Study Smart! A Randomized Control Trial Examining the Effectiveness of an Individual Planning Intervention to Reduce Smartphone Interferences on Students' Academic Performance and Well-being
试验速览
- 阶段
- 不适用
- 入组人数
- 140
- 试验地点
- 1
- 主要终点
- Subjective measure of well-being: Subjective well-being
研究概览
简要总结
Smartphone use in academic contexts (e.g., in lectures or while studying for an exam) appears to go along with negative effects on students' academic performance (i.e., concentration, perceived learning achievement, and grades) and well-being (e.g., anxiety, positive and negative affect). Despite these alarming effects, intervention studies aiming at reducing smartphone interference are generally scarce and evidential inconsistent. For instance, existing studies suggest that short separation phases from smartphones accelerate anxiety and lead to cravings and smartphone overuse after the separation period. Other studies, however, conclude that separation phases enhance individual well-being and academic performance.
RESEARCH QUESTIONS. The present study aims at rigorously studying the effects of smartphone separation during exam phases on university students' performance and well-being. To do so, smartphone use reduction is incorporated into students' everyday life and encouraged through a planning intervention. The main research questions concern whether the intervention can reduce smartphone use in students, whether planning is effective in this regard, whether the intervention positively affects students' academic performance (e.g., concentration, perceived performance, grades), and whether the intervention enhances students' well-being (e.g., increased positive and decreased negative affect, lower anxiety). Furthermore, possible moderating (e.g., smartphone dependence, FoMO) and mediating variables (e.g., exam preparation-related flow, smartphone usage time, used mobile applications) are examined.
METHOD. Students are to develop action plans (BCT 1.4; plans on how to reduce smartphone use during exam phases) and coping plans (BCT 1.2; plans on how to uphold reduced smartphone use during exam phases despite potential stressors or urges). The relevant variables are assessed over the course of 5 measurement points (t1-t3 take place on a weekly basis, t4 takes place after the last exam, t5 takes place 2 months after t4). Furthermore, smartphone use (smartphone use time, used mobile applications) is objectively measured via a mobile application.
详细描述
Smartphones have become integral parts of students' everyday life. Research has shown that students excessively use their smartphones during semester times, in lectures, and while studying and that their smartphone use seldomly serves educational purposes. Unsurprisingly, smartphone interferences within such academically relevant situations can impair students' performance. For instance, it has been shown that students are more distracted, experience less study-related flow, evaluate their own performance more negatively, and achieve lower grades when engaging with their smartphones in academic contexts. Besides these performance-related downsides, research also suggests that smartphone use can impair students' well-being. Excessive use of smartphones and social media applications has been linked to various well-being-related issues such as negative affect, stress, and anxiety. As students have been identified as a high-risk group prone to smartphone overuse and smartphone addiction, they should be particularly susceptible to such well-being-related consequences.
The overall goal of all institutions of higher education must be the promotion of students' academic success as well as students' well-being as these two interrelated factors act as important predictors for both individual and public health and functioning. Consequently, while it is valuable to examine the negative effects of smartphone use on performance and well-being in academic contexts and understand their underlying processes, it is just as important to explore possible interventions to mitigate such negative outcomes. Here, it is necessary to answer questions regarding the effectiveness of such interventions (e.g., smartphone abstinence) on a variety of outcome variables and incorporate possible mediating or moderating influences relevant to the effects of such interventions on students' performance and well-being. Unfortunately, intervention studies in this regard are scarce. Yet, existing research indicates inconsistent findings. In fact, there is some evidence that short separation phases from smartphones result in higher anxiety levels. Moreover, phases of smartphone and social media abstinence appear to go along with smartphone cravings and potential overuse after the intervention is over. However, some studies found promising effects of separation phases on well-being, life satisfaction, procrastination, perceived stress or depression. A first study that investigated separation phases from smartphones among students revealed positive effects on individual well-being and performance by enhancing personal lifestyle, health, and academic management and reducing smartphone overuse. Yet, such intervention studies are extremely limited and need to be studied more rigorously. Especially moderating or mediating variables need to be taken into account to explain the effectiveness of smartphone abstinence interventions. In this light, smartphone addiction and fear of missing out (FOMO) seem to play an important role concerning the detrimental effect of smartphone abstinence on well-being. Finally, existing studies have mainly focused on the effects of smartphone separation phases lasting several hours or even days. As these are rather unrealistic settings, future interventions should be designed in ways that integrate pauses from smartphone use into people's everyday life.
Consequently, the present study aims at investigating the effectiveness of an intervention in which students are to develop action plans (BCT 1.4; ) as well as coping plans (BCT 1.2) allowing them to study without smartphone interferences. Planning is a very simple strategy with impressive effects, as indicated by medium to large effect sizes on behavior observed across various populations and behaviors. During a planning intervention, an individual is linking a situational cue (when/where) to an intended behavioral response (how) by mental simulation of anticipated situations. Thus, the goal is to link a specific cue to an intended action in order to translate goal intentions into behavior. In addition, planning is often complemented by coping planning (anticipation of barriers and the formation of plans on how to overcome them). In this study, individuals are to complete a planning sheet that contains both action and coping plans to restrict their own smartphone use during learning periods.
The measured outcomes include a variety of performance- (i.e., ability to concentrate, perceived learning achievement, exam grade, exam-related stress) and well-being-related variables (e.g., positive and negative affect, anxiety, subjective well-being). Furthermore, in this study, the mediating role of variables sought to be promoted through the intervention (i.e. decreased daily smartphone use, decreased daily use of social media applications, increased exam preparation-related flow) and possible moderators (i.e. smartphone addiction, FoMO) are also investigated.
The aims of the present study are threefold. First, the effectiveness of planning a separation from the smartphone during an exam phase is compared against a control group on a device-based assessment of smartphone use. Besides this first main aim, it is also aimed at specifically comparing the effectiveness of the planning intervention to a control group on academic performance and well-being among students. Third, this study examines the assumed underlying mechanisms as well as possible moderators of the planning intervention.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Prevention
- 盲法
- Single (Participant)
入排标准
- 年龄范围
- 16 Years 至 —(Child, Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Students from universities and universities of applied science
- •At least one written or oral exam during the data collection period
- •Ownership of an Android smartphone
- •Daily usage of the smartphone
- •Experience of distractions due to the smartphone during exam phases
- •At least 16 years of age
- •At least good German language skills
排除标准
- •Withholding consent to the data security regulations
- •Withholding consent to the installation of the study application
- •Students who are currently being treated for exam anxiety
研究组 & 干预措施
Intervention Group
Intervention points in time include:
- Baseline measure
- Installation of the study app
- Advice on general enhancements regarding study environment and behavior (BCT 4.1)
- Students are to develop up to three action plans (BCT 1.4) and coping plans (BCT 1.2) to reduce smartphone interference during exam preparation periods by putting the smartphone away
- Students receive weekly questionnaire (t1-t3) and one questionnaire after their first exam (t4). All these questionnaires concern their academic performance and well-being. A short questionnaire (t5) asks for the participants' exam grades approx. 2 months after their exam. A time period of 2 months has been chosen to ensure that universities have enough time to announce the grades.
- During the whole period of the study, the mobile application tracks the students' smartphone behavior (i.e., daily smartphone use, daily screen activations, and specific app usage).
干预措施: Smartphone Use Reduction in Academic Context (Behavioral)
Control Group
Control points in time include all parts except for number 4. Here students in the control group will receive questionnaires on general health behavior in order to achieve an equal questionnaire completion time compared to the intervention group.
干预措施: Control (Behavioral)
结局指标
主要结局
Subjective measure of well-being: Subjective well-being
时间窗: Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline)
Changes in students' subjective well-being will be assessed through subjective self-report measures. Measure: WHO-5 Well-being-Index; score: 1 \[never\] to 6 \[all the time\]).
Objective measure of smartphone use
时间窗: Continuously from time point 1 (baseline) through time point 2 (1 weeks after baseline), time point 3 (2 weeks after baseline) to time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline)
The daily smartphone use will be assessed via the mobile application Murmuras measuring daily smartphone use in minutes and specific application use concerning the 10 most used applications.
Subjective measure of academic performance: Ability to concentrate
时间窗: Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline)
Changes in students' ability to concentrate will be assessed through subjective self-report measures. Measure: LIST; Inventory for assessing learning strategies in students; score: 1 \[not at all agreed\] to 5 \[completely agreed\]).
Subjective measure of academic performance: Experienced study-related stress
时间窗: Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline)
Changes in students' experienced study-related stress will be assessed through subjective self-report measures. Measure: Self-developed based on STQL-S; Stress coping and quality of life in students; score: 1 \[not at all\] to 5 \[extremely\]).
Subjective measure of academic performance: Perceived learning achievement
时间窗: Time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline)
Students' perceived learning achievement will be assessed through subjective self-report measures. Measure: Self-developed. Measure: Self-developed; score: 1 \[not at all agreed\] to 6 \[completely agreed\]).
Subjective measure of academic performance: Exam grades
时间窗: Time point 5 (2 months after final exam in the current semester)
Students' exam grades will be assessed through subjective self-report measures. Measure: Self-developed.
Subjective measure of well-being: Positive and negative affect
时间窗: Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline)
Changes in students' positive and negative affect will be assessed through subjective self-report measures. Measure: PANAS; Positive and negative affect schedule; score: 1 \[not at all\] to 5 \[extremely\]).
Subjective measure of well-being: Anxiety
时间窗: Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline)
Changes in students' anxiety will be assessed through subjective self-report measures. Measure: PSS; Perceived stress scale - German version; score: 1 \[never\] to 5 \[very often\]).
次要结局
- Subjective measure of moderating variables: Fear of missing out(Time point 1 (baseline))
- Subjective measure of mediating variables: Individual action planning(Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline))
- Subjective measure of moderating variables: Smartphone dependence(Time point 1 (baseline))
- Subjective measure of mediating variables: Individual coping planning(Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline))
- Subjective measure of mediating variables: Exam preparation-related flow(Time point 1 (baseline), time point 2 (1 week after baseline), time point 3 (2 weeks after baseline), time point 4 (after final exam in the current semester, approx. 4 - 6 weeks after baseline))
研究者
Theda Radtke
Prof. Dr.
University of Witten/Herdecke
