Barbell Medicine - From Bench to Bedside

Takeaway: 

Education and exercise are two mainstays for the treatment of persistent pain. However little is known about appropriate dosage of exercise (type, frequency, intensity, time, and duration) for particular pain states. The recent article by Polaski et al further demonstrates our lack of knowledge regarding appropriate exercise dosage for those dealing with persistent pain. However, this shouldn’t be viewed as a negative. Rather, these findings should be encouraging to clinicians to work collaboratively with patients dealing with persistent pain by creating an exercise prescription specific to their goals and based on recent activity history while also fostering long term adherence. 

Introduction

Chronic pain has broadly been defined as persistent or recurrent pain lasting longer than 3 months and is estimated to affect approximately 1.5 billion people worldwide. Treede 2015 Polaski 2019 Education and exercise are two commonly recommended interventions for the treatment of chronic pain. However, little is known about the appropriate dosage of exercise prescription for this population.

In the US, we have physical activity guidelines in place for the general population for overall health benefits (mortality, comorbidities, quality of life, etc), which recommend adults complete aerobic and muscle-strengthening activities each week as follows:

However, since these guidelines are designed for the general population, it is unclear whether they can be generalized to those dealing with persistent pain. If they are not appropriate for this population, how should we alter the dosage?

A recent review by Polaski et al, Exercise-induced hypoalgesia: A meta-analysis of exercise dosing for the treatment of chronic pain, sought to answer these questions and more as they relate to the appropriate dosage of exercise prescription for those dealing with persistent pain. The authors re-examined data from a prior 2017 Cochrane review by Geneen et al, which provided the following clinical implications for practice:

“The evidence in this overview suggests that the broad spectrum of physical activity and exercise interventions assessed here (aerobic, strength, flexibility, range of motion, and core or balance training programmes, as well as yoga, Pilates, and tai chi) are potentially beneficial, though the evidence for benefit is low quality and inconsistent. The most commonly reported adverse events were increased soreness or muscle pain, which subsided after several weeks of the intervention. Physical activity and exercise may improve pain severity as well as physical function and quality of life.”

It appears there was not exactly an overwhelming amount of evidential support for the recommendation of exercise or a particular dosage for individuals with persistent pain.

In this new review article, the authors sought to understand how altering the dose of exercise might affect pain. Their primary objective was to “…test the hypothesis that the dose of exercise would impact the efficacy of exercise and physical movement-based therapy to reduce chronic pain.

Methods

The authors reviewed each included article from the 2017 Cochrane review, which was a comprehensive review of 21 papers from the Cochrane Library Meta-Analyses (381 individual studies) examining the effects of physical activity and exercise interventions on eight pain-based conditions. The included articles met the following criteria:

  1. Randomized, controlled trials 
  2. Adult patients (18+ years of age) 
  3. Chronic non-cancer pain (≥ 3 months in duration)
  4. Meta-analysis reporting post-intervention Effect Sizes (ES) for pain 
  5. Published in peer-reviewed journals

Studies were excluded for the following reasons:

  1. Not in English-language
  2. Multi-modal interventions (exercise A plus exercise B – this would confound the data on exercise dosage, specifically type, effects on pain)
  3. Individualized exercise prescription for each participant in the study (this would diminish the external validity of the review’s findings)
  4. Intervention failed to meet World Health Organization definition of exercise – “Exercise is a subcategory of physical activity that is planned, structured, repetitive, and purposeful in the sense that the improvement or maintenance of one or more components of physical fitness is the objective.

Pain states were classified into eight categories as follows: 

  • Rheumatoid arthritis (RA)
  • Osteoarthritis (OA)
  • Fibromyalgia (FMS)
  • Low Back Pain (LBP)
  • Intermittent Claudication (IC)
  • Neck Pain (NP)
  • Spinal Cord Injury (SCI)
  • Patellofemoral Pain (PFPS)

The authors took the data from included studies in Geneen et al and extracted effect sizes, means, standard deviations, and 95% confidence intervals strictly for the pain outcomes measured immediately post-intervention. The effect sizes demonstrated comparative changes between the exercise and control groups. The authors then converted the effect sizes from mean differences (effect size for each group) or standardized mean differences (experimental vs control groups) to just standardized mean differences (Cohen’s D – which demonstrates the size of an effect exercise dosage has on pain analgesia). The standardized effect sizes were then converted to denote a positive effect value when a reduction in pain occurred. 

Data analyses were based on two factors: 1) Pain outcome measures and 2) Exercise Dosage.

  1. Pain outcome measures
  • Visual Analog Scale (VAS)
  • Numerical Rating Scale (NRS)
  • McGill Pain Questionnaire (MPQ)
  • Arthritis Impact Measurement Scale 2 (AIMS2)
  • Western Ontario McMaster Osteoarthritis index (WOMAC)
  • Short Form-36 Health Survey (SF-36, for bodily pain) 
  • Health Assessment Questionnaire (HAQ)
  • West-Haven Yale Multidimensional Pain Inventory (WHYMPI)

*Authors stated they calculated pain effect sizes based on pain specific sections or subscales from these questionnaires.

2. Exercise Dosage

The authors classified exercise dosage according to frequency, time, and duration. See outline (Fig.1) for descriptions. The authors gave the following example:

Figure 1: Classification of exercise dose.

The authors classified exercise dosage according to frequency, time, and duration. See outline (left) for descriptions. The authors gave the following example:

Prescribed exercise intervention = 3 x / week, 30 minutes a session for 4 weeks 

          • Frequency = 3 
          • Time = 90 minutes
          • Duration = 4 weeks

Note: Intensity of exercise was recorded via a separate analysis and was based on metabolic equivalent of task (MET). MET for each activity was taken from the 2011 Compendium of Physical Activities: a second update of codes and MET values. 

Univariate analyses were initially completed and then multivariate modeling was completed based on trends found from the univariate analyses. 

For univariate analyses, the authors ran linear regressions with Pearson’s Correlation Coefficients based on the standardized pain effect size and dose of exercise for all recorded disease states. Statistical significance was set at p < 0.05. 

Three univariate analyses were completed: 

  1. Pain state – between-study comparisons for the same cohort of pain classification, data were combined across types of exercise interventions.
  2. Exercise type – between-study comparisons for the same cohort of exercise type, data were combined across pain states. 
  3. Intensity – assessed after the above analyses were completed, using a “Dose Intensity x Time” analysis. The authors assessed for interactions between exercise intensity and standardized pain effect size.

Multivariate analysis 

For multivariate analysis, significant results were assessed based on exercise dosage via time, frequency, and duration. The authors explain how they arrived at their multivariate model,

“In order to control for studies that produced significant effect sizes and to model the effects of the three time-related dose measurements simultaneously, multivariate linear regression modeling was fit using a dummy variable for whether the study showed a significant (p<0.05) pain effect or not plus adding the three main effects of measured dose as TIME, FREQUENCY, and DURATION. Two-way interactions between the three measured dose effects were also added to the model. Selection of the best model fit was determined by significant main effects and interaction effects providing an overall significant model F-statistic (p<0.05) and adjusted R2.”

Risk of bias

Risk of bias was assessed via the Review Manager assessment tool from the Cochrane Collaboration. See Figure 2 (above) for a breakdown of the risk of bias for each assessed category. Some assessment categories, like “Blinding of participants and personnel (performance bias)”, are listed as high risk but this was inevitable given the type of interventions utilized and probably could not have been mitigated. 

Findings

The authors included 75 of the original 381 studies from the 2017 Cochrane Review. The primary reasons cited for excluding studies were: not reporting an effect size for a pain related outcome, not reporting the effect size immediately post-intervention, and/or not reflecting the relationship for control vs. exercise group comparison. Overall – the authors found the following:

“Most of the studies included in this review demonstrated some positive benefits of exercise on pain outcomes (69 of 75 studies); of which 30 were statistically significant. Of the statistically non-significant studies, 39 of 45 described positive trending benefits of exercise while only six studies reported worse pain with exercise.”

Granted, “trending towards statistically significant” is voodoo word trickery that isn’t really meaningful beyond trying to support a bias. However, 30 studies of the included 75 did demonstrate statistically significant effect on pain outcomes.

Before diving into the data – a brief overview of Pearson’s Correlation Coefficients.

If you are not familiar with Pearson’s Correlation Coefficient, the measurement is denoted by “r” and describes the strength of a linear relationship between two variables.

Negative, weak correlation shown by negative “R” value that is close to zero.
Positive, strong correlation shown by positive R value that approaches 1.

When a line of best fit is applied to data, the closer r is to +1.0 or -1.0, the more clustered the data points are around the line of best fit with minimal variation, denoting a stronger relationship. Said differently, the closer R is to +1.0 or -1.0, the stronger the data correlates (negatively or positively).

Positive numbers represent a direct, or “upward” trend in the data, and negative numbers represent an inverse, or “downward” trend.

Guidelines have been recommended:

 

Back to the Polaski et al article: 

Univariate Analyses:

1) Pain state analysis – The authors combined the data from all exercise modalities and examined how the dosage affected individual pain states (only NP, FMS, OA, and LBP were included). See table 2 (below). 

Examining table 2 reveals a statistically significant positive correlation for ONLY neck pain as it relates to exercise duration (r = 0.8619, p = 0.0059, n = 8). 

 2) Exercise type analysis – The authors assessed exercise dose effect on pain states. Each exercise type was classified and combined across studies, then effects assessed for pain conditions. The authors then ran a secondary analysis with more specific exercise categories (see table 2).

Surprisingly, the authors found no statistically significant correlations for either analysis as it relates to exercise type and dosage for effects on pain states. 

 3) Intensity analysis – Recall, this analysis was based on METs. METs was combined with exercise time (Intensity x Time) to assess the effect of exercise intensity on pain states (n = 43). Again, the authors found no statistically significant relationship in this analysis.

Multivariate Analysis:

The authors sought to better understand dose effects of exercise (frequency, time, and duration) on pain states by conducting a multivariate analysis. This modeling allows the authors to predict how dose might affect pain outcomes (n = 43). 

The authors found their model accounted for 55.2% of the variation (R2 = .552) in standardized effect size observed. R2 demonstrates the model’s ability to explain variation in the data’s mean for the dependent variable (pain analgesia). 

The model demonstrated that changing dosage of exercise influenced pain outcomes, even for studies not showing a significant effect size. Overall, increasing time of exercise dose decreased analgesic effects and increasing frequency enhanced analgesic effects on pain outcomes. However, it’s important to note that the pain outcomes observed in this model are heavily dependent on the dosage of the other exercise variables and associated interactions.

An example will help illustrate the nuanced interactions of exercise dose variables:

The studies used to develop the model had an average exercise time of 120 minutes/week, average frequency 3 x / week, and average duration of ~15 weeks. Based on the authors’ model, this exercise dosage predicts an effect size of 0.8 for studies demonstrating a significant effect, and 0.04 for those studies failing to demonstrate a significant effect. Although this can be debated, the authors argue that any effect greater than 0 should be considered a positive analgesic effect.

Based on the model, if a single variable of exercise dosage is altered while keeping the other variables consistent to the model – the varying pain effects can be assessed. 

The model suggests that increasing frequency from 3 x / week to 6 x / week increases the pain effect from 0.8 to 1.5 for those studies which already found a significant effect, and from 0.04 to 0.8 for those studies that didn’t find a significant effect. This is an interesting prediction because it increases studies originally not finding a significant effect to the predicted average for studies that did find a significant effect.

However, the opposite can be seen when adjusting the time variable of exercise dosage. The authors predictive model found increasing time from the average of 120 minutes/week to 210 minutes/week had a detrimental effect on pain outcomes reducing the effect to 0.3 in studies that found a significant effect and -0.4 in studies that didn’t find a significant effect. Oddly, if time were decreased to 30 minutes/week the predictive effect was enhanced to 1.2 for significant studies and 0.5 for non-significant studies. If you are interested in further examining the predictive effects of the model by varying exercise dosage, see table 4 in the paper.

Why does this article matter?

Exercise is regularly recommended for many persistent pain states.Skelly 2018 However, we continue to struggle to find appropriate dosage of exercise. The authors of this recent review state “The lack of dosing studies for exercise means that patients may not be receiving the optimal therapy and/or be receiving a therapy that actually increases pain.

Even this most current review, building on the 2017 Cochrane Review, was unable to demonstrate strong correlation of a particular exercise dosage on a pain state. The only positive finding was with a single variable of exercise dosage, duration, on patients dealing with persistent neck pain. The multivariate linear regression model the authors utilized to predict exercise dosage effects on pain outcomes demonstrated how each individual exercise dosage variable can alter outcomes but didn’t elucidate appropriate dosage. In the authors defense – the model does appear to demonstrate analgesic effects on pain states with manipulation of exercise dosage variables, but this is likely to be highly variable to pain states or even between individual patients. In other words, appropriate exercise dosage may not be generalizable beyond the individual patient given their goals and prior activity levels. 

We do know that it’s ok to allow patients dealing with persistent pain to exercise with pain and there may be some short-term benefits in allowing such an approach by decreasing kinesiophobia, instilling self-efficacy, and teaching that pain doesn’t equal tissue damage necessitating avoidance for protection. Smith 2018 Luque-Suarez A 2019 Perhaps it isn’t necessary (or even realistic) to find an optimal, generalizable dosage of exercise for pain states, but rather to find appropriate exercise dosage for the individual based on their desired goals

Similar to recommended national physical activity guidelines, it would be nice to have a starting point that we can confidently state confers some benefit for the patient. Unfortunately, at this time such information isn’t available and we will need further studies on exercise dosage and their associated effects on particular pain states. Until then, I recommend working collaboratively with patients to find exercises they enjoy to meet their goals while eliciting long-term adherence. The authors share this sentiment by advocating for a “low and slow” approach for patients with persistent pain. This suggests that it is likely better to err on the side of caution with patients dealing with persistent pain by starting conservatively with exercise dosage that is likely below their current abilities and progressing from there, rather than risking “overdosing” from the start. Such an approach allows for the accumulation of small “wins” over time, building the patient’s confidence in their abilities and allowing the clinician to gradually titrate dosage to tolerance.

In conclusion, the authors state,

“Overall, this analysis of the existing literature demonstrated insufficient evidence for the presence of dose effects of exercise in relation to analgesia. Ultimately, the major problem in this area is that no studies identified in this analysis individually account for the dose of exercise in the trial. Specific randomized controlled studies with larger n’s, done in specific patient populations, and multiple doses are necessary to determine the effects of exercise dose on the efficacy of exercise for chronic pain conditions.”

The lack of specified dosage for exercise interventions is a major limitation to better understanding the effects of exercise on pain. A specific example is utilizing METs for tracking exercise dosage for resistance training. The authors and myself are aware this isn’t the best metric to utilize. However, the authors cite lacking data on load, volume, rest periods, etc from the primary included studies. This is an important limitation of the included studies as it relates to appropriate exercise dosage of resistance training for those dealing with persistent pain. 

We need future studies to be specific in their exercise dosage, reporting:

  1. Type of exercise (aerobic, resistance, etc)
  2. Frequency (how many sessions per week)
  3. Intensity (subjective and objective measurements specific to the type of exercise)
  4. Time (how long a single session lasts in minutes)
  5. Duration (total time for length of exercise prescription i.e. weeks, months, years)

The accurate tracking and reporting of the above information would likely help with the generalizability of research findings as it relates to this topic. Either way. hopefully the findings from this review help stifle claims that one must do a particular exercise dosage (type, frequency, intensity, time, and duration) to “get themselves out of pain” and rather reframe focus onto finding the patient’s preferred exercise dosage based on activity history and individual goals.

References

  1. Treede R, Rief W, Barke A, et al. A classification of chronic pain for ICD-11 PAIN. 2015;
  2. Polaski AM, Phelps AL, Kostek MC, Szucs KA, Kolber BJ. Exercise-induced hypoalgesia: A meta-analysis of exercise dosing for the treatment of chronic pain. PloS one. 2019; 14(1):e0210418. 
  3. Geneen  LJ, Moore  RA, Clarke C, Martin  D, Colvin LA, Smith BH. Physical activity and exercise for chronic pain in adults: an overview of Cochrane Reviews. Cochrane Database of Systematic Reviews 2017, Issue 4. Art. No.: CD011279. DOI: 10.1002/14651858.CD011279.pub3.
  4. Ainsworth BE, Haskell WL, Herrmann SD, et al. 2011 Compendium of Physical Activities: a second update of codes and MET values. Medicine and science in sports and exercise. 2011; 43(8):1575-81. 
  5. Smith BE, Hendrick P, Smith TO, et al. Should exercises be painful in the management of chronic musculoskeletal pain? A systematic review and meta-analysis Br J Sports Med. 2017; 51(23):1679-1687.
  6. Luque-Suarez A, Martinez-Calderon J, Falla D. Role of kinesiophobia on pain, disability and quality of life in people suffering from chronic musculoskeletal pain: a systematic review. British journal of sports medicine. 2019; 53(9):554-559. 

 

About Michael Ray

Dr. Ray is the founder of Shenandoah Valley Performance Clinic in Harrisonburg, VA. He obtained a M.S. in Exercise Science from the University of South Carolina and graduated Magna Cum Laude with his Doctorate of Chiropractic (D.C.) from Sherman College of Chiropractic.

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