Overall Structure & Word Allocation
✅ Introduction → ~1/3 of total word count
✅ Method → ~1/3 of total word count
✅ Results → Brief
✅ Discussion → ~1/3 of total word count
✅ Abstract, References, Appendices → Abstract is short; References & Appendices don’t count towards the word limit.
General Writing Rules
- Audience → Psychologists who know general psychology but not your specific topic; define all key terms and abbreviations.
- Tone →
- Use third person (“It was found…” not “I found…”).
- Use past tense (except when discussing future research).
- Avoid causal language (surveys reveal associations, not causation).
- Avoid saying you’ve “proven” something; stick to support or reject.
Section Breakdown
Here’s what typically goes into each section:
Abstract
- Very brief summary (about 150–200 words)
- Summarize: background, aims, methods, key findings, conclusions.
Introduction (~1/3)
- Introduce the research topic.
- Provide background literature to build a rationale.
- Clearly state your research question and hypotheses.
Method (~1/3)
- Explain participants (who, how many, recruitment).
- Describe materials/measures (questionnaires, scales, etc.).
- Explain procedure (step by step what was done).
- Describe analysis approach (what tests, software, etc.).
Results (brief)
- Report key findings, including statistical outcomes.
- Include tables/figures if helpful (numbered, titled, APA style).
- Don’t interpret results here — just report them.
Discussion (~1/3)
- Summarize key findings.
- Relate back to the research question and hypotheses.
- Compare with previous literature.
- Discuss limitations.
- Suggest future research directions.
- End with a clear conclusion.
References & Appendices
- Full APA-style reference list.
- Appendices for extra materials (e.g., full questionnaire, ethics forms).
✅ Introduction Structure (Downward-Pointing Triangle)
1️⃣ Start Broad but Focused
- Open with why the topic matters in psychology (not vague life statements).
- Identify theoretical models or big-picture psychological relevance.
2️⃣ Literature Review (Relevant & Focused)
- Only include studies directly related to your research question.
- For each study:
- What was investigated?
- What method was used (briefly)?
- What was found?
- How does it connect to your project?
- Don’t summarize irrelevant or background studies; stay targeted.
3️⃣ Introduce Your Variables
- Use clear paragraphs for:
- Explaining each key variable (what it is, why it matters).
- Explaining why you chose these variables.
- Explaining how they are expected to relate to each other.
4️⃣ State the Gap
- Where does the existing research fall short?
- What gap are you addressing?
- Why is your research important in filling this gap?
5️⃣ Present the Research Question/Hypothesis
- End with a clear, direct statement:
- Your research question.
- Your predictions (if doing multiple regression) or specific aim (if exploratory).
- Be precise: state whether you predict positive/negative relationships or specific effects.
💡 Quick Reminders
- Write in your own words (no long quotes).
- Link every cited study directly to your research purpose.
- Make sure paragraphs flow logically toward your final hypothesis.
- Remember: you’re building a funnel from broad importance → specific focus.
here’s a clear summary of the multiple regression results from your SPSS output for your report writing:
✅ Model Summary (best model)
- R = 0.570
- R2 = 0.325 → This means 32.5% of the variance in mental health attitudes (MHSA_total) is explained by the predictor (CD_total, i.e., collectivism/individualism).
- Adjusted R2 = 0.310
- Std. Error of Estimate ≈ 11.51
✅ ANOVA (overall model significance)
- F(1, 46) = 22.105, p < .001 → This is statistically significant, meaning the model significantly predicts the outcome .
✅ Regression Coefficients
- Constant (Intercept): B = -1.650, p = .879 (not significant)
- CD_total (Cultural Dimensions): B = 0.368, β = 0.570, t = 4.702, p < .001 → This predictor is strong and highly significant.
✅ Excluded Predictors
- SBS_total (Supernatural Belief Scale): β = 0.199, p = .103 → Not significant in the final stepwise model.
- SS_total (Social Support): β = -0.158, p = .300 → Not significant.
✅ Reliability (for MHSA scale)
- Cronbach’s alpha = 0.945 → Excellent internal consistency.
Results
Descriptive Statistics
The final sample included 71 participants. Demographic characteristics showed a balanced gender distribution (43.7% male, 38% female, 1.4% non-binary, 1.4% prefer not to disclose), with a broad age range (18–52 years). Educational backgrounds included secondary, undergraduate, and postgraduate levels.
The Mental Health Attitudes Scale (MHSA) showed excellent internal consistency, with a Cronbach’s alpha of 0.945, indicating high reliability.
Correlation Analyses
Preliminary Pearson’s correlations examined the relationships between MHSA scores and the main predictors. Collectivism/individualism (CD_total) showed a significant positive correlation with MHSA scores, suggesting that cultural dimensions were meaningfully associated with mental health attitudes. Supernatural beliefs (SBS_total) and social support (SS_total) showed weaker or nonsignificant correlations.
Multiple Regression Analysis
A stepwise multiple regression was conducted to predict attitudes toward mental health (MHSA_total) using cultural dimensions (CD_total), supernatural beliefs (SBS_total), and social support (SS_total) as predictors.
The final model retained CD_total as the sole significant predictor:
- Model fit: R = 0.570, R2 = 0.325, Adjusted R2 = 0.310, F(1, 46) = 22.105, p < .001.
This indicates that cultural dimensions explained approximately 32.5% of the variance in mental health attitudes. - Predictor coefficients:
- CD_total: B = 0.368, β = 0.570, t(46) = 4.702, p < .001 — a strong and highly significant predictor.
- SBS_total (supernatural beliefs) and SS_total (social support) were excluded from the final model due to nonsignificance (p = .103 and p = .300, respectively).
These results partially support the original hypotheses: cultural values were significant predictors, while supernatural beliefs and social support did not significantly predict mental health attitudes in this sample.
Research Question and Hypotheses
The central research question guiding this study is: Which factors best predict attitudes toward mental health in Pakistan?
Based on the literature, the following hypotheses are proposed:
- H1: Stronger supernatural beliefs will predict more negative attitudes toward mental health.
- H2: Stronger collectivist values will predict more negative attitudes, while stronger individualist values will predict more positive attitudes.
- H3: Younger age and higher education levels will predict more positive attitudes toward mental health.
- H4: Gender differences will emerge, with females showing more supportive and less stigmatizing attitudes.