Measuring Comfort (Immediate Outcome)

In this section, I included most of the comfort instruments that either I or other researchers have used. A new instrument can be adapted from the original or shortened general comfort questionnaire (GCQ) when an innovative comforting intervention is developed. Nurses want to know if there is an increase in comfort with that intervention. Another source of adapted comfort questionnaires is the desire to use them on a non-English speaking population. Therefore you will see many translations in this section, more evidence for the universality of comfort.

 

If you are interested in pediatrics, please look at the Doggie Study, which is a complete article written by an honors student. She used the comfort daisies. to measure the difference between comfort and pain before and after a doggie visit to hospitalized children.  Another favorite comfort questionnaire is designed for an LGBTQ population. Sadly, there is no article to accompany this instrument, which did have strong psychometrics.  A poster about this instrument may be helpful. The thermal comfort questionnaire was developed in response to the manufacturer of Bair Paws who was rolling out a new patient-controlled heated gown for perioperative use. The Comfort Behaviors Checklist was developed and tested by me to measure the comfort of unconscious or non-verbal patients. Although it demonstrated good inter-rater reliability, I did not publish this instrumentation study. Others have used it for their special populations and/or interventions, but have not informed me about a resulting publication (check with your reference librarian or Google Scholar for your particular need).

 

 Below is a picture of me with nurses from Mt. Sinai Hospital in NYC. Magic Johnson was visiting and kindly consented to have his picture taken with us. This hospital  successfully implemented Comfort Theory throughout all levels of staffing, families, and patients.

Instruments

Introduction

 

APPLYING CT TO YOUR POPULATION/RESEARCH QUESTION

 

Comfort Theory proposes that when comfort of patients and/or families is enhanced, they can engage more fully, either consciously or subconsciously, in health seeking behaviors (HSBs). HSBs are mutually agreed upon goals. Health seeking behaviors can be internal (e.g. blood work), external (goals in physical therapy), or a peaceful death (Part Two).  When patients and families do better, the institution does better, as in measures of patient satisfaction or improved ratings (Part Three).  

 

So, how can you apply Comfort Theory to a different patient population and/or problem area to test part 2 or 3 or both? Please remember, any of the existing comfort questionnaires or checklists (most of which are listed in this section) can be adapted by using YOUR common sense and the taxonomic structure of comfort, which assures you are covering the content map of your immediate outcome (comfort). Your subsequent outcomes and institutional outcomes are up to you, your patients and/or families, and/or your administrators to determine (a) what they would like to accomplish and (b) what is feasible with existing data banks or instruments for measurement. You have my permission to do any of the above; indeed, it is my wish that you all become self-sufficient comfort researchers. 

 

Creating your own questionnaire Using the Taxonomic Structure (TS) of Comfort as your Guide

 

  1. Delete questions from the original General Comfort Questionnaire that are not relevant for your population.

  2. Place the number of retained questions on the TS of comfort, noting whether they are positive indicators of comfort (+) or not instances of comfort (-). This process creates a map of the questions you presently have in the content domain of comfort. (Please remember to cite the origin of the TS in your proposals/presentations/articles [Kolcaba, 2003; or TheComfortLine.com]. You can also cite the psychometric properties of the original CGQ when presenting your plans for an adapted instrument. Just indicate that they provide your adapted instrument with preliminary validity and reliability.

  3. Fill in the map with your own and retained positive and negative items that that are specific to your population and research question. You want to achieve a balance across the entire content domain of comfort. If you decide that one of the contexts or types of comfort is not important to assess for your population, take that row or column out, but justify the exclusion in your write-up.

  4. When constructing your questionnaire, it may be difficult to discern between positive questions for relief and ease. I think of the difference as this: relief is the immediate lifting of an existing, acute discomfort, while ease is a longer lasting and positive condition such as contentment, peacefulness, or restfulness, that connotes a possible predisposition to a discomfort. To keep a patient in a state of ease, however, the health care tea, should be aware of the acute discomforts to which he or she is predisposed. 

  5. Adapted Instrument Sample Paragraph:  (see PACU or thermal comfort- related documents in this section): 

 

Thermal comfort will be measured with the TCQ (Appendix __) which was modified from the original GCQ (Kolcaba, 1992). The GCQ was a 48-item questionnaire with a six-point Likert-type response format. After reverse-coding negative items, higher scores indicate higher comfort. The GCQ was pilot tested with 256 subjects randomly selected from the community and diverse hospital groups, including the population of interest for this study. The data from the pilot test were factor analyzed revealing three factors. The factors were semantically consistent with the types of comfort in the taxonomic structure and were named relief, ease, and transcendence (Kolcaba, 1992). Cronbach’s alpha was .88 for the 48 items.

 

In order to test Part 3 of Comfort Theory, you need to show a correlation between Health Seeking Behaviors (of either patients or nurses) and Institutional Integrity (InI). Unfortunately, you need an insider nurse manager to access the proprietary data on patient satisfaction, cost/benefit analysis, or staff retention. Less proprietary, and perhaps more quickly accessible, are specific benchmarks decided upon by nurse leaders with staff feedback.  Some examples might be (a) increase nurse retention by 20 % in next 12 months; (b) increase patient satisfaction with ED department in next 6 months; (c) decrease use of agency nurses by 30 % in next 3 months; or implement comfort projects on 3 units in next 3 months. Some of these InI outcomes are related to patients’ comfort and some are related to nurses’ comfort.  It is important to be specific, and to collect baseline data before implementing any comfort strategies. 

Links to Comfort Instruments

Translations

© 1997 - 2019 by Kathy Kolcaba

Webmaster Paul Cantlay

  • Facebook Clean Grey