Introduction: Components other than the active
ingredients of treatment can have substantial effe... more Introduction: Components other than the active ingredients of treatment can have substantial effects on pain and disability. Such ‘non-specific’ components include: the therapeutic relationship, the healthcare environment, incidental treatment characteristics, patients’ beliefs and practitioners’ beliefs. This study aims to: identify the most powerful non-specific treatment components for low back pain (LBP), compare their effects on patient outcomes across orthodox (physiotherapy) and complementary (osteopathy, acupuncture) therapies, test which theoretically derived mechanistic pathways explain the effects of non-specific components and identify similarities and differences between the therapies on patient–practitioner interactions. Methods and analysis: This research comprises a prospective questionnaire-based cohort study with a nested mixed-methods study. A minimum of 144 practitioners will be recruited from public and private sector settings (48 physiotherapists, 48 osteopaths and 48 acupuncturists). Practitioners are asked to recruit 10–30 patients each, by handing out invitation packs to adult patients presenting with a new episode of LBP. The planned multilevel analysis requires a final sample size of 690 patients to detect correlations between predictors, hypothesised mediators and the primary outcome (self-reported back-related disability on the Roland-Morris Disability Questionnaire). Practitioners and patients complete questionnaires measuring non-specific treatment components, mediators and outcomes at: baseline (time 1: after the first consultation for a new episode of LBP), during treatment (time 2: 2 weeks post-baseline) and short-term outcome (time 3: 3 months postbaseline). A randomly selected subsample of participants in the questionnaire study will be invited to take part in a nested mixed-methods study of patient–practitioner interactions. In the nested study, 63 consultations (21/therapy) will be audiorecorded and analysed quantitatively and qualitatively.
Introduction: Components other than the active
ingredients of treatment can have substantial effe... more Introduction: Components other than the active ingredients of treatment can have substantial effects on pain and disability. Such ‘non-specific’ components include: the therapeutic relationship, the healthcare environment, incidental treatment characteristics, patients’ beliefs and practitioners’ beliefs. This study aims to: identify the most powerful non-specific treatment components for low back pain (LBP), compare their effects on patient outcomes across orthodox (physiotherapy) and complementary (osteopathy, acupuncture) therapies, test which theoretically derived mechanistic pathways explain the effects of non-specific components and identify similarities and differences between the therapies on patient–practitioner interactions. Methods and analysis: This research comprises a prospective questionnaire-based cohort study with a nested mixed-methods study. A minimum of 144 practitioners will be recruited from public and private sector settings (48 physiotherapists, 48 osteopaths and 48 acupuncturists). Practitioners are asked to recruit 10–30 patients each, by handing out invitation packs to adult patients presenting with a new episode of LBP. The planned multilevel analysis requires a final sample size of 690 patients to detect correlations between predictors, hypothesised mediators and the primary outcome (self-reported back-related disability on the Roland-Morris Disability Questionnaire). Practitioners and patients complete questionnaires measuring non-specific treatment components, mediators and outcomes at: baseline (time 1: after the first consultation for a new episode of LBP), during treatment (time 2: 2 weeks post-baseline) and short-term outcome (time 3: 3 months postbaseline). A randomly selected subsample of participants in the questionnaire study will be invited to take part in a nested mixed-methods study of patient–practitioner interactions. In the nested study, 63 consultations (21/therapy) will be audiorecorded and analysed quantitatively and qualitatively.
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Papers by Laura J. Parry
ingredients of treatment can have substantial effects on
pain and disability. Such ‘non-specific’ components
include: the therapeutic relationship, the healthcare
environment, incidental treatment characteristics,
patients’ beliefs and practitioners’ beliefs. This study
aims to: identify the most powerful non-specific
treatment components for low back pain (LBP),
compare their effects on patient outcomes across
orthodox (physiotherapy) and complementary
(osteopathy, acupuncture) therapies, test which
theoretically derived mechanistic pathways explain the
effects of non-specific components and identify
similarities and differences between the therapies on
patient–practitioner interactions.
Methods and analysis: This research comprises a
prospective questionnaire-based cohort study with a
nested mixed-methods study. A minimum of 144
practitioners will be recruited from public and private
sector settings (48 physiotherapists, 48 osteopaths
and 48 acupuncturists). Practitioners are asked to
recruit 10–30 patients each, by handing out invitation
packs to adult patients presenting with a new episode
of LBP. The planned multilevel analysis requires a
final sample size of 690 patients to detect correlations
between predictors, hypothesised mediators and the
primary outcome (self-reported back-related disability
on the Roland-Morris Disability Questionnaire).
Practitioners and patients complete questionnaires
measuring non-specific treatment components,
mediators and outcomes at: baseline (time 1: after
the first consultation for a new episode of LBP),
during treatment (time 2: 2 weeks post-baseline)
and short-term outcome (time 3: 3 months postbaseline).
A randomly selected subsample of
participants in the questionnaire study will be invited
to take part in a nested mixed-methods study of
patient–practitioner interactions. In the nested
study, 63 consultations (21/therapy) will be audiorecorded
and analysed quantitatively and qualitatively.
ingredients of treatment can have substantial effects on
pain and disability. Such ‘non-specific’ components
include: the therapeutic relationship, the healthcare
environment, incidental treatment characteristics,
patients’ beliefs and practitioners’ beliefs. This study
aims to: identify the most powerful non-specific
treatment components for low back pain (LBP),
compare their effects on patient outcomes across
orthodox (physiotherapy) and complementary
(osteopathy, acupuncture) therapies, test which
theoretically derived mechanistic pathways explain the
effects of non-specific components and identify
similarities and differences between the therapies on
patient–practitioner interactions.
Methods and analysis: This research comprises a
prospective questionnaire-based cohort study with a
nested mixed-methods study. A minimum of 144
practitioners will be recruited from public and private
sector settings (48 physiotherapists, 48 osteopaths
and 48 acupuncturists). Practitioners are asked to
recruit 10–30 patients each, by handing out invitation
packs to adult patients presenting with a new episode
of LBP. The planned multilevel analysis requires a
final sample size of 690 patients to detect correlations
between predictors, hypothesised mediators and the
primary outcome (self-reported back-related disability
on the Roland-Morris Disability Questionnaire).
Practitioners and patients complete questionnaires
measuring non-specific treatment components,
mediators and outcomes at: baseline (time 1: after
the first consultation for a new episode of LBP),
during treatment (time 2: 2 weeks post-baseline)
and short-term outcome (time 3: 3 months postbaseline).
A randomly selected subsample of
participants in the questionnaire study will be invited
to take part in a nested mixed-methods study of
patient–practitioner interactions. In the nested
study, 63 consultations (21/therapy) will be audiorecorded
and analysed quantitatively and qualitatively.