Inventory-Description

The Cohen-Hoberman Inventory of Physical Symptoms (CHIPS-33) is a self-report tool developed to measure physical symptoms associated with stress and anxiety. The CHIPS-33 consists of 33 questions that refer to common physical symptoms, such as headaches, stomach pains, dizziness, and others. Participants are asked to indicate how often they experience these symptoms within a specific time frame, usually on a Likert scale (e.g., from “not at all” to “very much”).

Data Analysis and Usage

The analysis of data from CHIPS-33 is quantitative, aiming to assess the number and intensity of physical symptoms reported by participants. It is often used in studies related to stress and psychosomatic reactions. The analysis may include evaluating the overall intensity of symptoms, exploring relationships between physical symptoms and psychological variables (e.g., anxiety, depression), and comparing population groups.

Statistical analysis of the results can involve calculating means and standard deviations for each symptom, as well as using factor analysis to identify subscales or common factors influencing physical symptoms.

CHIPS-33 is widely used to measure the frequency and intensity of physical symptoms in studies examining stress and its psychological effects on various populations. Data collected from this scale can be used to link physical symptoms with psychological factors, such as burnout, chronic fatigue, or mood disorders. Additionally, CHIPS-33 is useful in intervention programs, as it can measure changes in physical symptoms before and after therapeutic interventions.

Purpose

The goal of CHIPS-33 is to assess the occurrence and severity of physical symptoms associated with stress and anxiety. The scale allows for monitoring the frequency of these symptoms across different populations and can be used to explore the relationship between psychological and physical reactions.

Calibration

The calibration of the CHIPS-33 scale is based on recording the frequency of physical symptoms reported by participants. The responses are aggregated and converted into quantitative scores that reflect the overall frequency and severity of symptoms. The reliability coefficient of the scale (usually Cronbach’s alpha) is used to evaluate the internal consistency of the data, meaning how well the various symptoms relate to a common psychological framework (e.g., stress).

References

Cohen, S., & Hoberman, H. M. (1983). Positive events and social supports as buffers of life change stress. Journal of Applied Social Psychology, 13(2), 99-125.

Cohen, S., Kessler, R. C., & Gordon, L. U. (1997). Measuring Stress: A Guide for Health and Social Scientists. Oxford University Press.