What to Do When Cronbach’s Alpha Is Below 0.7

In research that uses questionnaires, one of the most important steps in verifying the reliability of the research instrument is calculating the Cronbach’s Alpha coefficient. This value measures the internal consistency of items within a variable or dimension.

What to Do When Cronbach’s Alpha Is Below 0.7

Generally, Cronbach’s Alpha can be interpreted using the following criteria:

• ≥ 0.90 = Excellent

• 0.80 – 0.89 = Good

• 0.70 – 0.79 = Acceptable

• 0.60 – 0.69 = Questionable

• 0.50 – 0.59 = Poor

• < 0.50 = Unacceptable

Therefore, if your Cronbach’s Alpha is below 0.7, it indicates that your questionnaire may not have sufficient internal consistency — directly affecting the reliability of your data.

But don’t worry — there are systematic ways to review and improve your reliability score, as explained below

1. Review the Number of Items

The number of questions in a construct has a strong influence on the Cronbach’s Alpha value. If the number of items is too small (e.g., only 2–3 questions), Alpha will usually be low even if the questions are reasonably correlated. Ideally, include 4–6 items or more that measure the same concept to improve reliability.

Tip: Avoid adding unnecessary questions. Each item should be theoretically justified and relevant to the construct being measured.

2. Check the “Corrected Item-Total Correlation”

In SPSS, you will find a column labeled “Corrected Item-Total Correlation.” This shows how strongly each item correlates with the total score of the variable. If a question has a value below 0.30, it may not be consistent with the others. Try removing that item and recalculate Cronbach’s Alpha. Even deleting one or two inconsistent items can increase the Alpha value — for example, from 0.6 to 0.8.

3. Review Respondents’ Understanding of the Questions

Sometimes, the issue lies not in the instrument itself but in how respondents interpret the questions.Common problems include:

• Complex or technical wording

• Ambiguous phrasing

• Inappropriate rating scales

To fix this, simplify the wording, ensure clarity, and conduct a pre-test with a small sample to check if respondents interpret the questions consistently.

4. Examine the Construct Dimension

A single construct may have multiple dimensions. For example, “Job Satisfaction” may consist of sub-dimensions such as work environment, colleagues, and compensation. If you combine questions from multiple dimensions without separating them before analysis, Cronbach’s Alpha will likely be low.

Suggested Solution:

• Calculate Cronbach’s Alpha for each sub-dimension separately.

• Identify which dimension has a low Alpha value and refine those items accordingly.

Why You Should Use Data Investigator

Improving a low Cronbach’s Alpha requires both theoretical understanding and statistical expertise. With over 15 years of experience in data analysis and research methodology, Data Investigator provides professional guidance at every stage, including:

• Reliability (Cronbach’s Alpha) and validity testing of research instruments

• Questionnaire improvement and refinement to raise reliability scores

• Data analysis using SPSS

• Detailed interpretation and explanation of statistical results

• Issuance of a Certificate of Statistical Analysis for official submission

Whether you are a graduate student, medical researcher, or government agency, Data Investigator ensures your research achieves reliable, accurate, and statistically valid results.

For more information, please contact:

Email: info@datainvestigatorth.com

LINE: @datainvestigator