Klingler C, Bertram T, Rogowski WH, Marckmann G. What is personalized
medicine: sharpening a vague term based on a systematic literature review. BMC Medical Ethics 2013, 14:55 doi:10.1186/1472-6939-14-55
Background: Recently, individualized or personalized medicine (PM) has become a buzz word in the academic as well as public debate surrounding health care. However, PM lacks a clear definition and is open to interpretation. This conceptual vagueness complicates public discourse on chances, risks and limits of PM. Furthermore, stakeholders might use it to further their respective interests and preferences. For these reasons it is important to have a shared understanding of PM. In this paper, we present a sufficiently precise as well as adequate definition of PM with the potential of wide acceptance.
Methods: For this
purpose, in a first step a systematic literature review was conducted to
understand how PM is actually used in scientific practice. PubMed was searched
using the keywords “individualized medicine”, “individualised medicine”,
“personalized medicine” and “personalised medicine” connected by the Boolean
operator OR. A data extraction tabloid was developed putting forward a
means/ends-division. Full-texts of articles containing the search terms in
title or abstract were screened for definitions. Definitions were extracted;
according to the means/ends distinction their elements were assigned to the
corresponding category. To reduce complexity of the resulting list, summary
categories were developed inductively from the data using thematic analysis. In
a second step, six well-known criteria for adequate definitions were applied to
these categories to derive a so-called precising definition.
Results: We
identified 2457 articles containing the terms PM in title or abstract. Of those
683 contained a definition of PM and were thus included in our review. 1459
ends and 1025 means were found in the definitions. From these we derived the
precising definition: PM seeks to improve stratification and timing of health
care by utilizing biological information and biomarkers on the level of
molecular disease pathways, genetics, proteomics as well as metabolomics.
Conclusions:
Our
definition includes the aspects that are specific for developments labeled as
PM while, on the other hand, recognizing the limits of these developments.
Furthermore, it is supported by the quantitative analysis of PM definitions in
the literature, which suggests that it it is widely acceptable and thus has the
potential to avoid the above mentioned issues.
Sherman KJ, Eaves ER, Ritenbaugh C, Hsu C, Cherkin DC, Turner JA. Cognitive
interviews guide design of a new CAM patient expectations questionnaire. BMC Complementary and Alternative Medicine
2014, 14:39 doi:10.1186/1472-6882-14-39
ABSTRACT
Background:
No
consistent relationship exists between pre-treatment expectations and
therapeutic benefit from various complementary and alternative medicine (CAM)
therapies in clinical trials. However, many different expectancy measures have
been used in those studies, with no validated questionnaires clearly focused on
CAM and pain. We undertook cognitive interviews as part of a process to develop
and validate such a questionnaire.
Methods: We reviewed
questions about expectations of benefits of acupuncture, chiropractic, massage,
or yoga for pain. Components of the questions - verbs, nouns, response options,
terms and phrases describing back pain - were identified. Using seven different
cognitive interview scripts, we conducted 39 interviews to evaluate how individuals
with chronic low back pain understood these individual components in the
context of expectancy questions for a therapy they had not yet received. Chosen
items were those with the greatest agreement and least confusion among
participants, and were closest to the meanings intended by the investigators.
Results: The
questionnaire drafted for psychometric evaluation had 18 items covering various
domains of expectancy. "Back pain" was the most consistently
interpreted descriptor for this condition. The most understandable response
options were 0-10 scales, a structure used throughout the questionnaire, with 0
always indicating no change, and 10 anchored with an absolute descriptor such
as "complete relief". The use of words to describe midpoints was
found to be confusing. The word "expect" held different and shifting
meanings for participants. Thus paired items comparing "hope" and
"realistically expect" were chosen to evaluate 5 different aspects of
treatment expectations (back pain; back dysfunction and global effects; impact
of back pain on specific areas of life; sleep, mood, and energy; coping).
"Impact of back pain" on various areas of life was found to be a
consistently meaningful concept, and more global than "interference".
Conclusions:
Cognitive
interviews identified wordings with considerable agreement among both
participants and investigators. Some items widely used in clinical studies had
different meanings to participants than investigators, or were confusing to
participants. The final 18-item questionnaire is undergoing psychometric
evaluation with goals of streamlining as well as identifying best items for use
when questionnaire length is constrained.
Yost J, Ciliska D, Dobbins M. Evaluating the impact of an intensive
education workshop on evidence-informed decision making knowledge, skills, and
behaviours: a mixed methods study. BMC
Medical Education 2014, 14:13 doi:10.1186/1472-6920-14-13
ABSTRACT
Background:
Health
professionals require a unique set of knowledge and skills in order to meet
increasing expectations to use research evidence to inform practice and policy
decisions. They need to be able to find, access, interpret, and apply the best
available research evidence, along with information about patient preferences,
clinical expertise, and the clinical context and resources, to such decisions.
This study determined preferences for continuing education following an
intensive educational workshop and evaluated the impact of the workshop on
evidence informed decision making (EIDM) knowledge, skills, and behaviours.
Methods: An
explanatory mixed methods, longitudinal study design was implemented among a
convenience sample of various health care professionals attending the workshop.
EIDM knowledge, skills, and behaviours were quantitatively measured at baseline
and six month follow-up, with EIDM knowledge and skills measured additionally
immediately following the educational workshop (post-test measurement). To determine
participants preferences for continuing education, data were collected using
quantitative survey (post-test measurement) and qualitative (individual
telephone interviews after six-month follow-up) methods.
Results: EIDM
knowledge and skills increased significantly from baseline to immediately
following the intervention [5.6, 95% CI (3.7, 7.4), P < 0.001] and from
baseline to six-month follow-up [3.7, 95% CI (2.1, 5.3), P < 0.001], with a
significant decrease from immediately following the intervention to six-month
follow-up [-1.9, 95% CI (-3.5, -0.3), P 0.018]. EIDM behaviours increased, but
not significantly, from baseline to six-month follow-up [1.7, 95% CI (-0.3,
3.8), P 0.095]. At baseline and six-month follow-up there was a weak,
non-significant positive correlation between EIDM knowledge and skills and EIDM
behaviours (r = 0.29, P 0.069 and r = 0.24, P 0.136, respectively). Over time
there was a shift in preferences for timing and frequency of online continuing
education strategies. Willingness to participate in continuing education,
however, remained evident.
Conclusions:
An intensive
educational workshop shows promise for increasing EIDM knowledge and skills.
Increasing EIDM knowledge and skills may promote the capacity of health
professionals to use research evidence when making practice and policy
decisions and, in turn, lead to positive patient outcomes.
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