Southern New Hampshire University PSY 322 Adolescent Development, 5-3 Final Project Milestone Three: Critical Literature Review
Compose a two- to four-page critical literature review, roughly 600 to 1,000 words, evaluating two peer-reviewed empirical research articles related to your approved adolescent development topic. Southern New Hampshire University positions Milestone Three in Module Five as the critical scholarly foundation for the PSY 322 final project submission, weighted in the course grading architecture as a core formative milestone graded against an analytical four-tier rubric.
A Critical Literature Review
[Student Name]
Southern New Hampshire University
PSY 322: Adolescent Development
[Instructor Name]
[Submission Date]
| ADOLESCENT DIGITAL MEDIA AND WELL-BEING |
Adolescent digital media use has become a developmental concern because online interaction forms part of ordinary peer life. Researchers disagree about whether screen duration has a meaningful association with psychological well-being. The two empirical studies reviewed here support a qualified position: average associations are small, but increases in particular activities may coincide with higher depressive symptoms. Orben and Przybylski (2019) test the stability of associations across three large datasets; Boers et al. (2019) follow annual changes across four years. A reproducible Shapiro search uses Multi-Search and APA PsycINFO (EBSCO), with the terms “adolescent AND (digital technology OR screen time) AND (well-being OR mental health).” Apply peer-reviewed, English-language, empirical-research, and 2018–2026 filters. Publisher and PubMed/PMC records confirm the article metadata and original study designs; full-text access should be confirmed through the authenticated Shapiro account.
Article One Evaluation
Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3(2), 173–182. https://doi.org/10.1038/s41562-018-0506-1
The study addresses concern that digital technology reduces adolescent well-being. It reanalyses three nationally representative datasets collected between 2007 and 2016: the U.S. Youth Risk Behavior Survey (YRBS; 74,814 students, mostly in grades 9–12), Monitoring the Future (MTF; 268,672 students in grades 8 and 10), and the U.K. Millennium Cohort Study (MCS; 11,872 cohort members, mainly ages 13–15). The combined analytic pool included 355,358 adolescents. The authors used dataset-specific self-report measures rather than one common instrument. YRBS included five items on mental health and suicidal ideation; MTF included a four-item depressive-symptom measure and Rosenberg self-esteem items; MCS included adolescent well-being and mood questions, plus caregiver-completed Strengths and Difficulties Questionnaire (SDQ) ratings.
Technology exposure also relied on survey questions whose wording and response scales differed across datasets. Specification curve analysis tested many defensible combinations of exposure, outcome, and control variables, reducing the risk that the result depended on one selected model. The negative associations remained small: digital technology use explained no more than 0.4% of variation in well-being. Large national samples and sensitivity analysis strengthen confidence in the estimate, but different measures limit construct equivalence and self-reported exposure invites recall error. The authors did not report one internal-consistency estimate for the many alternative composites. Cross-sectional analyses also leave prior symptoms, sleep, family stress, and peer relationships as possible confounders. Educators and counselors should assess online experiences alongside mood, sleep, bullying, and family context rather than treating total screen hours as a diagnosis.
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Boers, E., Afzali, M. H., Newton, N., & Conrod, P. (2019). Association of screen time and depression in adolescence. JAMA Pediatrics, 173(9), 853–859. https://doi.org/10.1001/jamapediatrics.2019.1759
Boers et al. (2019) examine whether different screen activities track changes in depressive symptoms during early adolescence. Their secondary analysis followed 3,826 students recruited from 31 schools in the Greater Montreal area; 1,798 (47%) were girls, and the mean starting age was 12.7 years (SD = 0.5). Adolescents completed confidential web surveys annually across four years, from Grade 7 onward. The research tested displacement, upward social comparison, and reinforcing-spirals explanations. Measures covered social media, television, video gaming, and general computer use through daily-use questions grouped into four ordinal categories: 0–30, 30–90, 90–150, and 210 minutes or more. Depressive symptoms were assessed with the seven-item depression subscale of the Brief Symptom Inventory (BSI).
The researchers also used the 10-item Rosenberg Self-Esteem Scale, a weekly exercise-frequency question, the Family Affluence Scale for Adolescents, and demographic items for age, sex, and school. Multilevel models estimated between-person differences and within-person yearly changes, with random intercepts and slopes at student and school levels; models adjusted for sex and socioeconomic status. A one-category increase in social media use within a given year was associated with a 0.41-point increase in depressive symptoms (95% CI [0.32, 0.51]); television use showed a smaller within-person association of 0.18 points (95% CI [0.09, 0.27]). Video gaming showed no significant association. Repeated measurement and multilevel analysis offer stronger temporal evidence than a single survey, and the BSI and Rosenberg scales have established use in adolescent samples. The authors describe the measures as reliable but do not report sample-specific reliability coefficients. Screen exposure itself was not randomized, so the study cannot establish that screen use caused symptom change. Broad time categories did not capture content, platform, or social purpose; self-report invites recall error, and the Montreal school sample may not represent other regions or clinical settings. Counselors can ask whether online comparison, conflict, or mood changes accompany increased social media use without assuming that every screen activity carries the same risk.
Integrative Methodological Comparison
The studies differ in scale and design, but their findings do not necessarily conflict. Orben and Przybylski estimate a small average association across broad populations and multiple operational definitions; Boers et al. identify modest within-person links for social media and television in one regional cohort. A small population-level association can coexist with stronger associations for particular adolescents, media types, or periods. Neither investigation measured online content in enough detail to explain why an adolescent used a platform. Nesi et al. (2018) argue that social media changes peer interaction through visibility, permanence, and quantifiable feedback, which helps explain why exposure time alone may miss relevant experiences. Odgers and Jensen (2020) report that the wider evidence contains small, inconsistent associations and limited causal certainty. An umbrella review of 25 reviews found that most reviews described links between social media and adolescent mental health as weak or inconsistent (Valkenburg et al., 2022).
Bronfenbrenner’s ecological systems theory offers a useful developmental interpretation: digital activity sits within adolescents’ peer and family microsystems and interacts with school, community, and wider cultural influences (Bronfenbrenner, 1979). Supportive online messages may strengthen connection, whereas cyberbullying or constant social comparison may increase distress. The evidence supports individualized screening and school responses that consider content, relationships, sleep, and existing symptoms. It does not support the claim that screen time alone causes adolescent depression. Digital media forms part of a wider developmental context in which risk and support depend on the adolescent and the circumstances of use.
| ADOLESCENT DIGITAL MEDIA AND WELL-BEING |
Boers, E., Afzali, M. H., Newton, N., & Conrod, P. (2019). Association of screen time and depression in adolescence. JAMA Pediatrics, 173(9), 853–859. https://doi.org/10.1001/jamapediatrics.2019.1759
Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Harvard University Press.
Nesi, J., Choukas-Bradley, S., & Prinstein, M. J. (2018). Transformation of adolescent peer relations in the social media context: Part 1-A theoretical framework and application to dyadic peer relationships. Clinical Child and Family Psychology Review, 21(3), 267–294. https://doi.org/10.1007/s10567-018-0261-x
Odgers, C. L., & Jensen, M. R. (2020). Annual research review: Adolescent mental health in the digital age: Facts, fears, and future directions. Journal of Child Psychology and Psychiatry, 61(3), 336–348. https://doi.org/10.1111/jcpp.13190
Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3(2), 173–182. https://doi.org/10.1038/s41562-018-0506-1
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Valkenburg, P. M., Meier, A., & Beyens, I. (2022). Social media use and its impact on adolescent mental health: An umbrella review of the evidence. Current Opinion in Psychology, 44, 58–68. https://doi.org/10.1016/j.copsyc.2021.08.017
Assessment Context
Southern New Hampshire University structures PSY 322 Adolescent Development as an exploration of normative and non-normative biological, cognitive, social, and emotional development across the adolescent lifespan into emerging adulthood. Milestone Three follows the Milestone One topic selection and the Milestone Two annotated bibliography, demanding that students shift from merely listing sources to conducting a methodical evaluation of quantitative or qualitative research designs. Course materials, grading guides, and submission dropboxes reside within Brightspace, so this brief extrapolates from the published undergraduate curriculum guidelines and syllabi across the social sciences at SNHU. The critical review serves as an academic reality check: it requires students to look behind an author’s assertions, inspect sample characteristics, identify methodological limitations, and assess whether conclusions genuinely inform youth development practitioners. The review directly prevents common analytical errors before students draft their comprehensive final project synthesis.
Students regularly face deductions on Milestone Three for two predictable reasons. Learners often write a purely descriptive article abstract rather than an analytical critique, leaving the author’s research instruments and operational definitions unexamined. Submissions also tend to omit the specific clinical or classroom application, failing to connect developmental theory directly to real-world adolescent environments.
Learning Outcomes Assessed
- Demonstrate the capacity to critique empirical methodology, data collection instruments, and statistical claims within peer-reviewed adolescent development literature.
- Differentiate between correlational associations and causal trajectories in adolescent cognitive, behavioural, and psychosocial research.
- Connect published developmental findings directly to Bronfenbrenner’s ecological systems framework, Piagetian cognitive development, or Eriksonian identity consolidation.
- Evaluate research limitations, including retrospective reporting biases, non-representative sampling, and uncontrolled environmental variables.
- Apply current APA 7th edition formatting to citations, references, headings, and statistical notations.
Task Instructions
- Access the Shapiro Library and locate two empirical, peer-reviewed journal articles published within reputable psychological journals addressing your approved PSY 322 adolescent topic.
- Confirm that both selected sources feature original empirical investigations with stated hypotheses, distinct participant sample sizes, clearly defined instruments, and explicit statistical or qualitative findings, rather than theoretical essays or literature summaries.
- Organise your review into discrete sections for each article, followed by an integrated developmental synthesis comparing the methodological rigor of the investigations.
- Provide the complete APA 7th edition citation at the opening of each article section.
- Identify the repository or database origin within the Shapiro Library, stating the exact search criteria and filters that established the credibility and validity of the source.
- Define the precise developmental problem or clinical issue under investigation, justifying why the research represents a substantial concern within adolescent psychology.
- Examine the empirical methodology: detail the participant sample demographics, name every psychometric assessment or measurement instrument utilized, and summarize the key statistical outcomes.
- Critique the study’s construct validity and internal consistency: assess whether the research instruments accurately measured the targeted developmental constructs and identify specific variables the researchers failed to control.
- Formulate actionable takeaways explaining how the empirical conclusions inform secondary school educators, adolescent counselors, or child welfare practitioners.
- Identify at least two distinct limitations acknowledged by the investigators or revealed through your critical reading, such as reliance on self-report surveys, small sample sizes, or demographic homogeneity.
- Conclude with an integrative synthesis comparing how the two studies collectively deepen understanding of your adolescent development topic.
Structural Requirements by Section
- Article One Evaluation. Header in APA level 2. Complete citation, research justification, database provenance, detailed breakdown of participants, instruments, data collection procedures, statistical conclusions, methodological strengths, weaknesses, and practitioner relevance.
- Article Two Evaluation. Header in APA level 2. Mirror the analytical architecture of Article One, focusing on comparative measurement differences or distinct methodological approaches to the developmental problem.
- Integrative Methodological Comparison. Header in APA level 2. Minimum of two substantive paragraphs synthesizing the findings, evaluating conflicting conclusions, and stating what the combined research establishes regarding adolescent outcomes.
- References Page. Dedicated final page featuring full APA 7th edition bibliographic entries with permanent DOIs.
Document Specifications and Academic Authenticity
- Page count: Two to four double-spaced pages of narrative text, excluding the title page and references page.
- Font and Margins: 12-point Times New Roman or 11-point Calibri; standard one-inch margins on all sides.
- Running Head and Page Numbers: Professional APA header formatting with page numbers right-aligned in the top margin.
- Direct Quotes: Quotations must not exceed 10 percent of the total word count; prioritize paraphrasing accompanied by author-year in-text citations.
- Academic Integrity: Upload the completed document as a Microsoft Word (.docx) file directly to the Module Five Brightspace dropbox; submissions pass through Turnitin, where unoriginal phrasing or unverified citations will trigger an academic integrity inquiry under SNHU university policy.
Marking Criteria and Rubric Architecture
| Critical Element | Exemplary (100%) | Proficient (85%) | Needs Improvement (55%) | Not Evident (0%) |
|---|---|---|---|---|
| Background and Empirical Scope (20%) | Provides an exhaustive overview of the research problems, detailing specific empirical participant cohorts, data collection instruments, and statistical models. | Explains the research problem, participants, and instruments used in both articles with minor descriptive gaps. | Mentions general research context but glosses over participant demographics, data instruments, or methodology. | Fails to describe empirical background, sample characteristics, or research instruments. |
| Theoretical and Course Relevance (20%) | Demonstrates profound comprehension of developmental theory, explicitly linking empirical variables to adolescent cognitive, emotional, or social development models. | Links the research to relevant course concepts and adolescent developmental milestones effectively. | Attempts to connect findings to developmental theory, but relationships remain superficial or mischaracterized. | Omits discussion of theoretical grounding or adolescent developmental relevance. |
| Critique of Strengths and Limitations (30%) | Delivers a rigorous critique identifying methodological strengths, validity threats, confounding variables, and specific sampling limitations for both studies. | Critiques the articles by identifying recognizable strengths and at least two distinct limitations. | Provides a superficial critique focused on writing style or general opinions rather than methodological rigor. | Offers no critique of research validity, methodology, or study limitations. |
| Practitioner Application (15%) | Translates empirical findings into actionable, evidence-based recommendations for educators, clinicians, or adolescent advocates. | Suggests logical practical applications of the study findings for individuals working with adolescents. | Mentions practical use in vague terms without practical implementation details. | Fails to articulate any practical or clinical application of the findings. |
| Articulation of Response and APA Formatting (15%) | Crafts clear, highly disciplined prose free of mechanical errors, using flawless APA 7th edition formatting, active voice, and verifiable DOIs. | Writes clearly with minor grammatical slips and generally accurate APA citations. | Contains recurring grammatical errors, mechanical flaws, or significant APA formatting errors. | Exhibits severe mechanical errors or pervasive APA non-compliance that obstructs comprehension. |
Example Student Response
Evaluating empirical investigations requires moving past public assumptions to inspect the exact measurement tools that researchers deploy. Orben and Przybylski investigate adolescent psychological well-being across three distinct social datasets comprising 355,358 total participants, examining whether time spent using digital screens correlates with measured decrements in life satisfaction. Traditional surveys frequently deploy selective statistical configurations that inflate minor associations into dramatic public headlines. Applying specification curve analysis across thousands of plausible analytical models, the authors document that digital technology use explains at most 0.4 percent of the variance in adolescent well-being in The Association Between Adolescent Well-Being and Digital Technology Use (Orben & Przybylski, 2019). That statistical reality demonstrates that screen engagement shares roughly the same diminutive correlation with psychological distress as wearing eyeglasses or eating potatoes. Practitioners reviewing these outcomes must recognize that blanket restrictions on device duration fail to address the underlying psychological vulnerabilities driving maladaptive media use.
Investigating the qualitative and structural elements of online peer engagement shifts the empirical focus from duration to psychological mechanism. Nesi et al. establish a comprehensive transformation framework detailing how social media alters adolescent peer dynamics through seven distinct technological architectures, including asynchronicity, permanence, publicness, and quantifiability (Nesi et al., 2018). Screen time metrics treat all digital consumption as an identical exposure, yet passive scrolling produces distinct developmental outcomes compared to reciprocal interpersonal messaging. Empirical researchers repeatedly find that adolescent girls experiencing pre-existing depressive symptoms engage in heightened online co-rumination and appearance-focused social comparisons. Clinicians working with youth must evaluate the specific communicative affordances that adolescents activate rather than tallying daily device hours. Methodological designs that aggregate disparate online behaviours into a solitary hourly exposure measure mischaracterize the developmental reality of contemporary adolescent socialization.
Differential Susceptibility and Contextual Moderation
Adolescent media effects operate through individualized cognitive and social filters rather than universal causal mechanisms. Valkenburg and Peter (2013) formalized this transactional reality through the Differential Susceptibility to Media Effects Model, demonstrating that cognitive, emotional, and behavioral outcomes depend on dispositional traits, developmental milestones, and social environments. Pre-existing psychological vulnerabilities determine whether an adolescent processes digital communication as validating socialization or threatening exclusion. Longitudinal data confirm that well-adjusted adolescents leverage digital networks to consolidate friendships and satisfy basic psychological needs for relatedness. Conversely, adolescents navigating interpersonal trauma or developmental vulnerabilities experience amplified depressive symptoms when engaging with quantifiable peer feedback mechanisms. Methodological frameworks must account for these interactive predispositions to avoid flattening diverse adolescent cohorts into uniform statistics.
Common Analytical Pitfalls in Milestone Submissions
Undergraduate researchers working on Milestone Three frequently encounter critical deductions when completing their evaluation sections.
- Confusing cross-sectional surveys with longitudinal designs, attributing causal harm to digital media when the data merely demonstrate concurrent correlations.
- Neglecting sample demographics, generalizing findings gathered from small clinical populations to typical secondary school student bodies.
- Ignoring validated psychometric properties, accepting brief self-report questionnaires without checking whether the authors established construct validity.
- Failing to identify confounding variables, such as family socioeconomic stress, pre-existing anxiety, or disrupted sleep hygiene.
Addressing these issues requires a disciplined reading of each article’s methods section. Instructors expect students to name the exact measurement inventories employed, such as the Center for Epidemiologic Studies Depression Scale or the Rosenberg Self-Esteem Scale, rather than stating vaguely that researchers measured mental health. Inspecting how variables were measured reveals whether a study captured authentic developmental shifts or transient emotional states. Clear evaluations also note whether the investigators secured independent reports from parents and teachers or relied exclusively on adolescent self-reporting. Explicitly naming these methodological constraints marks the difference between basic summaries and professional psychological critique.
Synthesizing Empirical Contradictions for Practice
Resolving conflicting conclusions in the literature forms the highest level of scholarly critique in child and adolescent psychology. Large-scale population datasets identify minimal aggregate risks from digital technology exposure, while specialized clinical investigations document acute distress among vulnerable subgroups. Odgers and Jensen (2020) synthesize these competing empirical streams, concluding that digital technologies amplify offline vulnerabilities rather than generating novel epidemics of distress among healthy youth. Practitioners must abandon generic advice regarding total screen limits and instead conduct targeted assessments of each adolescent’s relational ecosystem. School psychologists should focus intervention resources on students demonstrating problematic social displacement, compulsive late-night engagement, or significant peer conflict online. Methodological critique leads directly to targeted, humane intervention models that protect vulnerable youth while preserving developmental opportunities for typical connection.
Final Position on the Task
Milestone Three establishes whether a student can interrogate scientific evidence before assembling a comprehensive adolescent development capstone. Completing this assignment successfully requires treating research studies as empirical investigations built from specific operational choices rather than unquestioned authority. Naming the participant sample, evaluating the psychometric reliability of the measurement instruments, and identifying unexamined confounding variables elevates a submission from a generic summary to a true psychological critique. APA formatting must remain accurate across all parenthetical citations, in-text attributions, and bibliographic entries to maintain professional credibility. Approaching both articles with methodical rigor ensures that the subsequent project synthesizes authentic developmental knowledge capable of supporting real-world youth interventions.
References
Nesi, J., Choukas-Bradley, S., & Prinstein, M. J. (2018). Transformation of adolescent peer relations in the social media context: Part 1—A theoretical framework and application to dyadic peer relationships. Clinical Child and Family Psychology Review, 21(3), 267–294. https://doi.org/10.1007/s10567-018-0261-x
Odgers, C. L., & Jensen, M. R. (2020). Annual research review: Adolescent mental health in the digital age: Facts, fears, and future directions. Journal of Child Psychology and Psychiatry, 61(3), 336–348. https://doi.org/10.1111/jcpp.13190
Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3(2), 173–182. https://doi.org/10.1038/s41562-018-0506-1
Southern New Hampshire University. (2024). PSY 322 Final project milestone three: Literature review guidelines and rubric. SNHU Academic Archive.
Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. Journal of Communication, 63(2), 221–243. https://doi.org/10.1111/jcom.12024
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