Guide to the Practical Investigation Revision Notes for Edexcel A-Level Psychology

Guide to the Practical Investigation

Introduction

When conducting psychological research, it is essential to follow established research guidelines. The planning stage ensures that investigations adhere to these standards and are executed properly. Within health psychology, researchers commonly employ three main investigation approaches:

Questionnaires – structured written surveys to gather self-report data
Interviews – face-to-face or verbal questioning to collect detailed information
Content analysis – systematic examination of communication materials (e.g., television programmes, newspapers, social media)

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This guide focuses on content analysis as a practical investigation method, using an example study examining drug references in television programmes before and after the 9:00 pm watershed.

Conducting health psychology research

Research in health psychology follows systematic stages to ensure validity and reliability. The investigation must be carefully planned to produce meaningful, ethical results that can contribute to the field.

Defining the aim

The aim states the overall purpose of the investigation. It should clearly explain what the study intends to achieve.

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Example aim: To conduct a content analysis investigating drug references in television programmes before and after the watershed. The watershed is a broadcasting deadline preventing television programmes with adult content, including references to or portrayals of drug-taking behaviour, from being shown before 9:00 pm.

Formulating the research question

The research question transforms the aim into a specific, testable query.

Example research question: Is there a difference in the exposure to drug references in programmes broadcast before and after the watershed?

Developing hypotheses

Two types of hypotheses should be stated:

Alternative hypothesis (H₁): A directional prediction about what the researcher expects to find. This should be based on theory or previous research.

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Alternative Hypothesis Example

There will be more drug references in television programmes after the watershed than before it.

This is directional because legislation predicts that more drug references would appear after the watershed, when they are permitted to be shown.

Null hypothesis (H₀): States that there will be no difference between conditions, and any difference found is due to chance.

Example: There will be no difference in the number of drug references made before and after the watershed, and any difference found will be due to chance factors.

Planning the content analysis

Careful planning is essential before beginning data collection. Several key considerations must be addressed:

Operational planning

The procedure should clearly outline each step of the investigation. Consider the following:

What to observe: Which programme(s) will you watch and for how long? Will you analyse just one episode or multiple programmes?
What to look for: Exactly what behaviours or references will you be recording? What constitutes a "drug reference"?
How to record findings: What recording method will you use? Will a frequency chart (tally chart) be sufficient, or do you need to collect qualitative data as well?
How to analyse data: What is your overall plan for data analysis? How will you compare results between conditions?

Sampling decisions

Consider how many programmes you plan to analyse. Will you examine just one programme or a variety? Recording data from multiple programmes can provide a more representative sample. For the example study, one programme would be viewed on a specified Monday night before the watershed, and a different programme would be watched after the watershed. A frequency chart would monitor how often specific references to substances are made.

Operationalisation and behavioural coding

Operationalisation means clearly defining the variables being measured so that if the study were repeated, another researcher would know exactly what to observe and record.

Defining "drug references"

For the investigation to be replicable, "references to drugs" must be precisely defined. Consider:

Are you examining references to specific drugs, or all drugs?
If all drugs, does this include alcohol?
What behaviours relate to drug use?

Behavioural categories

Establishing clear behavioural categories ensures clarity in data collection, making findings more reliable. In the example study, the following behaviours or references from actors would be observed and tallied:

Smoking
Going to the pub
Buying cigarettes
Talking about wanting or needing a cigarette
Drinking alcohol at home

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Each time one of these behaviours is observed, it is recorded on the tally chart. At the end of the programme, tallies are added up to produce frequency data.

Inter-rater reliability

Inter-rater reliability reduces subjectivity by having multiple individuals observe the same content and compare their findings. This process improves the objectivity and reliability of data collection.

Implementing inter-rater reliability

In the example content analysis:

More than one person watches television before and after the watershed
Each observer rates the number of drug references independently
Researchers compare their findings afterwards
When using multiple researchers, operationalisation becomes even more important to ensure consistent recording

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The accuracy of coding increases when researchers are specific about what constitutes a drug reference on television. Tallies gathered by both raters can be compared to check for agreement. High levels of agreement indicate good inter-rater reliability, which ensures data reliability.

Recording procedure

In this investigation, a whole episode of each soap would be watched. The tally chart would be filled in as behaviours are observed. Other individuals would watch the same television programme on the same night, looking for the same behaviours, and record data on their own copies of the tally chart.

Example tally chart structure

Behaviour category	Programme 1 (before watershed)	Programme 2 (after watershed)
An actor smoking
An actor going to the pub
An actor buying cigarettes or talking about wanting to smoke a cigarette
An actor drinking alcohol at home

Ethical considerations

When undertaking research, ethical issues must be carefully considered. The example investigation involves watching television programmes, which raises particular ethical questions.

Pre-watershed programmes

For programmes broadcast before the watershed, there are no ethical issues in undertaking a content analysis. The raters are permitted to watch these programmes.

Post-watershed programmes

Raters are also permitted to watch programmes broadcast after the watershed. However, the research may uncover something considered socially sensitive. For example, discovering that children are exposed to a large number of drug references on television could be problematic. If this occurs, this knowledge could benefit society as it might act as an agent for change.

Ethical checklist

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Before Starting Your Investigation

Review the British Psychological Society (BPS) guidance on conducting research and use this as a checklist to ensure all areas of ethics have been considered. Check with your teacher that your procedure is ethical before proceeding with the investigation. This is particularly important if you are conducting a questionnaire or interview.

Analysing results

The data gathered from the study are collated as quantitative data. For example, the number of times a drug reference was made on television, based on the specific behaviours outlined at the planning stage. Quantitative data allow for simplistic statistical analysis, as discussed in detail in previous topics. Any qualitative data collected will need to be translated into quantitative data so it can be analysed statistically.

Example data: Tally chart results

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Tally Chart Results

The tally chart might show the following pattern:

Behaviour	Programme 1 (before watershed)	Programme 2 (after watershed)
An actor smoking	III	IIII
An actor going to the pub	IIII	III
An actor buying cigarettes or talking about wanting to smoke a cigarette	I	II
An actor drinking alcohol at home	II	IIII

This tally chart demonstrates that a range of drug references were made in both television programmes, both before and after the watershed.

Creating a contingency table

The data can be presented more clearly when references to cigarettes and alcohol are totalled separately in a 2×2 contingency table:

	References to alcohol	References to nicotine	Total
Programme 1 (before watershed)	6	4	10
Programme 2 (after watershed)	7	6	13
Total	13	10	23

Visual representation

Converting the tally chart into a visual record, such as a bar chart, assists in comparing data. A bar chart showing the total number of drug references in a single episode of Programme 1 and Programme 2 would display:

Actor smoking: ~12 references (Programme 1), ~14 references (Programme 2)
Actor going to the pub: ~14 references (Programme 1), ~13 references (Programme 2)
Actor buying cigarettes: ~2 references across both
Actor talking about wanting a cigarette: ~1 reference
Actor drinking alcohol at home: ~3 references

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Of the 23 references to drug use, 10 occurred before the watershed and 13 after the watershed. This may not seem a huge difference, but whether it is statistically significant can only be established by conducting a chi-squared statistical test.

Chi-squared analysis

As normal level data has been gathered and we are looking for a difference between drug references before and after the watershed, a chi-squared test is the most appropriate statistical test to use.

Understanding chi-squared

The procedure for chi-squared analysis involves calculating the expected frequencies of the data being gathered. An expected frequency needs to be calculated for all four cells in the 2×2 contingency table, so it is useful to label each cell as a, b, c and d.

Data table for chi-squared

Observed frequencies	References to alcohol	References to nicotine	Total
Programme 1 (before watershed)	Cell a: 6	Cell b: 4	10
Programme 2 (after watershed)	Cell c: 7	Cell d: 6	13
Total	13	10	23 (overall total)

Calculating expected frequencies

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Chi-Squared Calculation: Step-by-Step

Use the formula to calculate the expected frequencies for each cell:

Formula: $\text{(Row total} \times \text{Column total)} \div \text{Overall total}$

Step 1: Multiply the row total by the column total for each cell and divide by the overall total.

Cell a: $10 \times 13 \div 23 = 5.65$
Cell b: $10 \times 10 \div 23 = 4.35$
Cell c: $13 \times 13 \div 23 = 7.35$
Cell d: $13 \times 10 \div 23 = 5.65$

Step 2: For each cell, subtract the expected frequencies from the observed frequencies.

Cell a: $6 - 5.65 = 0.35$
Cell b: $4 - 4.35 = -0.35$
Cell c: $7 - 7.35 = -0.35$
Cell d: $6 - 5.65 = 0.35$

Step 3: Square the result for each cell.

Cell a: $0.35^2 = 0.1225$
Cell b: $(-0.35)^2 = 0.1225$
Cell c: $(-0.35)^2 = 0.1225$
Cell d: $0.35^2 = 0.1225$

Step 4: Divide the sum of step 3 by the expected frequencies for each cell.

Cell a: $0.1225 \div 5.65 = 0.02$
Cell b: $0.1225 \div 4.35 = 0.03$
Cell c: $0.1225 \div 7.35 = 0.02$
Cell d: $0.1225 \div 5.65 = 0.02$

Step 5: Find the sum total of all the scores calculated in step 4.

$0.02 + 0.03 + 0.02 + 0.02 = 0.09$

Chi-squared test statistic = 0.09

Determining degrees of freedom

This result needs to be compared to a table of critical values for a chi-squared test to establish whether the findings are significant. Before using the critical value table, we need to calculate the degrees of freedom (df). This determines which row to follow in the table.

Degrees of freedom formula:

$df = (R-1)(C-1)$

Where:

R refers to the total number of rows (in this case, two cell rows)
C refers to the total number of columns (in this case, two column cells in the 2×2 contingency table)

$df = (2-1) \times (2-1) = 1$

Critical values table

Level of significance for a one-tailed test
	0.1	0.05
Level of significance for a two-tailed test
df	0.2	0.1
1	1.64	2.71
2	3.22	4.60

Note: Calculated value of chi-square must be equal to or exceed the table (critical) value for significance at the level shown.

Interpreting the results

This example investigation proposed a directional hypothesis, so a one-tailed test will be used. The accepted level of significance in psychology is $p=0.05$ , with $df=1$ , the critical value is 2.71.

The calculated chi-square value = 0.09 must be equal to or exceed the critical value of 2.71, which it does not. Therefore, the result is not significant at the significance level of 0.05. This means that there is no difference between references to drugs before and after the watershed, and the null hypothesis should be retained.

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Reporting Statistical Values

When reporting the statistical value/outcome, do so carefully, as missing a '0' from the $p$ value can have major implications on whether the data is significant or not.

Drawing conclusions

The conclusions should be logical, based on the findings presented. Conclusions can be discussed briefly to avoid repeating the findings in detail. When discussing conclusions, it is helpful to return to the original research question and hypothesis. You can then conclude whether the data supports or disproves the hypothesis.

Example conclusion statement

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Example Conclusion

The example investigation proposed a directional hypothesis and used a one-tailed test. The accepted level of significance in psychology is $p=0.05$ , with $df=1$ , the critical value is 2.71. The calculated chi-square value = 0.09 must equal or exceed the critical value of 2.71, which it does not. Therefore, the result is not significant at the significance level of 0.05. This means that there is no difference between references to drugs before and after the watershed, and the null hypothesis should be retained.

Discussion

Once the analysis has been conducted, you should present your findings in a way that is clearly understandable to the reader. Using subheadings can help ensure clarity within the discussion. When discussing findings, it is best to address all findings, including those that do not support the hypothesis. This demonstrates transparency in your research.

Example discussion points

A discussion point within the current example may be:

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It is noted that there were more references to drinking alcohol than there were to smoking, though there was only a small difference in the number of references made between alcohol and cigarettes. While there were a number of actors smoking on the programme before the watershed, very few actually spoke about wanting a cigarette. The pub was heavily featured in the episode, with many actors going to the pub. This is where most of the alcohol observed was consumed, with very few actors drinking within their own home.

Evaluation: Strengths

When evaluating a study, it is helpful to consider its strengths or weaknesses in several areas. These can include:

Participant numbers and where they were recruited from
How the data was gathered
The methodology used
Validity, reliability and generalisability of findings to the research field

Strength 1: Inter-rater reliability

One strength of this practical investigation was the use of inter-rater reliability. This means that the raters' scoring is compared for agreement. If there is good agreement between the tallies observed by the raters, inter-rater reliability can be established. A correlation can be conducted to establish the rate of agreement between the raters. A high positive correlation co-efficient shows good agreement.

Strength 2: Objective data collection

The use of operationalised behavioural categories meant that data collection was systematic and objective, reducing the potential for subjective bias in recording drug references.

Evaluation: Weaknesses

Weakness 1: Loss of meaningfulness

The process of quantifying the content of television programmes may lose the meaningfulness of the data as it is converted into a numerical form. The context and nuances of how drugs are portrayed may be lost when reducing observations to simple frequency counts.

Weakness 2: Limited sample

Only one episode of each television programme was analysed. It may be that the particular episode was dealing with a drug-related issue, which may have overemphasised drug use. Such drugs being used in this way may not be representative of the content shown in programmes before and after the watershed. A suggestion for improvement would be to use more than one episode of each television programme to counteract this problem.

Weakness 3: Generalisability concerns

Only one programme before and one after the watershed were analysed. The programmes analysed may not be representative of the content of programmes shown before and after the watershed. A suggestion for improvement would be to analyse a range of different genres of programmes both before and after the watershed to obtain a more generalisable sample.

Fully explaining your reasoning

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When evaluating a study, it is important to fully explain your reasoning, rather than simply assuming the reader will understand why you think a study has ecological validity, for example. Proper justification strengthens the quality of evaluation.

Summary

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Key Points to Remember:

Content analysis requires careful operationalisation of behavioural categories to ensure replicability and reliability of data collection.
Inter-rater reliability is established by having multiple observers independently record the same content and comparing their results for agreement.
A chi-squared test is appropriate for analysing nominal data when looking for differences between conditions in a contingency table.
Degrees of freedom must be calculated using the formula $df = (R-1)(C-1)$ before comparing the chi-squared statistic to critical values.
null hypothesis is retained when the calculated chi-squared value does not equal or exceed the critical value at the accepted significance level ( $p=0.05$ ).
A comprehensive discussion should present findings clearly, evaluate the study's strengths and weaknesses, and suggest improvements for future research.

Guide to the Practical Investigation (Edexcel A-Level Psychology): Revision Notes