Clinical practical: a content analysis of attitudes to mental health

Planning and design decisions

Aim (example): to compare attitudes to mental health in newspaper articles from 2005 and 2025.

• Sources: secondary data from at least two sources, such as two newspapers or two years, found through a newspaper database or archive. Judge credibility (reputable publishers, complete articles).
• Sampling: for example, the first 40 articles in each year containing 'schizophrenia' or 'mental illness', or a random sample from a search.
• Coding scheme (operationalised categories): stigmatising (for example 'psycho', linking illness with violence), neutral (factual reporting), supportive (recovery stories, accurate information).
• Controls: same search terms and dates in each source; clear definitions with examples for each category.
• Ethics: avoid reproducing stigmatising language unnecessarily, do not identify private individuals, be sensitive to how the topic may affect classmates.

Carrying it out and reliability

1. Pilot the coding scheme on a few articles and refine unclear categories.

2. Read each article and assign it (or each relevant sentence) to one category, tallying frequencies.

3. Inter-rater reliability: a second researcher codes the same articles independently. Agreement = agreed codes / total x 100. If two coders agree on 46 of 50 articles, agreement is 92%; a high figure (or a strong correlation between coders' tallies) shows the scheme is reliable.

4. Qualitative comments can also be gathered through thematic analysis of article language.

Results and analysis

Practice results (invented):

Chi-squared = 10.87, df = 2. Critical value (df 2, p ≤ .05) = 5.99; (p ≤ .01) = 9.21.

Discussion and evaluation

With χ² = 10.87 (df = 2) above the critical value of 9.21 for p ≤ .01, there is a significant association between year and attitude: 2025 articles were less stigmatising and more supportive.

Strengths of content analysis: uses existing data, so no participants are harmed or affected by demand characteristics; replicable with a clear coding scheme; produces quantitative data for statistical testing.

Weaknesses: coding involves interpretation (subjectivity); categories may miss subtle attitudes; newspapers may not represent public attitudes; sources chosen may be biased.

Improvements: more coders, larger or randomly selected samples, more sources (radio, social media), clearer category definitions.

Worked example

Describe how you would make sure the coding in your content analysis was reliable.

1. Write precise definitions and examples for each category (for example, 'stigmatising: links mental illness with violence or uses words such as psycho').
2. Pilot the scheme on articles not in the main sample and refine unclear categories.
3. Have two researchers code the same articles independently.
4. Calculate the percentage agreement (for example 46 / 50 = 92%) and discuss disagreements.

Answer: Operationalised categories, piloting and inter-rater reliability, all linked to mental health articles.

Check yourself

1. Using the practice results table, calculate the chi-squared value to 2 decimal places.
   Show answer

   10.87. Expected values: 15.50, 13.00, 11.50, 15.50, 13.00, 11.50. Sum of (O - E)² / E = 10.87.

2. What are the degrees of freedom for this 2 x 3 table?
   Show answer

   2. (2 - 1) x (3 - 1) = 2.

3. What is the expected frequency for '2005 articles, stigmatising'? Give your answer to 1 decimal place.
   Show answer

   15.5. Row total 40 x column total 31 / grand total 80 = 15.5.

4. Two coders agreed on 43 of 50 articles. What is the percentage agreement?
   Show answer

   86 %. 43 / 50 x 100 = 86%.

5. What type of data does the content analysis practical use?
   • Secondary data from existing sources such as newspapers
   • Primary data from interviews with patients
   • Brain scan data
   • Data from animal experiments
   Show answer

   Secondary data from existing sources such as newspapers. The examiners gave 0 for claims of collecting primary data.

6. What is the minimum number of sources the spec requires you to analyse?
   • One
   • Five
   • Two
   • Ten
   Show answer

   Two. At least two sources, to compare attitudes.

7. Explain one weakness of using content analysis to investigate attitudes to mental health.
   Show answer

   Deciding which category an article fits involves interpretation, so coding can be subjective and another researcher might code it differently, reducing reliability.. Subjective coding or unrepresentative sources.

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Sources

• Pearson Edexcel International Advanced Subsidiary/Advanced Level in Psychology specification (issue January 2026)
• Pearson IAL Psychology component guide: WPS04 (Issue 2, November 2024)
• Pearson WPS03/01 question paper, January 2022 (formulae and critical values tables)
• Pearson WPS04/01 examiners' report, June 2025

Last updated 8 November 2026. Spotted a mistake? Tell us.