🧠AP Psychology
Using the source provided, respond to all parts of the question.
1. Your response to the question should be provided in six parts: A, B, C, D, E, and F. Write the response to each part of the question in complete sentences. Use appropriate psychological terminology in your response.
Identify the research method used in the study.
State the operational definition of evening screen exposure in the study.
Describe the relationship between evening screen exposure and sleep efficiency as indicated by the correlation coefficient.
Identify one ethical guideline described in the study. Describe one way the researchers in the study applied this ethical guideline.
Explain the extent to which the research findings may or may not be generalizable to all adolescents using specific and relevant evidence from the study.
Explain how the research findings support or refute the concept of the role of melatonin in the sleep-wake cycle.
Source
This study investigated how evening screen exposure relates to sleep quality and academic outcomes in adolescents over an extended developmental period. Building on previous research suggesting that blue light exposure disrupts circadian rhythms and melatonin regulation, researchers sought to determine whether habitual evening screen use predicts changes in sleep efficiency and subsequent academic performance across two years of high school.
Total N: 342
Recruitment: Participants were recruited from three large urban and suburban school districts through informational sessions held during parent-teacher conferences and school assemblies. Students who expressed interest were screened for eligibility, which required ownership of at least one personal electronic device and no pre-existing diagnosed sleep disorders. The study followed participants across four assessment waves spanning 24 months, with data collection occurring at baseline (fall semester of Year 1), 6 months, 12 months, and 24 months. Of the initial 342 participants enrolled at baseline, 298 completed the 24-month assessment, representing an attrition rate of 12.9%. Primary reasons for dropout included family relocation (n = 22), withdrawal of consent (n = 14), and inability to contact (n = 8).
Gender: 51.2% female, 47.1% male, 1.7% non-binary or other gender identity¹
Race/Ethnicity: 42.4% White, 28.1% Hispanic/Latino, 18.4% Black/African American, 7.6% Asian, 3.5% multiracial or other
Age Range: 14-18 years
Age Mean: 15.8
Age SD: 1.2
Compensation: Participants received a $25 gift card at each assessment wave, with a $50 bonus for completing all four waves
Actiwatch Spectrum Plus wrist-worn actigraphy devices for continuous sleep monitoring
ScreenTime tracking application installed on participants' primary devices (smartphones, tablets, computers)
Demographic and health history questionnaire
Sleep diary for supplementary self-report data
Academic records release forms for GPA verification
At baseline, researchers obtained written parental informed consent and participant assent during individual enrollment sessions at each school site; researchers explained the study's purpose, procedures, potential risks, and emphasized participants' right to withdraw at any time without penalty.
Participants completed demographic questionnaires and were fitted with actigraphy devices, receiving instructions to wear them continuously for 14-day monitoring periods at each assessment wave.
The ScreenTime tracking application was installed on participants' primary electronic devices to automatically log daily screen use duration specifically after 8:00 PM, with data syncing to a secure research server.
At each of the four assessment waves (baseline, 6 months, 12 months, and 24 months), participants underwent the same 14-day actigraphy monitoring period and concurrent screen time tracking.
Research assistants contacted participants weekly via text message during monitoring periods to ensure device compliance and address technical issues, serving as a retention strategy.
Academic records were obtained directly from school registrars at the end of each semester to calculate cumulative GPA at each time point.
At the 12-month and 24-month follow-ups, participants and parents were asked to reaffirm their consent to continue participation, ensuring ongoing informed consent throughout the study.
All data were de-identified using participant ID codes, with the linking key stored separately in an encrypted file accessible only to the principal investigator.
Sleep Efficiency Score was measured as the percentage of time spent asleep relative to the total time spent in bed, calculated using the Actiwatch Spectrum Plus algorithm that analyzes wrist movement patterns during each 14-day monitoring period. Specifically, the actigraphy device recorded movement in 30-second epochs throughout the night, classifying each epoch as 'sleep' or 'wake' based on validated activity thresholds. The Sleep Efficiency Score was computed by dividing total sleep time (sum of sleep epochs) by total time in bed (from initial sleep attempt to final awakening) and multiplying by 100 to yield a percentage score ranging from 0-100%, with higher scores indicating more efficient sleep with fewer nighttime awakenings.
Parental informed consent and participant assent were obtained from all families prior to enrollment, as required for research involving minors. Parents signed detailed consent forms explaining the study's longitudinal nature, data collection procedures, and privacy protections, while adolescent participants signed age-appropriate assent forms indicating their voluntary agreement to participate. Additionally, ongoing consent was reaffirmed at the 12-month and 24-month assessments, and all participants were reminded of their right to withdraw from the study at any time without consequence.
Longitudinal analysis revealed that as participants increased their evening screen exposure over the 24-month study period (from M = 98.4 minutes at baseline to M = 142.6 minutes at 24 months), their sleep efficiency scores correspondingly decreased (from M = 87.2% to M = 76.8%). The negative correlation between evening screen minutes and sleep efficiency strengthened over time, growing from r = -.52 at baseline to r = -.71 at the 24-month assessment, indicating a strong negative relationship. Concurrent with declining sleep efficiency, cumulative GPA showed a moderate decrease from M = 3.21 to M = 2.89, with sleep efficiency demonstrating a moderate positive correlation with GPA that also strengthened across assessment waves (r = .31 to r = .44).
Variable | Baseline (N=342) | 6 Months (N=328) | 12 Months (N=314) | 24 Months (N=298) |
|---|---|---|---|---|
Evening Screen Minutes (M) | 98.4 | 112.7 | 128.3 | 142.6 |
Evening Screen Minutes (SD) | 34.2 | 38.5 | 41.8 | 45.3 |
Sleep Efficiency Score % (M) | 87.2 | 84.1 | 80.6 | 76.8 |
Sleep Efficiency Score % (SD) | 6.8 | 7.4 | 8.9 | 10.2 |
Cumulative GPA (M) | 3.21 | 3.14 | 3.02 | 2.89 |
Cumulative GPA (SD) | 0.58 | 0.61 | 0.67 | 0.72 |
Correlation: Screen Minutes & Sleep Efficiency² | r = -.52 | r = -.58 | r = -.64 | r = -.71 |
Correlation: Sleep Efficiency & GPA | r = .31 | r = .36 | r = .41 | r = .44 |
These longitudinal findings demonstrate that increased evening screen exposure is associated with progressively declining sleep efficiency across adolescent development, with downstream implications for academic achievement. The results align with research on circadian rhythms and melatonin regulation, which suggests that blue light emitted from electronic screens suppresses the pineal gland's production of melatonin—the hormone responsible for signaling sleepiness and regulating the sleep-wake cycle. As adolescents in this study increased their evening screen use over time, the chronic disruption to their natural circadian rhythms likely impaired their ability to fall asleep quickly and maintain consolidated sleep throughout the night, ultimately manifesting in reduced sleep efficiency scores and associated academic difficulties. However, because this sample was drawn exclusively from urban and suburban school districts, these findings may not generalize to adolescents in rural populations, where lifestyle factors and screen access patterns may differ substantially, nor to older adult populations whose circadian rhythm functioning differs developmentally.
Martinez, K. L., Chen, R. J., & Thompson, A. D. (2023). Evening screen exposure and sleep efficiency trajectories in adolescents: A 24-month longitudinal study. Journal of Adolescent Health Psychology, 48(3), 267-284. https://doi.org/10.1037/jahp0000892
- Gender categories reflect participants' self-identification at baseline. The terminology used in this study follows current APA guidelines for inclusive reporting of gender identity in psychological research.
- Actigraphy refers to the use of a small, wearable device that monitors movement patterns to objectively assess sleep-wake cycles. The correlation coefficients reported (r values) indicate the strength and direction of the relationship between variables, with values closer to -1.0 indicating stronger negative relationships.
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