Each domain of health has
many components: like symptoms, ability to function, and disability, that need
to be measured. Because of
this multidimensionality (Fig. 1), there is an almost infinite number of states
of health, all with differing qualities, and all quite independent of
longevity.

 

 

 

 

Figure 1: Conceptual Scheme of the Domains
and Variables Involved in a Quality-of-Life Assessment.

“x” axis represents subjective perceptions
of health,

“y” axis objective health status,

Coordinates Q (X, Y) the actual quality of
life, and

“Z” measurement of the actual quality of
life associated with a specific component (e.g., positive affect) or domain (e.g.,
the psychological domain).

Measuring quality of life

 

Translating the various domains and
components of health into a quantitative value that indicates the quality of
life is a complex procedure, drawing their tenants from the fields of
clinimetrics,20 psychometrics, and clinical decision theory.

Usually most of the researchers
measure each quality-of-life domain individually, by asking specific questions
related to its most important components. By asking a simple question, such as
“Please rate your quality of life or overall health on a scale from 1 to 10,”
although it may provide a useful global assessment, leaves “quality of life”
and “overall health” ambiguously defined and the quantity being measured too
vague to be interpreted more exactly. Relying purely on data indicating
objective health status, such as physicians’ reports of symptoms, omits such
relevant factors as a person’s threshold for the tolerance of discomfort.21

Variation among quality-of-life
questionnaires is often related to the degree to which they emphasize objective
as compared with subjective dimensions, the extent to which various domains are
covered, and the format of the questions, rather than differences in the basic
definition of quality of life.

Constructing
scales of measurement

As we know that many components of
quality of life cannot be observed directly, they are typically
evaluated according to the classic principles of item measurement theory.22

According to this theory the true
quality-of-life value, Q, cannot be measured directly, but it can be measured
indirectly by asking a series of questions known as “items,” each of which
measures the same true concept or construct. These set of questions are then
asked to the patient, and the answers are converted to numerical scores that
are then combined to yield “scale scores,” which may also be combined to yield
domain scores or other statistically computed summary scores.23

If all the selected items have been
chosen properly, the resulting scale of measurement, Z, should differ from the
corresponding true value, Q, only by random error of measurement and should
possess several important properties.

These properties are:

1)   
Coverage

The measurement of quality of life should
cover each objective and subjective component (symptom, condition, or social
role) that is important to members of the patient population and susceptible to
being affected, positively or negatively, by interventions.

2)   
Reliability

The process of measurement must yield
values that are consistent or remain similar under constant conditions, even in
an extended series of repeated assessments.

3)   
Validity

The observed scales should be so valid; that is, they target and
measure what they claim to measure.

4)   
Responsiveness

Responsiveness is a measure of the
association between change in the observed score, Z, and the change in true
value of the construct, Q.

Since quality of life is not directly
observable, a change in Q also cannot be measured directly. So, responsiveness
is often assessed by changing a criterion variable, C.

5)   
Sensitivity

Sensitivity refers to the ability of the
measurement to reflect true changes or differences in Q (Quality of life).

Selecting
an Assessment Instrument

The instruments and techniques used
to assess quality of life vary according to the identity of the respondent
(that is, whether he or she is a clinician, patient, relative, or care
provider), the setting of the evaluation and the type of questionnaire used
(short form, self-assessment instrument, interview, clinic-based survey,
telephone query, or mail-back survey), and the general approach to the
evaluation.

Generic instruments are used in
general populations to assess a wide range of domains applicable to a variety
of health states, conditions, and diseases.24,25 Disease-specific
instruments focus on the domains most relevant to the disease or condition
under study and on the characteristics of patients in whom the condition is
most prevalent.26-28 Disease-specific instruments are most
appropriate for clinical trials in which specific therapeutic interventions are
being evaluated.29-31

The Oral Health Impact Profile (OHIP)
questionnaire is one of the most commonly used instruments; it has been used in
various studies across different cultures and socio-demographic profiles. The
OHIP was developed in order to provide a comprehensive measurement of the
dysfunction, discomfort, and disability associated with oral conditions as
reported by the individual.32,33 OHIP analyzes the different
dimensions of functional patterns.

These dimensions are functional
limitation (e.g., difficulty chewing), pain (e.g., sensitivity of teeth),
psychological discomfort (e.g., personal embarrassment), physical disability
(e.g., changes in diet), psycho- logical disability (e.g., reduced
concentration), social disability (e.g., avoiding social contact), and
incapacitation (e.g., being unable to work productively).33,34

In 1997, Slade described an abridged version of the OHIP, called
OHIP-14, which was derived from the original version, OHIP-49.32
Among the 14 questions of OHIP-14, relate to the psychological and behavioral
impact and four address each of the remaining general dimensions. Therefore,
OHIP-14 can be considered one of the best detectors of the psychosocial impact
in a population.