Log off to Level Up: The Effect of Social Media Hiatus on Goal Pursuit

Abstract

Concerns are growing that social media, with its constant notifications and attention-grabbing content, may distract individuals and hinder progress toward important goals. Despite its pervasive presence in our lives, the impact of social media on goal achievement has not been thoroughly studied. This within-subject experimental study aims to investigate the effects of social media hiatus (SMH), a short abstinence from social media usage, on goal pursuit processes. Participants (N = 107) completed daily diaries over three consecutive days of SMH and three days of regular social media use. SMH was manipulated by blocking participants’ access to multiple social media platforms. The results found that SMH predicted greater goal progress. In addition, SMH did not affect implementation planning but led to a better ability to resist temptations that conflict with important goals and greater volitional strength to pursue goals. The present research, in showing that even a short non-usage of social media can exert some effects on goal advancement outcomes, draws attention to the potential negative influence of social media and proposes regulation of social media use as a strategy to facilitate goal pursuit.

Keywords

social media hiatus goal progress self-control emotion

Social media platforms such as Facebook, Instagram, and TikTok have accumulated hundreds of millions of users in downloads every year. Their effects on daily functioning have gained considerable research attention. A recurring concern is whether social media use has become counterproductive, compromising important activities in daily life. An ensuing question is whether reduced use of social media could have the opposite effects. We examined whether social media hiatus (SMH) can affect a person's ability to make progress towards important goals. Specifically, we refer to SMH as the complete abstinence from all social media platforms over a short period of time.

One perspective is that excessive social media usage can negatively influence a person's ability to function effectively. This is because social media platforms frequently send messages and notifications of contents that are gratifying to attend to but can compromise attention on everyday tasks (Hofmann et al., 2017). Frequent users may grow to react automatically to media messaging (Naab & Schnauber, 2016) and what starts off as occasional usage can develop into an addictive pattern as motivation to resist the content becomes compromised (LaRose, 2010). Indeed, some studies have shown that social media use can be detrimental. It can be a source of distraction for students (David et al., 2015) and predicts poorer academic performance (Giunchiglia et al., 2018). It also predicts poor workplace performance (Andreassen et al., 2014). In contrast, reduced use of social media has been found to predict lower procrastination (Hinsch & Sheldon, 2013), improved attention (van Wezel et al., 2021), and better cognitive performance (Turel & Cavagnaro, 2019). Even pausing distracting notifications enabled increased attention and productivity (Fitz et al., 2019).

Goal Pursuit Processes

It is not clear to what extent SMH affects the ability to pursue goals in daily life. Goal pursuit is the process of working towards achieving a specific goal. Arguably, the chief indicator is goal progress, which reflects one's assessment of the progress made towards a goal. Perception that one is progressing well towards a goal have long been known to predict better well-being (Brunstein, 1993) and improved performance (Locke & Latham, 2002) and hence deserves continued study. Since social media can be distracting (David et al., 2015; Hofmann et al., 2017) and reduced usage appears to improve productivity and performance (Fitz et al., 2019; Giunchiglia et al., 2018), it could be predicted that SMH should increase goal progress. However, goal pursuit is not just about assessing how well one is moving towards a goal. Goal pursuit is a self-regulatory process that involves many components including constructing plans, motivating persistence, overcoming distractions, and so on. One might feel that good progress is being made right now. But if they also are unable to make plans, succumb to counter-goal activities, or lack motivation, their current upward trajectory towards the goal could turn south. Hence, we believe that it would be beneficial to examine several indicators of the different processes in goal pursuit. Drawing from recent research developments, we examined three ways that goal pursuit can be affected.

Implementation Planning

First, classic goal pursuit theories emphasize the importance of purposeful and strategic planning in effective goal pursuit. Goals are conscious targets demanding mental resources and behavioral actions. Goal attainment is enabled to the extent that implementable plans are made that include effective actions that facilitate progress (Gollwitzer, 2012; Inzlicht et al., 2014). For instance, to excel in a course, students’ chances would be higher if they develop implementable plans such as dividing study materials into manageable units and devoting specific times to learn them. Consistently, a meta-analysis found that when individuals are instructed to make concrete plans, they are more likely to achieve their goals (Gollwitzer & Sheeran, 2006). Considering this perspective, we examined implementation planning which refers to the extent to which plans were made to implement actions to achieve a goal (Gollwitzer & Sheeran, 2006; Wilkowski & Ferguson, 2016). As noted, goal pursuits are deliberative endeavors. Planning reflects a focus on the goal and requires mental resources. Hence, we expect social media users to have greater implementation planning when they avoid usage because they are able to leverage the additional time and resources that are freed up from the hiatus.

Temptation Resistance

Second, a person could make actionable plans but may not make progress because they fail to resist activities that are disruptive to their goal pursuit (Hofmann et al., 2012; Wilkowski & Ferguson, 2016). In real life, goal pursuits are rarely smooth sailing in part because of daily temptations which function as attractive alternative goals that conflict with the target goal. In the same example, the students could have developed implementable plans to excel in a course, but as good as the plans are, their progress could be disrupted by tempting activities that provide an alternative goal (e.g., watching TV to relax). Not everyone would be tempted; some would stay on course (e.g., not everyone wants to watch TV). But for those who are tempted, the ability to resist the tempting activities could be pivotal in changing the course of goal progress (Hofmann et al., 2012; Inzlicht et al., 2014). If attempts at resisting temptations are successful, progress becomes more likely. Hence, and following past studies (Hofmann et al., 2012; Wilkowski & Ferguson, 2016), we examined three components of temptation resistance—temptation, self-control attempt, and successful resistance, which refer to how tempted the person is to engage in activities that interfere with the targeted goal, how strongly the person tries to resist the temptations, and how successful the person is in resisting the tempting activities, respectively.

Goal Pursuit Volitional Strength

Third, it is possible that despite having implementable plans and the ability to resist temptations, one might still not make progress because there is no willpower (or “fuel”) to pursue the goal. This is even more pertinent considering that many goals are difficult to attain, sustained hard work is necessary, and there could be a substantial amount of knowledge and skills that must be learned to pursue the goal. Hence, we also tested goal pursuit volitional strength. This refers to one's deliberate intention or will to achieve a goal. It is a volition variable because a conscious decision is made to attain the objective and to ready oneself to exert the necessary effortful actions. It is a “strength” because of its state-like property that can vary in magnitude. The extent to which one is bent on achieving the goal is reflected by how determined and committed one feels about the goal. That is, the variable captures how unwavering one feels about pursuing the goal (determined) and the intention to stay on course despite potential obstacles (commitment). The higher is one's goal pursuit volitional strength, the more determined and committed one is in achieving the goal, reflecting a stronger deliberate intention to achieve the objective. Both determination and commitment are key constructs in several motivation theories related to goal pursuit. For instance, grit is a character strength that involves determination and perseverance despite lack of progress towards a goal, challenges or failures (Duckworth et al., 2007). Goal-setting research has found that goal commitment is a key moderator that increases the likelihood that people will continue to pursue a difficult goal (e.g., Locke & Latham, 2002). Self-determination theory specifies the types of need fulfilment that are predictive of volitional motivation (Ryan & Deci, 2000). Specifically, when fundamental needs for autonomy, competence and relatedness are met, one is more likely to be intrinsically driven to achieve valued objectives.

We predicted that SMH would lead to higher levels of goal progress. In addition, we predicted that SMH should also lead to higher implementation planning, self-control attempts, successful resistance, and volitional drive to pursue the goal, and lower levels of temptation and discouragement, relative to regular social media usage.¹

Methodological Limitations

In addition, there were methodological limitations in past studies, and we aimed to test our predictions with methods that improve on these limitations. First, there are many cross-sectional studies, which preclude causality assessment. Second, studies that used a retrospective survey design are at risk of recall bias (Jager et al., 2020). Third, experimental studies are few and limited by weak manipulation of social media usage. Some studies depended on participants’ compliance; they were only instructed to abstain from a social media platform (Hinsch & Sheldon, 2013; Stieger & Lewetz, 2018; Turel, 2021; Turel & Cavagnaro, 2019). However, they could still access social media if they wanted to. As an example, in Turel (2021), participants in the experimental group were instructed to “try to abstain from using Facebook for up to one week” and answer a self-report measure on noncompliance; 40% of the experimental group reported noncompliance. Fourth, some studies imposed only selective behavioral restrictions or partial usage controls, such as restricting a certain social media behavior (e.g., posting; Hall et al., 2021) or reducing rather than prohibiting social media usage (van Wezel et al., 2021). These approaches are not in line with the notion of social media hiatus which is the complete disuse of social media platforms within a period of time. Fifth, some studies employed methods that are easily circumvented, such as simply deleting social media applications from participants’ devices (Vally & D’Souza, 2019). Unfortunately, in this method, participants could easily redownload the apps in secret and delete them again before meeting the experimenter. Finally, highly stringent but disruptive protocols had been employed to prevent access to social media (Dunican et al., 2017; Eide et al., 2018; Wilcockson et al., 2019). These included confiscating participants’ smartphones for the period of study, which is too disruptive to participants’ daily needs (Wilcockson et al., 2019).

The Present Study

We conducted a daily diary study that employs a within-subject design comprising two conditions, SMH vs control. Participants first defined a goal that they were working towards. They completed six days of daily diary measures that included questions about the same goal. They were restricted from using social media over three consecutive days (SMH condition) and allowed use over another three consecutive days (control condition). An approximately one-week social media manipulation is a common protocol among past studies (Brailovskaia et al., 2023; Turel et al., 2018; van Wezel et al., 2021). In real life, long-term social media hiatuses are uncommon given genuine needs for social media and transient reasons for hiatus (e.g., to study for exam). A longer hiatus in a research study would also be disruptive for participants’ daily needs. As such, a three-day hiatus was deemed appropriate.

To manipulate SMH, we used technical protocols to block multiple social media platforms that are difficult to override, while still allowing participants usage of their devices for other purposes. Our study methodologically advances beyond previous investigations in various aspects. First, in contrast to non-experimental studies, SMH was manipulated to enable conclusions about causality. Second, no retrospective recall of social media usage was required to provide data free of memory bias concerns. Third, rather than relying on participants to avoid social media usage on their own volition, we installed technical restrictions in their devices to ensure actual prevention of usage. Fourth, in contrast to manipulations that allow partial and often times significant amount of social media usage, our study ensures an almost complete restriction of all social media platforms; ‘almost complete’ because—as will be explained—iPhone and Mac devices allow a minimum of one-minute usage per day that cannot be deactivated. Fifth, unlike previous SMH protocols that can be deactivated, we used technical protocols to block multiple social media platforms that are difficult to override. Finally, our method is not disruptive to participants’ daily needs as they could still use their devices except that social media could not be accessed for a short period of time.

Transparency and Ethics Approval

Data, data codes, and materials for this study can be found at https://osf.io/v836y/overview?view_only = dc3a9118f4e04c329965bbc005d9ec20. This study was not pre-registered. Ethics approval was obtained before the start of the study from our Departmental Ethics Review Committee and is endorsed by our institution's IRB (Reference Code: 2023-August-01).

Methods

Participants

This study employed a within-person daily diary experimental design with two counterbalanced conditions—SMH vs control. The key analysis compared goal-dependent variable scores averaged across the multiple measurements between conditions. We conducted a power analysis for repeated-measures designs, specifying an effect size of f = .20, power = 0.80, and α = .05, which indicated a minimum N = 52 to detect reliable effects. Considering expected attrition, exclusion due to noncompliance and the possibility of underestimating the effect size, we adopted a conservative approach and recruited more participants, stopping only when the research pool diminished significantly. We recruited 119 participants, most of whom were drawn from our participant pool participating for course credit with a minority (N = 29) recruited through word of mouth and Telegram channels for a payment of $15 (local currency).

The SMH and control conditions were counter-balanced across participants. Approximately half of the participants underwent the SMH condition first, while the rest underwent the control condition first. 12 participants were removed because they failed to describe their goals during the daily diary phase, used social media for two or more days in the SMH condition, or did not use social media for two or more days in the control condition. Final sample size was 107 participants (80 females, 26 males, 1 declined to report; Mean age = 21.2, SD = 3.3) of which 49 were in the SMH-first condition and the remainder were in the control-first condition.

Procedure

The present research was part of a broader daily diary study. The study lasted for six days, during which participants experienced three consecutive days of temporary social media non-use (SMH condition) and three consecutive days of regular use (control condition). Before signing up for the study, participants first read an online description stating that the study examined abstinence from social media. They were informed that they would be answering questionnaires every day for six days, out of which they would have to abstain from social media for three days. Participants in our institution were briefed that they should only sign up for a study after carefully reading its description and giving their consent. The description was followed by a consent button which also signed them up for the study. Later in the study, when participants met the experimenter and before installing the social media blocks, they were also informed that they had the right to withdraw anytime from then on. No participants dropped out of the study. If participants did drop out, they would still have been assigned course credit or monetary reimbursement on a pro-rated basis.

Upon signing up, participants were randomly assigned to the SMH-first condition or the control-first condition. Those in the control-first condition were immediately emailed a link to complete a pretest questionnaire online that included demographic items and personality (e.g., the Big 5) measures meant for other research purposes. The pretest was also for participants to identify a goal that they would rate later in the study. After completing the pretest measures, they would begin the six-day main phase of the study, starting the three days of normal social media usage. Those in the SMH-first condition scheduled a meet-up with the experimenters during which they would complete the same pretest. They began the six-day main phase of the study on the same day, starting with the three days of social media hiatus. The control-first participants met the experimenters on the fourth day where they would start undergoing the SMH condition. The meet-up was meant for installing social media blocks in the participants’ devices. For both order conditions, most meet-ups occurred in the morning between 9 a.m. and 11 a.m. and participants completed the diary in the evening.

During the meet-up, the experimenters placed social media blocks on the participants’ phones and laptops in line with recommendations from past studies (Stieger & Lewetz, 2018; van Wezel et al., 2021). The blocks targeted five platforms: Facebook, Instagram, Snapchat, TikTok, and X. YouTube was not included because its primary purpose was long-form video sharing which students might use for more informational or educational purposes rather than socializing. The blocks differed based on the participants’ devices (n_iphone = 71, n_Android = 36, n_Mac = 58, n_Windows = 49). For iPhone and Mac users, the native Screen Time application was used to block access to the five social media platforms. A daily usage limit of one minute was already programmed on the social media applications installed on participants’ phones. A minute was the minimum duration required by Screen Time blocks and could not be circumvented. This meant that for each day, participants could access the application for up to a minute, after which they were blocked for the rest of the day. Participants were instructed not to use this single minute allowance. The option ‘Block at End of Limit’ was turned on, and a password was set by the researcher to prevent participants from removing the limits. For Android users, the native Digital Well-being application (specifically the Focus Mode feature) was used to similar effect. Digital Well-being was used because other methods were expensive or intrusive. For Windows users, because there was also no method that would allow password-protected blocks, we edited host files to prevent participants from accessing the IP address of the social media websites. Participants could in principle amend the file, but this would be highly unlikely because most users do not have the relevant knowledge, the right solution was not easily found online without specific search terms (e.g., “host files”), and participants were unaware of how we implemented the blocks. The iPhone and Mac blocks were password protected by the investigators and could not be circumvented by the participants. Although the Windows blocks could not be password protected, it is highly unlikely that participants could circumvent the blocks. Furthermore, the Android blocks, while less robust, still provided some deterrence against noncompliance for participants. The blocks began at the time of the meetup with the experimenters and lasted until the completion of the final diary in the hiatus condition.

In the pretest, participants were asked to define and describe a goal that they were working towards. Our aim was to have participants focus on one goal and rate the goal pursuit measures on the same goal throughout the daily dairy phase. In addition, it should be a mid-term goal that the participant was working on regularly. It should not be a short-term goal (e.g., completing an assignment), which could be fulfilled before the study ended, or a long-term goal (e.g., retiring wealthy), which could be so far in the future that participants might not be thinking about it regularly. Hence, we asked participants to think of a goal that they would be working on within the academic semester, or to allow them more flexibility, a goal that they could be working towards till the end of the year. The instruction was: “We would like you to think of a goal that you are currently trying to achieve. This goal can be about anything you’d like. However, it should be a goal that you will be working on many or most days to achieve by the end of the semester or within the year.” All participants except five clearly reported only one goal as instructed (see Table 1 for examples). Of these five, four reported multiple goals (“getting an A for my mods, going to the gym at least two times a week, go for dance sessions more often,” “achieve good academic results and maintain healthy relationships,” “Achieve good grades while maintaining a high level of commitments to CCAs,” “To truly understand myself, be more organised, and have better time management skills”). It was unclear whether the remaining participant reported a single goal or multiple goals (“Planning my courses and things to do for 24/25 sem 2 exchange. Improving my Chinese”). In the daily diary phase of the study, participants were instructed to write down their goal in every diary, and this allowed us to determine the exact goal they focused on.

Table 1.

Number of Goals in Each Goal Type

Goal Type	Definition	Example Goals as Written	Number of Goals
Academics	goals related to academic pursuits including school activities (e.g., attending lectures, homework, projects) and outcomes (e.g., grades, mastering course contents)	“gpa 5.0 for the semester!,” “getting all A for my mods”	39
Job and Career	goals related to jobs (including part and full time) and career, including being an employee and self-employment (e.g., starting a business)	“Finding a stable job,” “Expanding my current photobooth rental business”	8
Habits and Routines	goals related to developing desired personal habits and daily routines and stopping undesired ones.	“Wake up for breakfast every day,” “Spending less time on my phone”	18
Hobbies	Goals related to seeking activities done in one's leisure time largely for pleasure	“To bake more,” “One goal I am working towards is having more time to work on new hobbies”	6
Skill Development	Goals related to learning and improving ability and competency (both technical and soft skills) to boost personal effectiveness (e.g., learning driving, a new language) but in domains not related to academic and job/career pursuits	“German,” “Aim to improve my mastery over Japanese”	3
Character Development	Goals related to building the self by cultivating positive traits (e.g., integrity, resilience, empathy)	“To be less judgemental: to be more kind to myself and to others,” “To take pride in the work I have done”	7
Physical Health	Goals related to health and fitness	“To be healthier,” “Improving my aerobic fitness”	17
Relationships	Goals related to forming, strengthening, or amending relationships	“Make new friends,” “Making strong, lasting relationships with people.”	2
Others	Goals that are difficult to classify and multi-goals	“To graduate from my cca” “getting an A for my mods, going to the gym at least 2 times a week, go for dance sessions more often”	7

Participants completed the same set of daily diary measures online every evening for the six days. They were emailed the questionnaire link daily at 8 p.m. and instructed to complete it by the end of the night. If participants did not complete the measures by 9 a.m. the next day, they would be reminded to do so as soon as possible and rate the items with respect to the day before. In each assessment, as a manipulation check, they were first questioned about their use of social media for that day. Eight participants did not use social media for two or more days while they were in the control condition and two participants used social media on two or more days while in the SMH condition; these participants were dropped from the analyses. The latter accessed social media through other devices (e.g., their friends’ phone). Next, participants were asked to briefly describe in one sentence the goal they stated in the pretest. This was to ensure that participants would be rating the same goal throughout the six days. Two participants did not complete this item in four or more assessments. As it was unclear whether they rated the same goal described in the pre-test (both indicate only one goal in the pretest), they were dropped from the analyses. One participant wrote a different goal from the pretest during the daily diary phase but since she reported the same goal throughout the six diaries, we retained her data for further analyses. Of the five participants who indicated or appeared to report multiple goals in the pretest, three were consistent in reporting a single goal throughout the six diaries (e.g., “achieving good results in schoolwork,” “Do well academically without sacrificing other commitments,” “Improve my Chinese and prepare for exchange”). Hence, we could determine for these three participants that only one goal was rated on in the dairy diary phase which is most pertinent to the present study. The remaining two participants consistently reported the same multiple goals across the six days (e.g., “study harder and get an A, be more active,” “Finding myself, be organized, time management skills”). To maximise power and considering that the number of these participants was small (N = 2), we included them for further analyses. All other participants reported the same goal on the pretest and across the six diary days. Then, participants answered measures related to their goal. Each goal item started with “Thinking back to your goal in relation to today, …”

On the last day of the SMH condition (for both order conditions), participants were emailed instructions to remove the social media blocks. They were encouraged to contact the experimenters if they had any questions. The debrief, containing the study's hypotheses, was immediately sent via email once participants completed the last diary.

Materials

Manipulation Check

Participants rated yes or no to two questions “Did you use social media on your laptop today?” and “Did you use social media on any other device today?” We expected phones to be the most common device participants would use to access social and hence blocked their phones. Hence, we included an item to check whether they also accessed social media through their laptops and another item to check for other devices. If participants responded yes to either question, they were asked to estimate the amount of time spent on each social media platform in minutes. To encourage truthful responses, participants were assured that they would still receive compensation if they reported using social media during the SMH phase.

Goal progress

Participants rated three items adapted from Koestner et al. (2008)—“I have made progress on this goal today,” “I felt like I was on track with my goal plan today,” and “I felt like I have achieved my goal today”—on 9-point scales ranging from 1 (none) to 9 (a great deal). The scale demonstrated high internal consistency (α_T1 = .96, α_T2 = .96, α_T3 = .99, α_T4 = .95, α_T5 = .95, α_T6 = .97).

Implementation planning

Participants rated two items from Wilkowski and Ferguson (2016)—“Did you think of specific actions for how to achieve this goal?” and “Did you plan when and where you should perform specific actions to achieve this goal?”—on 9-point scales that ranged from 1 (not at all) to 9 (definitely). The items were averaged and showed high internal consistency throughout the six days (α_T1 = .91, α_T2 = .95, α_T3 = .93, α_T4 = .90, α_T5 = .83, α_T6 = .96).

Temptation resistance

We used three items from Wilkowski and Ferguson (2016), rated on 9-point scales that ranged from 1 (not at all) to 9 (definitely), that measured temptation (“Were you tempted to do things which would interfere with this goal today?”), self-control attempts (“Did you try to resist the temptations that would interfere with achieving this goal today?”) and successful resistance (“Did you successfully resist temptations today that would interfere with achieving this goal?”)

Goal Pursuit Volitional Strength

The following items were rated on a 9-point scale that ranged from 1 (none) to 9 (a great deal)—“How determined did you feel about achieving your goal today?” and “How committed did you feel about achieving your goal today?” The scale demonstrated high internal consistency (α_T1 = .92, α_T2 = .92, α_T3 = .96, α_T4 = .88, α_T5 = .95, α_T6 = .95).

Results

Preliminary Analyses

We averaged each goal outcome across the three time points within each social media condition. The means are presented in Figure 1. The means suggest that participants were in general moderately driven in their goal pursuits in both the SMH and control conditions (i.e., they reported making moderate progress on their goals, were fairly apt at making plans, were reasonably effective at averting temptations, and felt moderately volitional about pursuing their goals).

Figure 1.

Means of goal outcomes by social media conditions.

Error bars represent standard error.

The correlations among these mean scores within each social media condition are presented in Table 2. The goal outcomes were generally strongly correlated with each other in both conditions.

Table 2.

Correlations between Goal Outcomes within Social Media Conditions

	1	2	3	4	5	6
1. Goal progress		.63**	.58**	.86**	.90**	.82**
2. Implementation Planning	.57**		.60**	.61**	.55**	.72**
3. Temptation	.57**	.44**		.65**	.52**	.53**
4. Self-control attempts	.79**	.60**	.70**		.89**	.78**
5. Successful resistance	.85**	.53**	.56**	.87**		.78**
6. Volitional strength	.82**	.66**	.46**	.64**	.72**

Below-diagonal panel: SMH condition; above-diagonal panel: control condition. * p < .05; ** p < .01

Main Analyses

For each goal outcome, we first conducted a 2 (social media: SMH vs control) × time (three assessments within each social media condition) × 2 (order: SMH-first vs control-first) mixed ANOVA with order as the only between-participant factor to examine whether there were any effects of time and order. The results are reported in Table 3. As shown, there were no main effects of time and order, indicating that the goal outcomes did not differ across days and were not affected by the counterbalancing of the SMH and control conditions. There was no interaction effect with social media with the only exception of a significant interaction effect between social media and time. Considering our interest in the effect of social media, we averaged the three scores within each social media condition and conducted a paired-samples t-test comparing the two conditions.²

Table 3.

Mixed ANOVA Predicting Goal Outcomes

	f	p	µ²	f	p	µ²
	Goal Progress			Implementation Planning
Social media (SM)	5.43	0.022	0.05	1.83	0.179	0.02
Time	1.94	0.146	0.02	0.92	0.401	0.01
Order	0.35	0.556	0.00	1.11	0.295	0.01
SM × Time	1.26	0.286	0.01	1.23	0.294	0.01
SM × Order	2.83	0.096	0.03	2.86	0.094	0.03
Time × Order	0.39	0.675	0.00	0.07	0.936	0.00
SM × Time × Order	0.61	0.543	0.01	0.06	0.938	0.00
	Temptation			Self-Control Attempts
Social media (SM)	0.00	0.951	0.00	3.57	0.062	0.03
Time	0.09	0.918	0.00	2.52	0.083	0.02
Order	0.61	0.438	0.01	0.31	0.577	0.00
SM × Time	3.82	0.024	0.04	0.92	0.401	0.01
SM × Order	0.93	0.338	0.01	2.13	0.147	0.02
Time × Order	0.05	0.951	0.00	0.28	0.754	0.00
SM × Time × Order	0.02	0.980	0.00	0.70	0.500	0.01
	Successful Resistance			Volitional Strength

As shown in Table 4 and Figure 1, several hypotheses were supported. The SMH condition was higher in goal progress, self-control attempts, successful resistance, and volitional strength, than the control condition. However, implementation planning and temptation did not differ between conditions. Hence, participants reported significantly more progress towards their goal, greater attempts at overcoming temptations, greater successful in resisting them, and feeling more volitional in pursuing their goals during the three days of social media hiatus compared to the three days of regular use. However, their extent of planning actions to pursue their goals and being tempted by distracting activities did not differ between these periods of non-use and use.

Table 4.

Descriptive Statistics and Paired-Sampled t-Test Comparing the SMH vs Control Conditions on Goal Outcomes

Goal Outcome	Paired-Sample T-Test
Goal Outcome	t	p	Cohen's d	95%CI Lower	95%CI Upper
Goal progress	2.80	0.006	0.27	0.08	0.46
Implementation planning	1.52	0.131	0.15	−0.04	0.34
Temptation	0.25	0.802	0.02	−0.17	0.21
Self-control attempts	2.06	0.042	0.20	0.01	0.39
Successful resistance	3.03	0.003	0.29	0.10	0.49
Volitional strength	2.28	0.025	0.22	0.03	0.41

All tests are two-tailed.

Moderating Effects of Goal Type

We explored whether the observed effects of social media might vary depending on participants’ goals. Note that the moderating role of goal was not a primary aim of this study. Therefore, results from the following analyses should be treated as exploratory. We adopted a two-pronged approach to classify the goals into several meaningful types. First, we considered the goal types commonly reported by youth and undergraduate populations based on prior empirical research. Research on youth goals has identified several common categories. For instance, Carroll et al. (2009, 2013) found that youths frequently report educational, career, interpersonal, sporting/health, family-related, autonomy, delinquency, and reputational goals. Similarly, studies employing Little's (1989) Personal Project Analysis—a widely used framework for examining youth life goals—have consistently identified categories including education, occupation, friendships, leisure, health, and daily routines (Cantor et al., 1987; Nurmi, 1991; Salmela-Aro & Nurmi, 1997). However, direct application of existing taxonomies requires cultural consideration. For instance, our understanding of Singaporean youths suggests that they might not report high levels of autonomy-related concerns or delinquent motivations. Our second, complementary approach involved examining the goals actually reported by our participants. Through observational analysis of all submitted goals, we aimed to identify whether there was a meaningful set of higher-order goal types in the data. Guided by both theoretical frameworks and observational analysis of our data, we identified eight broad goal types, as detailed in Table 1. Another category labelled “Other” was created for goals that could not be classified easily among the eight types and multi-goals. Recall that all participants except five reported the same goal in the pretest and the daily diary phase; for these participants, it was sufficient to code the goal reported at pretest. Recall also that three participants reported two goals at pretest but the same single goal across the six diaries; for these participants we coded the goal reported in the diaries. Finally, two participants reported two goals at both pretest and daily diary; at the final stage of the coding process, we agreed to code their goals as “Others.”

As the training round, two coders independently coded 20 goals to ensure that the coding scheme would be consistently understood and applied between them when coding all goals. They achieved consensus on 19 goals, indicating strong agreement even at this initial coding attempt. They then proceeded to code the remaining 87 goals. The coders agreed on 79 of the goals, showing strong inter-rater reliability (κ = .88). The coders then discussed the discrepancies with the aim of reaching an agreement on as many of them as possible. This led to the final set of coding with improved inter-rater reliability (κ = .97). Disagreements remained at this final round for three goals, which were assigned to the “Other” category. Table 1 presents the final number of goals within each goal type.

While the eight goal types extensively capture the range of goals reported by our participants, they present a problem for statistical analysis because the highly uneven sample sizes across goal types with some reported by very few participants would produce unreliable estimates. We therefore classified the goal types into two higher-order goal clusters—achievement and self-goal clusters—based on two considerations. First, the goal clusters are consistent with existing evidence. Salmela-Aro and Nurmi (1997) classified goals reported by undergraduates into broader categories including achievement goals which capture goals that increase socio-economic status and material attainment and self-goals which cover goals related to developing, indulging and protecting the self. Second, the two goal clusters have less uneven sample sizes. The achievement goal cluster (N = 47) includes the academic and job and career goals. The self-goal cluster (N = 57) comprised habits and routines, hobbies, skill development, character development, and health and fitness goals. This cluster also incorporated six of the seven “other” goals, which were largely self-related (e.g., religious motivation, doing well in extra-curriculum activities). The remaining “other” goal—a composite of achievement and self-goals (e.g., “getting an A for my mods, going to the gym at least 2 times a week, go for dance sessions more often”)—was excluded from subsequent analyses due to its mixed content. The two relationship goals were also excluded from subsequent analyses because they neither fit conceptually within either goal cluster or provided sufficient statistical power on their own.

We conducted mixed 2 (social media: SMH vs control) × 2 (goal cluster: achievement vs self) ANOVA on the four goal pursuit outcomes previously observed to differ significantly between the SMH condition and the neutral conditions. As shown in Table 5, no significant interaction was observed for all goal outcomes, indicating that goal type did not moderate the effects of social media. The effects of social media largely remained, albeit marginally significant for goal control attempts. There was no significant main effect of goal cluster.

Table 5.

Mixed ANOVA Predicting Goal Pursuit Outcomes from Social Media and Goal Cluster

Goal Outcome	F	p	µ²
Goal Progress
Social media	7.79	0.006	0.07
Goal cluster	0.06	0.802	0.00
Social media × Goal cluster	0.73	0.395	0.01
Goal Control Attempts
Social media	3.85	0.053	0.04
Goal cluster	0.91	0.341	0.01
Social media × Goal cluster	2.63	0.108	0.03
Successful Resistance
Social media	8.91	0.004	0.08
Goal cluster	0.87	0.355	0.01
Social media × Goal cluster	0.66	0.420	0.01
Volitional Strength
Social media	4.45	0.037	0.04
Goal cluster	0.20	0.654	0.00
Social media × Goal cluster	0.65	0.394	0.00

Discussion

The present study aimed to investigate the effects of temporary social media non-use on goal pursuit in daily life. We conducted a within-participant daily diary experiment in which participants underwent three consecutive days where social media was restricted and three consecutive days where they could use social media as usual. SMH was manipulated by blocking access to a wide range of popular social media sites using technical means. Before the daily diary phase of the study, participants were asked to think about an important goal that they hoped to achieve within the year and rated their progress, activities, and motivation towards the goal over the six days. Although the span of time was short, the study revealed significant differences as a function of the social media manipulation. In the days where the participants were restricted from social media, more progress toward one's goal was reported. In addition, they reported making more attempts at avoiding tempting activities that conflicted with their goal, were more successful at avoiding these temptations, felt greater intention to achieve their goals than on the days where they could use social media as normal. However, there was no effect on the extent to which plans were made to achieve the goals and how much temptation they encountered.³

The findings give some insights into distinct processes through which even a temporary non-usage of social media might affect goal pursuit. The first is predicated on the notion that goal pursuit is facilitated by deliberate efforts to make and implement concrete plans. However, we found no evidence in our data that SMH could impact goal pursuit through this process. As noted, SMH did not affect implementation planning. The second process draws on the fact that in real life, there are distracting activities that make it difficult to focus on one goal and goal pursuit relies on one's regulatory ability to resist them (Hofmann et al., 2012; Inzlicht et al., 2014). Our study found that SMH increased self-control attempts and enabled successful resistance. The third model is grounded in research on goal pursuit as a demanding process where challenges and setbacks are inevitable. According to this perspective, those with stronger volitional capacity—or “grit” (Duckworth et al., 2007)—are better able to sustain progress toward challenging goals (Locke & Latham, 2002). We therefore predicted that temporarily abstaining from social media could bolster volitional resources. Indeed, results show that the SMH participants reported feeling more determined and committed to pursuing their goals relative to the control condition participants, implying that a short social media hiatus of three days can strengthen one's deliberate intention to attain the goals no matter the difficulty.

Therefore, social media hiatus (SMH) may facilitate goal pursuit through mechanisms involving enhanced self-discipline and volitional resolve. In line with the Displacement Hypothesis (Neuman, 1988), reduced time spent on social media could enable more resources to be invested on averting activities contrary to one's goals. Interestingly, no significant difference was observed in how much temptations participants reported encountering across the days of regular social media use and temporary non-use. But with a short avoidance of social media, they reported being more able at self-control and more successful at resisting the temptations compared to the days where they could use social media. The results additionally suggest that SMH can also make people feel more driven to capture their goals (i.e., higher goal pursuit volitional strength). Past research has shown that determination and persistence influence progress in achievement contexts. Our findings suggest that social media hiatus (SMH) may facilitate goal achievement by strengthening the volitional resolve needed to execute goal-directed actions. However, the precise mechanism through which SMH enhances goal pursuit remains unclear. One potential explanation is that SMH liberates temporal and cognitive resources, thereby increasing perceived agency over one's goals and amplifying volitional commitment. Indeed, greater perceived personal control predicts heightened determination and goal commitment (Pekrun & Stephens, 2010; Smith et al., 2014)

SMH did not affect planning implementation. One reason might be that participants could only think of so many concrete plans. For instance, if the goal is to excel in a course, experienced students would already know the usual actions (e.g., complete readings, practice work problems, group discussion, revision). Therefore, whether they used social media or not made little difference. Nevertheless, it is quite pertinent that the difference in planning implementation between the SMH and control conditions was in the predicted direction albeit nonsignificantly. The effect size was small (d = 0.15), but a larger sample could potentially detect it.

The effects of SMH were consistent across participants’ reported goal types. For analytical purposes, we classified goals into specific categories and subsequently aggregated them into two broader clusters—achievement goals and self-development goals—to ensure statistical reliability. SMH's positive effects on goal progress, goal-directed control attempts, successful resistance to temptation, and volitional strength remained significant across both clusters (all ps ≤ .053), with no significant moderation by goal cluster. It should be noted that due to limited sample sizes within specific goal categories, we could not examine whether SMH effects vary across more granular goal types. While moderation by goal type was not a central focus of the present study, future research with larger samples should investigate this possibility.

Our study has other shortcomings that should be noted when interpreting the results. First, we examined only three days of non-usage of social media. It is unclear whether the observed effects from a short abstinence from social media would generalize to a longer period of avoidance. Second, we examined only social media platforms such as Facebook and Instagram. We would not generalize our findings to other types of digital platforms such as artificial intelligence (AI)-based tools. In this age where AI technology and use are accelerating, it is possible that avoidance of AI might eventually lead to reduced productivity in domains that depend on it. Third, no behavioral indicators were used. However, a variety of goals were examined here, each associated with different behavioral outcomes. It was untenable to include multiple behavioral measures to cover a range of goals within a single daily diary study without incurring participant fatigue. Furthermore, the literature lacks well-validated behavioral measures for many of the goal types examined here. Restricting to one goal so that only a limited number of behavioral measures could be included would reduce the generalizability and applied relevance of the findings.

As with any within-participant experimental design, there is a risk of participants being able to guess correctly the research question and adjusting their behaviour accordingly. However, the current items were rated together with a wide range of other measures administered for other research purposes as part of a larger study. The measures range widely, including mind wandering, forgetfulness, loneliness, several emotions, creative thinking, and attentional focus, making it difficult to figure out the hypothesis for any one of them. Furthermore, opposing lay hypotheses could be generated for the current measures. Some participants might believe that not having social media should make them more focused and motivated on their goals. Others might think that blocking out social media for just three days should not make a difference to the pursuit of any important goal. Yet others might even believe that taking social media away from them was supposed to make them feel depressed and less motivated.

We found that even a short three-day of temporary non-usage of social media can facilitate goal progress. We also found that SMH facilitates two processes that contribute to goal pursuit—self-control abilities against temptations and persistence-enabling emotional reactions. Overall, the findings suggest that social media can be an obstacle to goal pursuits and some abstinence can help in mitigating the negative effects and improving functioning and performance in daily life. Our current findings recommend periodic SMH as an intervention to facilitate pursuit of meaningful and impactful goals.

Footnotes

ORCID iD

Eddie M. W. Tong

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Notes

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