity was positively associated with social media engagement (β = 0.237, p = 0.004), whereas prioritizing meaning was not significantly associated with social media engagement (β = −0.134, p = 0.098) (for complete regression results, see Table 3). These findings support Hypothesis 2.

Table 3. Regression coefficients for social media engagement.

Variable	B	95% CI	β	t	p
Age	−0.021	[−0.042, 0.001]	−0.14	−1.91	0.058
Gender	−0.227	[−0.650, 0.197]	−0.07	−1.06	0.293
Marital status	−0.078	[−0.218, 0.062]	−0.08	−1.10	0.271
Religiosity level	−0.008	[−0.258, 0.241]	−0.04	−0.07	0.948
Prioritizing meaning	−0.010	[−0.022, 0.002]	−0.13	−1.66	0.098
Prioritizing positivity	0.038	[0.013, 0.064]	0.24	2.93	0.004

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

4.3. Fear of Missing Out

The overall model was statistically significant, F(6,407) = 2.75, p = 0.013, with an R² of 0.04 and an adjusted R² of 0.01. The corresponding effect size was f² = 0.04. Prioritizing meaning was negatively associated with fear of missing out (β = −0.187, p = 0.025), whereas prioritizing positivity was not significantly associated with fear of missing out (β = 0.074, p = 0.374) (for complete regression results, see Table 4). These findings support Hypothesis 3.

Table 4. Regression coefficients for fear of missing out.

Variable	B	95% CI	β	t	p
Age	−0.012	[−0.028, 0.004]	−0.11	−1.46	0.145
Gender	0.086	[−0.228, 0.399]	0.04	0.54	0.591
Marital status	0.010	[−0.094, 0.113]	0.01	0.18	0.854
Religiosity level	0.036	[−0.149, 0.221]	0.03	0.38	0.701
Prioritizing meaning	−0.010	[−0.019, −0.001]	−0.19	−2.26	0.025
Prioritizing positivity	0.009	[−0.010, 0.028]	0.07	0.89	0.374

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

4.4. Social Comparison

The overall model was statistically significant, F(6,407) = 3.74, p = 0.002, with an R² of 0.10, and an adjusted R² of 0.07. The corresponding effect was f² = 0.11. Prioritizing positivity was positively associated with social comparison (β = 0.202, p = 0.013), whereas prioritizing meaning was not significantly associated with social comparison (β = −0.120, p = 0.135) (for complete regression results, see Table 5). These findings support Hypothesis 4.

Table 5. Regression coefficients for social comparison.

Variable	B	95% CI	β	t	p
Age	0.006	[−0.013, 0.025]	0.05	0.634	0.527
Gender	−0.151	[−0.530, 0.228]	−0.05	−0.78	0.434
Marital status	−0.155	[−0.280, −0.030]	−0.18	−2.24	0.016
Religiosity level	0.019	[−0.204, 0.243]	0.01	0.17	0.866
Prioritizing meaning	−0.008	[−0.019, 0.003]	−0.12	−1.50	0.135
Prioritizing positivity	0.029	[0.006, 0.052]	0.20	2.50	0.013

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

The results also indicate that marital status was negatively associated with social comparison (β = −0.18, p = 0.016).

4.5. Digital Flourishing

The overall model was statistically significant, F(6,407) = 3.83, p = 0.001, with an R² of 0.10, and an adjusted R² of 0.08. The corresponding effect size was f² = 0.11. Prioritizing meaning was positively associated with digital flourishing (β = 0.288, p < 0.001), whereas prioritizing positivity was not significantly associated with digital flourishing (β = −0.019, p = 0.815) (for complete regression results, see Table 6). These findings support Hypothesis 5.

Table 6. Regression coefficients for digital flourishing.

Variable	B	95% CI	β	t	p
Age	−0.006	[−0.017, 0.005]	−0.08	−1.12	0.263
Gender	0.092	[−0.124, 0.308]	0.06	0.84	0.403
Marital status	0.020	[−0.052, 0.091]	0.04	0.54	0.587
Religiosity level	0.113	[−0.015, 0.241]	0.12	1.75	0.082
Prioritizing meaning	0.011	[0.005, 0.017]	0.29	3.60	<0.001
Prioritizing positivity	−0.002	[−0.015, 0.012]	−0.02	−0.23	0.815

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

It is noteworthy that, at the bivariate level, the Digital Flourishing Scale (DFS) total score showed a significant positive association with prioritizing meaning, whereas its associations with other study variables were generally weak or non-significant (Table 1). This pattern is theoretically consistent with the scale’s multidimensional, facet-based structure, whereby aggregating distinct components—such as connectedness, self-control, authenticity, civil participation, and positive social comparison—may attenuate or offset associations with specific psychological or behavioral outcomes. Accordingly, results related to digital flourishing are interpreted primarily on the basis of the preregistered multivariate regression models rather than simple bivariate correlations.

4.6. Self-Compassion

The overall model was statistically significant, F(6,407) = 5.59, p < 0.001, with an R² of 0.14 and an adjusted R² of 0.12. The corresponding effect size was f² = 0.17. Prioritizing meaning was positively associated with self-compassion (β = 0.279, p < 0.001), whereas prioritizing positivity was not significantly associated with self-compassion (β = 0.122, p = 0.105) (for complete regression results, see Table 7). These findings support Hypothesis 6.

Table 7. Regression coefficients for self-compassion.

Variable	B	95% CI	β	t	p
Age	−0.001	[−0.012, 0.009]	−0.02	−0.27	0.789
Gender	0.006	[−0.208, 0.220]	0.00	0.05	0.958
Marital status	0.067	[−0.004, 0.137]	0.14	1.86	0.065
Religiosity level	−0.056	[−0.182, 0.070]	−0.06	−0.90	0.380
Prioritizing meaning	0.011	[0.005, 0.017]	0.28	3.57	<0.001
Prioritizing positivity	0.011	[−0.002, 0.024]	0.12	1.68	0.105

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

4.7. Psychopathology

The overall model was statistically significant, F(6,407) = 7.16, p < 0.001, with an R² of 0.18 and an adjusted R² of 0.15. The corresponding effect size was f² = 0.21. Prioritizing meaning was negatively associated with psychopathology levels (β = −0.300, p < 0.001), whereas prioritizing positivity was not significantly associated with levels of psychopathology (β = −0.114, p = 0.075) (for complete regression results, see Table 8). These findings support Hypothesis 7.

Table 8. Regression coefficients for psychopathology.

Variable	B	95% CI	β	t	p
Age	−0.152	[−0.034, 0.001]	−0.14	−1.98	0.050
Gender	−0.818	[−3.83, 2.19]	−0.03	−0.53	0.593
Marital status	0.035	[−0.962, 1.03]	0.01	0.07	0.945
Religiosity level	0.954	[−0.824, 2.73]	0.07	1.06	0.291
Prioritizing meaning	−0.170	[−0.256, −0.084]	−0.30	−3.91	<0.001
Prioritizing positivity	−0.173	[−0.356, 0.011]	−0.11	−1.76	0.075

Note. B = unstandardized regression coefficient; CI = confidence interval; β = standardized beta; t = t statistic; p = significance level. Bold indicates statistical significance at p < 0.05.

Across all regression models, age, gender, marital status, and level of religiosity were included as covariates, and the central patterns of association between motivational orientations and the outcome variables remained stable after accounting for these demographic factors.

5. Discussion

The present findings reveal a clear motivational asymmetry in how individuals engage with and experience social media: prioritizing meaning was consistently linked to healthier, more intentional digital engagement and better psychological well-being, whereas prioritizing positivity was associated with more active use and increased social comparison, without corresponding well-being benefits. These findings highlight two distinct motivational pathways that influence how individuals navigate both daily life and digital environments. Importantly, these associations emerged above and beyond key demographic covariates (age, gender, marital status, religiosity level), suggesting that motivational orientation adds incremental explanatory value in predicting both digital behavior and well-being outcomes.

5.1. Prioritizing Meaning as a Protective Orientation in the Digital Age

A central contribution of the study lies in demonstrating the protective role of prioritizing meaning in the context of digital life. Individuals who prioritized meaning reported lower daily screen time and reduced fear of missing out. These associations are theoretically coherent with prior work showing that a sense of life meaning anchors attention toward personally valued goals, thereby reducing susceptibility to external cues and social monitoring pressures [16,17]. Building on this foundational work, more recent evidence suggests that meaning-oriented individuals not only anchor their attention internally but also employ a distinct intentional mindset that shapes how they interpret and benefit from everyday experiences [18]. From this perspective, prioritizing meaning reflects a stable orientation that guides appraisal processes and helps individuals derive coherence and purpose even in dynamic or emotionally charged environments such as social media. One plausible mechanism is that prioritizing meaning fosters a ‘purposeful use’ stance toward platforms, entering social media with a defined intention (e.g., connection, learning, contribution) rather than mood management, thereby reducing opportunistic scrolling, lowering exposure to FoMO triggers, and supporting self-control. Their online behavior appears to be guided by a more coherent internal framework, allowing them to navigate digital environments in ways that support autonomy, relational depth, and self-regulation—core components of healthy digital functioning identified in previous work [3,4].

Building on this perspective, recent research on value-based functioning shows that when individuals organize their daily choices around core personal values, they tend to interpret experiences—including mediated ones—through a lens of significance rather than stimulation [20]. This value-driven mode of engagement may help explain why meaning-oriented users translate digital interactions into greater flourishing and psychological resilience, rather than into affect-driven or comparison-based responses.

The pattern extended to psychological functioning: prioritizing meaning was associated with greater self-compassion and lower psychopathology. This aligns with meaning-making frameworks, suggesting that construing experiences through coherence and significance supports adaptive emotional processing and reduces distress [21,46], and that self-compassion is intertwined with eudaimonic processes that foster psychological stability [47]. Together, these findings underscore the multifaceted nature of meaning as a resource that promotes both digital well-being and broader mental health.

5.2. Prioritizing Positivity: A Mixed Digital Profile

In contrast, prioritizing positivity was associated with greater social media engagement (including commenting, sharing, and posting) but was not linked to higher digital flourishing or improved psychological well-being. This pattern suggests that individuals who prioritize positive emotional experiences may be more inclined toward active, expressive forms of digital participation, without necessarily deriving broader experiential or psychological benefits.

A plausible interpretation is that positivity-oriented engagement may yield short-term affective rewards—such as momentary enjoyment or social responsiveness—without translating into the deeper qualities captured by digital flourishing (e.g., authenticity, self-control, and relational depth). This distinction aligns with emerging perspectives that differentiate between transient affective gratification and more sustained, value-based forms of digital well-being [48]. Future research using experience-sampling methods could examine whether positivity orientation is associated with short-lived affective gains that dissipate over time.

The non-significant associations between prioritizing positivity and the well-being outcomes warrant cautious interpretation. Across models, the standardized coefficients were consistently small in magnitude, indicating that any potential association—if present—is likely to be of limited practical significance in the current context. Importantly, the absence of statistical significance should not be interpreted as evidence for the absence of any effect, but rather as suggesting that prioritizing positivity does not show a robust or consistent relationship with well-being outcomes under the conditions examined in this study.

Notably, increased engagement among positivity-oriented individuals was accompanied by higher levels of social comparison—a process widely associated with diminished well-being through heightened self-evaluation and perceived self-discrepancies [14]. This pattern is theoretically informative: it suggests that while positivity-oriented individuals may be more active on social media, their engagement may also increase exposure to evaluative dynamics that undermine subjective benefit. Consistent with research on the paradox of happiness-seeking [12,49], such dynamics may help explain why greater activity does not translate into enhanced flourishing, self-compassion, or reduced psychopathology.

5.3. Two Distinct Motivational Pathways in Digital Life

Taken together, the findings highlight two distinct motivational pathways. The meaning-oriented pathway is characterized by intentional, value-congruent engagement with the digital world, lower reliance on external validation, and greater psychological resilience. In contrast, the positivity-oriented pathway reflects a motivational style centered on affective reward-seeking, which may amplify exposure to comparison processes that do not contribute to sustained well-being. This distinction extends broader frameworks differentiating hedonic and eudaimonic motives [6,8] by demonstrating how these orientations are differentially expressed and experienced within digitally saturated environments.

Beyond the effects of the two primary life-orientation strategies, the analyses also identified theoretically meaningful associations involving key demographic covariates. First, age emerged as a negative predictor of daily social media screen time (β = −0.18, p = 0.017; Table 2), indicating that younger adults reported spending more time on social media. This pattern is consistent with prior research showing that younger cohorts tend to engage more frequently and habitually with digital platforms, partly due to greater integration of social media into their social and professional routines [3]. Given the heightened reactivity of younger users to socially evaluative cues, this finding aligns with theoretical models suggesting that age-related differences may shape not only the quantity of digital use but also its emotional and motivational underpinnings.

Second, marital status significantly predicted social comparison tendencies (β = −0.18, p = 0.016; Table 5), such that individuals in committed relationships reported lower levels of social media comparison. This result corresponds with the broader literature demonstrating that stable relational bonds provide psychological security, reduce evaluative self-focus, and buffer against upward comparison processes [44]. Within the framework outlined in the introduction, this pattern is theoretically coherent: when individuals are anchored in relationships that provide meaning, coherence, and emotional stability, they are less dependent on external validation cues and less susceptible to the socially curated portrayals characteristic of digital environments. Thus, although demographic factors were not the focus of the present study, these findings reinforce existing theoretical perspectives regarding how developmental and relational contexts shape digital vulnerability and support the broader motivational framework proposed herein.

The present findings suggest that motivational orientations may function as upstream influences within the proposed conceptual framework, rather than as definitive causal determinants. Specifically, prioritizing meaning accounted for unique variance in digital well-being–related outcomes above and beyond basic sociodemographic factors. At the same time, unmeasured dispositional characteristics, such as personality traits or baseline levels of positive psychological functioning, may also contribute to these associations. Accordingly, the findings are best interpreted as supporting a directional, theoretically grounded model of motivational influence rather than a fully specified causal hierarchy.

6. Theoretical and Practical Implications

6.1. Theoretical Contributions

The study offers several theoretical implications. First, it extends positive psychology research by illustrating how prioritizing meaning and positivity shape not only subjective well-being but also digital behaviors and perceptions, thereby integrating psychological functioning with contemporary person-centered models of digital flourishing and media effects [3]. Second, it suggests that meaning may serve as a regulatory mechanism that mitigates well-documented digital vulnerabilities such as FoMO and social comparison. Third, the findings challenge the assumption that positivity orientation necessarily enhances well-being, demonstrating that in the digital context, this strategy may be less adaptive.

Beyond their implications for positive psychology, these findings also speak directly to core questions in information science regarding how individuals engage with information-rich digital environments.

From an information behavior perspective, the findings suggest that motivational life orientations operate as upstream filters within the proposed framework that organize users’ engagement with socially embedded information environments. In doing so, the study extends information behavior research beyond cognitive and situational determinants by positioning motivational life orientations as stable, person-level antecedents of how information-rich digital environments are selected, interpreted, and regulated. Meaning-oriented individuals appear to regulate exposure, interpretation, and participation in ways that enhance informational coherence and subjective value, whereas positivity-oriented individuals may engage more frequently with information streams without deriving comparable experiential benefits. This distinction advances person-centered models of digital information behavior by highlighting motivational orientation as a key determinant of how such environments are navigated and experienced.

Importantly, the present findings also carry implications that extend beyond theory and point toward concrete, actionable applications in digital well-being interventions and platform design. By identifying meaning-oriented motivation as a key factor associated with more intentional and resilient digital engagement, the study offers a theoretically grounded basis for developing interventions that target how individuals approach digital environments, rather than merely reducing usage time or exposure.

6.2. Practical Applications

Importantly, the present findings suggest that digital well-being interventions may benefit less from encouraging “positive use” or increased engagement per se, and more from shaping the motivational stance with which individuals approach digital environments. Specifically, fostering meaning-oriented motivation appears more strongly linked to intentional, regulated, and psychologically beneficial patterns of digital engagement than strategies focused primarily on increasing positive affect.

Practically, these results point to promising applications for digital wellness interventions, coaching processes, and preventive mental health frameworks. Programs that cultivate meaning-making, clarify personal values, and foster intentional action may help individuals engage with social media more mindfully and reduce maladaptive patterns of use. At a design level, digital platforms might benefit from incorporating features that encourage reflective engagement and purpose-driven interactions rather than promoting emotionally stimulating but comparison-laden content. For example, a meaning-oriented digital intervention could incorporate a brief intention-setting prompt presented at the point of entry (e.g., “What is your purpose for opening this app right now?”), encouraging users to articulate a value-consistent goal before engaging. Such prompts do not aim to reduce usage per se or enhance immediate positive affect, but rather to shift engagement from affect-driven consumption toward intentional, purpose-guided interaction—an orientation that, in the present study, was consistently associated with greater digital flourishing and psychological well-being. Similar meaning-oriented approaches may also include brief post-use reflection cues that invite users to consider whether a given digital interaction aligned with their personal values, thereby reinforcing intentional, value-congruent engagement.

6.3. Limitations and Future Directions

A primary limitation of the present study concerns its cross-sectional design, which precludes any causal interpretation of the observed associations. Although the findings are consistent with the proposed conceptual framework, longitudinal or experimental research is required to determine whether changes in motivational orientations—such as prioritizing meaning—lead to subsequent changes in digital behaviors or well-being outcomes. Accordingly, it is also possible that digital experiences feed back into individuals’ motivational orientations over time, resulting in reciprocal or dynamic associations that cannot be disentangled in cross-sectional data.

Second, although several associations were statistically significant, effect sizes were generally small to medium in magnitude. This pattern is consistent with prior research on individual differences in digital behavior and well-being, which emphasizes that such outcomes are shaped by multiple psychological, contextual, and platform-related influences [3]. Accordingly, results should be interpreted with appropriate caution, particularly given that non-significant findings may reflect limited or context-dependent associations rather than a definitive absence of effects. Examining multiple related outcomes also increases the risk of Type I error, underscoring the need for cautious interpretation of marginal or isolated findings.

Third, the study relied on self-report measures of social media use and digital experiences, including a single-item assessment of daily screen time. Importantly, daily screen time was included as a complementary behavioral indicator rather than as the primary theoretical focus of the study. The central pattern of findings regarding the differential roles of prioritizing meaning and prioritizing positivity was observed consistently across multiple outcomes beyond time-based indicators.

Although such measures are common in survey-based research, they may be subject to recall bias or shared method variance. At the same time, self-reports are well-suited to the present research questions, which focus on subjective experiences, motivational priorities, and perceived digital flourishing—constructs that cannot be fully captured through objective usage metrics alone. Future research could integrate objective tracking or experience-sampling methods to further refine the measurement of digital media engagement.

In addition, because the present study did not include a parallel English-language sample, the validation of the Hebrew version of the Digital Flourishing Scale provides evidence for initial structural validity and internal consistency rather than full cross-cultural measurement equivalence. Accordingly, future research should examine measurement invariance across languages and cultural contexts.

Fourth, the sample’s composition limits the generalizability of the findings. Participants were predominantly female, relatively young, largely Jewish, and recruited through an online panel, likely reflecting an urban, middle-class, and digitally literate population. Although all analyses controlled for age, gender, marital status, and level of religiosity, broader generalization to other groups—such as older adults, individuals from lower socioeconomic backgrounds, or culturally distinct communities—should be made with caution. Replication in more diverse and representative samples is therefore warranted.

Finally, the present models did not include controls for broader dispositional variables, such as personality traits or baseline levels of positive psychological functioning. Prior research suggests that such factors may be associated with both motivational orientations and digital well-being outcomes, raising the possibility of residual confounding. Accordingly, the findings should be interpreted as evidence for bounded explanatory associations rather than as establishing motivational orientation as a fully independent or causal upstream determinant. Future research should explicitly examine the positioning of motivational orientations relative to dispositional traits and baseline well-being using more comprehensive measurement models and longitudinal designs.

7. Conclusions

In sum, the present findings suggest that life-orientation strategies—prioritizing meaning and prioritizing positivity—are differentially associated with how individuals experience and engage with digital environments. While prioritizing positivity was primarily associated with greater activity and social comparison, prioritizing meaning was more consistently associated with healthier digital practices and psychological well-being in the present sample.

Taken together, these results underscore the potential relevance of meaning-oriented motivational frameworks for understanding individual differences in digitally mediated experiences. At the same time, the findings should be interpreted within the study’s methodological boundaries and do not imply causal or exhaustive explanations. Rather, they point to promising directions for future research examining how motivational orientations interact with dispositional traits, contextual factors, and digital affordances to shape sustainable forms of digital flourishing.