| Course | PS 323 Psychology of Gender |
|---|---|
| Unit | Unit 6 |
| Paper type | Gender and health paper |
| Length | About 1,020 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | BS in Psychology |
| Updated | October 2026 |
Free sample paper for PS 323 Unit 6
Twice as Common From Adolescence On: A Gender and Health Paper Separating What Representative Data Show About Depression From What Has Been Proposed to Explain It
Student Name
Psychology, Herzing University
PS 323: Psychology of Gender
Instructor Name
August 11, 2026
Twice as Common From Adolescence On: A Gender and Health Paper Separating What Representative Data Show About Depression From What Has Been Proposed to Explain It
Two Questions, Kept Apart
This paper examines one health outcome, depression, and keeps two questions separate throughout. The first is what the data show about differences between women and men. The second is what has been proposed to explain those differences. Each finding is reported with its population and period, and each explanation is attributed to the research behind it. The paper does not settle a cause, and it contains no information that could be used to identify or assess depression in any person.
What the Data Show
The most comprehensive recent evidence comes from Salk et al. (2017), who conducted two meta-analyses using only nationally representative samples, which avoid the bias of studying people who happen to seek treatment. For diagnoses of major depression, they combined data from 65 articles and their national data sets, covering about 1.7 million people; for depression symptoms, 95 articles covering about 1.9 million people; together the data came from more than ninety nations.
For diagnoses, women were about twice as likely as men to meet criteria for major depression, an odds ratio of 1.95. For symptoms, the average difference was d = 0.27, a small-to-moderate difference in the number or severity of symptoms reported. Age was the strongest influence on the size of the difference. The gender difference in diagnoses was already present at age twelve, earlier than previous research had suggested, and it peaked in early-to-middle adolescence, with an odds ratio of about 3.0 at ages thirteen to fifteen. After adolescence the difference declined and then remained stable through adulthood. The authors also noted that, given the size of the difference, depression in men should not be overlooked.
Why the Choice of Samples Matters
The decision by Salk et al. (2017) to include only nationally representative samples is the main reason their estimates are more trustworthy than figures drawn from clinics. People who reach treatment differ from people who do not, and the difference is itself related to gender if women seek help more readily, so treatment records could exaggerate the gap. Representative surveys sample people whether or not they have ever sought care and assess them in the same way. That design does not remove every problem, since surveys rely on people's answers to structured questions and those answers may be shaped by how comfortable people are describing their feelings. But it removes the largest source of bias in earlier figures and allows comparisons across age groups and countries using similar methods.
What an Odds Ratio of About Two Means
An odds ratio near two describes a large relative difference in how often a diagnosis is met. It does not describe how common depression is overall, and it says nothing about whether any particular woman or man is affected. A difference can be large in relative terms while most people in both groups never meet criteria. The symptom measure, with its small-to-moderate effect size, shows that the underlying distributions of reported symptoms overlap substantially.
A Finding That Complicates Simple Explanations
Salk et al. (2017) also compared nations. For diagnoses of major depression, the gender difference was larger in nations with greater gender equity, though this pattern did not appear for symptoms. The finding is surprising if one expects inequality alone to produce the difference, and it is a reminder that cross-national comparisons can be shaped by differences in how depression is diagnosed, reported and recorded across countries.
What Has Been Proposed to Explain It
Artifact explanations
One early possibility was that the difference is not real but reflects reporting: that women are more willing to report distress or seek help. Nolen-Hoeksema (1987) reviewed this possibility and concluded that differences in reporting and help seeking did not account for the difference, in part because it appeared in community samples as well as in treatment records. The use of representative samples by Salk et al. (2017) addresses the same concern.
Response styles
Nolen-Hoeksema (1987) proposed that the difference arises partly from how people respond to low mood: on average, women were more likely to focus repetitively on their distress and its causes, which she called rumination, while men were more likely to distract themselves. Rumination was associated with longer and more severe low moods in her review of the evidence. This is a social and cognitive explanation, and it links the difference to learned patterns of responding.
Integrative accounts
Hyde et al. (2008) proposed an integrative model combining affective factors such as emotional reactivity and temperament, biological factors such as genetic vulnerability and pubertal hormones, and cognitive factors such as rumination and negative thinking styles, all interacting with stressful life events, which girls report more often in adolescence. The model was built to explain why the difference emerges in early adolescence, the period Salk et al. later identified as its peak. Its biological component is presented as one strand among several, interacting with experience, not as a cause on its own. That framing matters for anyone writing about this area, because describing hormones or genes as the reason for the difference would claim more than the model or its evidence supports.
What the Paper Does Not Settle
The evidence supports a reliable difference, emerging around puberty and largest in adolescence. It supports some explanations, such as rumination, more than others, such as reporting artifacts. It does not settle how much each proposed factor contributes, and the integrative model is designed to say that several do. Nothing here describes any individual. The difference is an average across millions of people; most women do not experience major depression, and many men do.
Sources and Personal Experience
Prevalence figures should come from representative surveys or meta-analyses of them, not from clinic records or news reports, because those reflect who seeks care. Writing about one's own diagnosis is not appropriate in this paper; the subject is group data, and personal health information is better kept private. Anyone concerned about their own mood is best served by talking with a health care provider.
References
Hyde, J. S., Mezulis, A. H., & Abramson, L. Y. (2008). The ABCs of depression: Integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychological Review, 115(2), 291-313. https://doi.org/10.1037/0033-295X.115.2.291
Nolen-Hoeksema, S. (1987). Sex differences in unipolar depression: Evidence and theory. Psychological Bulletin, 101(2), 259-282. https://doi.org/10.1037/0033-2909.101.2.259
Salk, R. H., Hyde, J. S., & Abramson, L. Y. (2017). Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychological Bulletin, 143(8), 783-822. https://doi.org/10.1037/bul0000102
What the PS 323 Unit 6 instructions ask for
Unit 6 of PS 323 asks students to examine one health outcome while keeping data and explanation separate. Expect to report each finding with its population and period, attribute biological and social explanations to the research behind them, and avoid settling a cause the evidence does not settle. Prevalence figures should come from representative surveys or meta-analyses of them rather than clinic records or news reports. Biology can be discussed without determinism by presenting it as one interacting factor, as integrative models do. Writing about a condition you have been diagnosed with is not appropriate for this paper; keep personal health information private. A paragraph explaining why the sample is representative is a useful addition.
Inside the PS 323 Unit 6 example
The paper states its two questions and its limits first. A data section reports Salk and colleagues' two meta-analyses with their samples, odds ratio, effect size and age pattern. A section explains why representative sampling makes these estimates more trustworthy, and another explains what an odds ratio near two does and does not mean. The cross-national finding is reported as a complication. Explanations follow under attributed headings: artifact explanations and Nolen-Hoeksema's conclusion about them, her response-style account, and the integrative model by Hyde and colleagues. The close states what is not settled and how to source prevalence figures. Every finding names the population it describes, and every explanation names the researchers who proposed it.
PS 323 Unit 6 rubric: what full points look like
The rubric for the gender and health paper generally rewards findings reported with population and period, separation of data from explanation, attributed explanations, careful treatment of biology and responsible writing about health. Findings earn credit when samples and effect sizes are given. Separation is often the most heavily weighted criterion, since the unit is built around it. Attributed explanations score when each is linked to its source. Biology earns points when presented as one interacting factor rather than a single cause. Responsible writing is credited when the paper avoids information that could be used to assess individuals. Explaining why representative samples are preferred to clinic records is often credited as methodological insight.
Common PS 323 Unit 6 mistakes, and how to avoid them
Health papers lose points when they mix findings with explanations so the reader cannot tell which is which. Another common weakness is citing prevalence from clinics or news reports. Students often present hormones or genes as the cause of a difference. Some dismiss differences as reporting artifacts without checking the research on that question. Others write about their own diagnosis. Including symptom lists or anything resembling a screening tool is outside the scope of this unit. Forgetting to note that depression in men also matters is a further imbalance. Using an odds ratio as if it described how common a condition is overall is a related misunderstanding. Treating cross-national differences as simple evidence about inequality ignores differences in how diagnoses are made and recorded.
Get a PS 323 Unit 6 example written to your instructions
Share the Unit 6 instructions and the PS 323 rubric from your classroom, along with the outcome or condition the assignment names. We write a custom example that reports the rates with population and period, formats both kinds of explanation alike, and keeps documented findings apart from proposed mechanisms. First custom sample free, returned in 24 to 48 hours.
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PS 323 Unit 6 questions, answered
Where should the prevalence figures come from?
Published epidemiological sources and peer-reviewed studies, cited with their release year. National statistical agencies and public health bodies publish the underlying data, and your library databases carry the studies that analyze it. Avoid figures that reach you through a news article or an advocacy page, because those are usually rounded, re-framed or drawn from a release that has since been updated.
How do I write about biology without sounding deterministic?
Keep the verbs on the research. A sentence reporting that a study proposed a mechanism and tested it in a named sample describes work that was done; a sentence saying a group is biologically predisposed states a conclusion the study did not reach. State the measure, the sample and the authors' own conclusion, then let the reader see the distance between them.
Can I write about a condition I have been diagnosed with?
Write about the literature, not the chart. Your diagnosis, your test results and anything a clinician has recorded belong to a file with protections a graded paper does not have, and an instructor reading coursework has no standing to receive them. Lived familiarity with an area is a good reason to choose it; it is not evidence, and the paper still runs on cited sources.
Where can I find a free PS 323 Unit 6 sample paper?
A complete PS 323 Unit 6 gender and health paper appears here at no cost, with the representative data, attributed explanations and margin notes. Examining a different health outcome? Share the prompt and a paper built on representative data is drafted free.
How do I write about biology in PS 323 Unit 6 without sounding deterministic?
Present it as one factor interacting with others. The sample reports an integrative model in which pubertal hormones and genetic vulnerability combine with stress and thinking styles.