INTERVIEW: Jason Silvernail on Low Back Pain

Jason Silvernail Low Back Pain

Chris Beardsley (@SandCResearch) interviews Jason Silvernail (@JasonSilvernail) about low back pain. Jason is a physical therapist, strength & conditioning specialist, and pain science expert.

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Chris: Thanks for the interview, Jason, we really appreciate your time. In your practice, what injury do you most commonly help rehabilitate? What area of research have you found most useful in learning how to help rehabilitate this injury?

Jason: Without a doubt, if you are in conservative musculoskeletal care, this is low back pain. I think being careful with our language is important – I don’t think many cases of this can be called ‘injury’. I prefer to think of what the research calls ‘nonspecific low back pain’ in terms of ‘mechanical back pain’ as a pain condition.

In terms of helpful research, we should be aware of Chekhov’s famous quote, “If there’s any illness for which people offer many remedies, you may be sure that particular illness is incurable, I think.” There are certainly many remedies offered for low back pain. Most of them offer modest or small effects when studied – and the more robust the study the smaller the effect. We can take from this that nothing works for back pain beyond placebo – and there certainly is an argument to be made there – but I don’t think that’s the case.

I think that back pain is such a heterogenous condition that it won’t respond uniformly to any one treatment – but combined treatments have promise if they are low cost, low risk, and noninvasive. I think the recent RCT by Fersum (2013) for a multimodal, education-heavy, graded exercise approach has a lot of promise. I think that’s the future of musculoskeletal rehabilitation – much more attention to beliefs and psychosocial aspects along with a graded type approach for the physical aspects.

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Chris: OK, so low back pain is the big one to tackle. What area of research do you believe is most commonly ignored or misunderstood in the treatment of low back pain or indeed of any injury?

Jason: I think clinicians are still pretty far behind the longstanding and robust research that demonstrates the high prevalence of degenerative changes in the asymptomatic. I don’t think a day goes by in the clinic where I don’t have to deal with a frightened or pessimistic patient whose well-meaning but misinformed health care practitioner has convinced them that their imaging results mean their back is damaged or injured. It feeds into the fear and the natural evolution to invasive and surgical care that reimburses well but doesn’t have a good track record in the literature.

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Chris: What currently unanswered research question would change the way you treat low back pain or injuries in general if it were solved?

Jason: I think we have the data we need to be able change the common treatment of low back pain in our country but we have systematic cultural and environmental structures that interfere with that. We have a huge interlacing web of restricted access to qualified clinicians (namely DPTs), elevated reimbursement for invasive and surgical care whose evidence base isn’t any more impressive than conservative approaches, and a series of perverse incentives that encourage the treatment of back pain with rest, dangerous medications (like opiates), early advanced imaging, and surgical approaches. All of which we know worsen outcomes and all of which have professoinal society standards and recommendations against them. People generally act in ways consistent with their incentives. We are treating back pain in exactly the manner incentivized by our system.

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Chris: Do you have any suggestions for how clinicians can better implement EBP, either in respect of treating low back pain or other injuries?

Jason: Absolutely. I think we need to do three things here. First, you have to know the basic science, then you have to apply a critical thinking process to everything you do, and third you have to limit your specific claims to the published evidence.

You have to know the basic science. Many people have an artificially low bar for treatments to be ‘biologically plausible’ because they don’t know the biology that well! Pain science is a great example of an area that so many clinicians know so little about, and changing that would really change their practice. Also included in this is the published literature. You should be able to recite off the top of your head the major RCTs supporting your general clinical or training process and the literature reviews by major organizations (Cochrane, ACSM, etc.) that inform what you do and why. And if your process is at odds with the evidence you should have a very convincing case prepared as to why you are choosing differently.

You need a critical thinking process to everything you do. Learning cognitive biases and common errors of thinking and rigorously applying them to what you do every day in every way. This takes an investment in time and effort and an intellectual commitment to humility and honesty. I am interested in applying this to what I do, I am much less interested in seeing people apply these concepts to win debates or to score points in arguments – though there is a role for that as well. It must be a personal commitment to self-examination and change.

You really need to limit your claims to just what you can defend with published evidence. Saying one approach is better than another, or one approach is effective for this or that is a specific claim that needs to be backed up with a specific citation of a scientific paper that actually matches what you are claiming. I have seen all kinds of different people make this mistake over the years. If you don’t have a good paper to justify your claim, just be honest and label it as your opinion or experience. Nothing wrong with expert opinion as long as it is humble, open to challenge, and announced as merely a perspective. Be honest with yourself, use claims and testimonials responsibly, and you’d be surprised what that process will teach you about yourself.

Chris: Thank you so much for your time putting these responses together, Jason. We really appreciate your expertise, particularly in respect of the problem of low back pain!

Jason: Thanks for this opportunity, Chris!

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Jason Silvernail is a Doctor of Physical Therapy (DPT), DSc, FAAOMPT. Please follow him on Twitter. The opinons expressed are those of the author only and do not reflect the official policy or position of the US Army, the Department of Defense, or the United States Government.

 

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INTERVIEW: James Steele on Low Back Pain

James Steele Low Back Pain

Chris Beardsley (@SandCResearch) interviews James Steele (@JamesSteeleII), a researcher exploring the causes and effective treatments for low back pain. 

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Chris: James, thank you for taking the time to do this interview. You recently completed your PhD, congratulations Dr Steele! I understand the purpose of your investigation was to advance knowledge on the treatment of chronic low back pain? Please can you outline the nature of this problem, its relation to acute low back pain, and why you decided to tackle it?

Thanks for the kind words Chris, and for inviting me to answer some of your questions. You are correct in that my PhD was intended to further investigate treatment of chronic low back pain. In particular I sought to investigate further the effects of specifically targeting treatment at strengthening the lumbar extensor musculature upon pain, disability and other outcomes commonly associated with chronic low back pain.

Low back pain is a considerable issue for populations worldwide. It has typically been labelled as a modern issue. However, my appraisal of the literature has highlighted it as a widespread issue in a number of populations, both modernised and traditional. Because of its prevalence it evidently puts considerable financial burden on those societies where healthcare systems attempt to address it yet, in addition to that, there is also the considerable personal burden for those suffering from low back pain.

Over recent years clinicians and researchers alike have become more accepting of low back pain as a multifactorial condition. One which is typically associated with a range of factors, though we do not completely understand which are causative or which are resultant of the impact of others. Further, the historical distinction between chronic and acute low back pain does not seem as clear as it has been previously presented either.

Though both acute and chronic instances may be associated with differential factors (e.g. psychosocial issues appear more commonly associated with chronic low back pain), most first-time instances of acute low back pain or low back injury appear to develop into chronic problems. Logically, all chronic pain has to start as acute at some point so although I have focused on the treatment of those suffering chronically within my research, I have attempted to conceptualise low back pain holistically incorporating the interrelatedness of these elements.

Within my PhD research, I chose to focus on a factor which seems to be potentially causative, or at the least consistently associated with low back pain: deconditioning of the lumbar extensor musculature. The intention was to take this aspect and examine its relation with other associated factors by using an intervention specifically designed to address it. The research included examining the effects of addressing this specific factor upon other factors associated with chronic low back pain (including lumbar kinematics during gait and intervertebral disc hydration) as well as the incorporation of the intervention in relation to existing factors (limitations to range of motion).

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Chris: What were your main findings in respect of low back pain and how do you think they will influence clinical practice and rehabilitation?

Some of the research has been published already, other elements of it are currently under review or in the process of being written up. I’ll try to summarise the three areas of study and the findings from those areas.

 

#1. Area one

The first study looked to examine whether limiting the range of motion (ROM) when performing isolated lumbar extension exercise (ILEX) impacted the effects of the intervention upon pain, disability and changes in strength across the full ROM. Previous studies into limited ROM training using this mode of exercise have focused on either flexion or extension portions of the ROM trained.

In this study, based on the fact that persons with low back pain can have issues with both end range flexion and extension, I chose to investigate the effects of a limited ROM training intervention that used the mid portion of the ROM (i.e. the mid two quartiles). In comparison to the control group, both full and limited ROM groups significantly and meaningfully improved pain and disability as well as significantly improving strength across their full ROM. I also found no difference between the full ROM and limited ROM groups for any outcome.

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2. Area two

The second study looked at the relationship between lumbar extensor strength and lumbar kinematics during gait. The first part of this study involved a cross-sectional examination of lumbar extension strength and kinematic parameters relating to the ability of persons with chronic low back pain to control their lumbar spine and replicate their movement patterns during walking.

Previous research indicates a role for the lumbar extensor muscles in controlling the lumbar spine during gait and that weakness of this musculature might impact this. I have just published the results of this stage of this study, where we found that there was a significant moderate correlation between lumbar extension strength and poorer ability to replicate movement patterns during gait.

Following up to this, I implemented the ILEX intervention and looked to see whether there were any improvements. At the end of the intervention, I found that the groups undergoing the ILEX intervention were able to significantly improve their ability to replicate movement patterns at the lumbar spine during gait. Though the clinical relevance of these findings aren’t particularly clear yet, due to the use of newly proposed kinematic analyses, it does provide evidence regarding the role that lumbar extensor deconditioning might play in low back pain as a multifactorial condition. It may be a factor that influences the presence of other factors associated with low back pain, in this case gait dysfunction.

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3. Area three

Finally, I looked to investigate the effects of the ILEX intervention upon the intervertebral discs. Most studies of the intervertebral discs response to loading come from animal model studies. Certainly, I was not able to locate any studies that have examined the response of the discs to a chronic loading intervention such as exercise in vivo.

We recently reviewed the animal literature and it seems as though there is biological plausibility to the hypothesis that the discs respond in a dose-response manner to loading: infrequent, brief, high magnitude loading seems to impart stimulus to potentially regenerative processes in the disc.

As the disc may be a source of pain in low back pain (though certainly not always) and abnormalities are frequently associated with low back pain, examining this factor in response to ILEX seemed appropriate. Ideally, I would have liked to have conducted a study utilising magnetic resonance imaging to directly examine the discs in vivo for changes in a number of factors in response to ILEX. Unfortunately, the timescale for the PhD did not allow the logistic issues associated with this. So as a pilot I decided to use an indirect measure to examine disc hydration: seated spinal height using stadiometery.

Since spinal height varies diurnally and is correlated quite well with changes in disc height, this indicates it might be a suitable measure of disc hydration. In fact, it has been used to examine the acute effects of a number of loading conditions in studies of viscoelastic creep. However, I was concerned about its reliability in this context. So using our own custom setup in the lab, I performed a reliability study to determine the standard error for the measurement before conducting the intervention. That way I could be sure if any difference I found was due to measurement error or not.

To cut a long story short, the measurement, though it appeared reliable in comparison to other studies, did not detect any changes in spinal height after the intervention that were big enough to exceed its standard error. So the findings from the final study indicated either disc hydration did not change in response to the ILEX intervention OR that if there was any change it was not large enough to be detected by the use of seated stadiometery.

As a spoiler for readers – we are in the process of obtaining funding for a larger study to use MRI to investigate this in more detail. Disc hydration is only one of a number of outcomes that might change in response to loading the disc and MRI is better able to examine other factors.

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Chris: Thank you for the great insights into the research process and the dedication to which you pursue finding things out, James. Finally, may I ask what you think are the really important questions that still need to be answered in relation to the rehabilitation of low back pain? How could researchers tackle them?

Obviously, first we need to develop a fuller understanding of the mechanisms of initiation of low back injury and low back pain as well as development of chronicity through prospective longitudinal trials tracking from first instance.

A better understanding of this I believe will assist in choosing both preventative approaches as well as interventions that tackle the appropriate factors in chronic low back pain. However, that being said, there is a lot we don’t really know about the mechanisms through which many rehabilitation approaches work.

Using ILEX as an example, I have speculated that because it specifically addresses the lumbar extensor deconditioning associated with low back pain that this may be a mechanism responsible for it producing improved outcomes such as pain and disability. Indeed, my research has shown that improvements in lumbar extension strength are associated with improved pain and disability. Yet despite this there are likely other mechanisms responsible to varying degrees such as psychosocial or cognitive factors which have also been shown to improve from exercise including early research using ILEX.

A better understanding of the predominant mechanisms through which different rehabilitation approaches can address low back pain would also allow better comparisons to be drawn through RCTs. It would allow us to compare interventions known to address different mechanisms in order to not only compare their efficacy but to also better understand the factors that are predominant issues in chronic low back pain.

That being said, all interventions offer varying degrees of success on an individual basis. Retrospective analysis of demographic and symptom characteristics in order to model those that appear to be best predictive of success with different interventions would be of considerable use to practitioners in prescribing interventions for patients.

Some work has attempted to determine whether such prospective sub-grouping might assist in rehabilitation success. However, this research makes the initial assumption that it works and thus rarely compares oppositely matched sub-groups/interventions. Comparative trials using prospectively defined sub-grouping for different interventions with two groups for each intervention (both matched and unmatched by sub-group) would allow us to understand whether this is a worthwhile aspect of the clinical decision making process. These are the questions that we are looking to work on over the next few years.

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Chris: I very much look forward to reading your work. Do you think your findings have implications for the wider use of resistance-training for strength gains, particularly in respect of ROM?

James: I think we should be careful extrapolating findings from patient groups to the general population. However, the ROM findings may have some implications for wider resistance training application and certainly research.

You have recently reviewed this area yourself Chris regarding both strength and hypertrophy. Most of the studies, with the exception of Pinto et al. (2012) I believe, have only examined limited ROM training with respect to either extremes of the ROM. I am not aware of any other research that attempted to compare full ROM training to limited ROM that just avoids either extremes of the ROM (i.e. trains through the mid-range).

It may well be that such training is similar to full ROM training whereas training that focuses on one limited end of the full ROM may not be as effective. I think further research should look to compare different limited ROM approaches with each other as well as full ROM.

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Chris: I think that would be very interesting to pursue as well, James. Thank you so much for your time!

Please follow James Steele on Twitter for more insight into research into the causes and treatments for low back pain, or view his profile on ResearchGate.

 

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INTERVIEW: Andrew Flatt on HRV

Andrew Flatt HRV

Chris Beardsley (@SandCResearch) interviews Andrew Flatt (@andrew_flatt), a researcher working on Heart Rate Variability (HRV) at the University of Alabama.

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Chris: Thanks for the interview, Andrew, we really appreciate your time. Can you tell us, what exactly are we measuring when we record HRV? What are the main measurements? Do each of these measurements of HRV tell us different things?

Andrew: My pleasure, Chris. This site has been a tremendous resource for me since day one and I am happy to contribute to the great content you provide.

In order to assess heart rate variability (HRV), a recording of beat to beat or “R-R” intervals is required. Subtle changes in heart rate regularly occur in response to respiration where HR tends to speed up during inspiration and slow down during expiration. With various mathematical and statistical procedures, we can quantify and assess heart rate variability.

The human heart is equipped with an intrinsic pacemaker called the sinoatrial (SA) node that when left alone sets heart rate at approximately 75 beats per minute, give or take. However, a component of our central nervous system called the autonomic nervous system largely influences SA node activity and thus heart rate.

Parasympathetic and sympathetic nerves extend from the brain stem and directly innervate the heart. Parasympathetic stimulation (via the vagus nerves) tends to inhibit SA node activity via the release of acetylcholine and therefore reduces heart rate and increases variability. Sympathetic stimulation has the opposite effect where SA node activity is increased via the release of norepinephrine which will speed up heart rate and reduce variability.

Therefore, assessing HRV provides a non-invasive measure of centrally mediated cardiovascular-autonomic control. Though numerous HRV parameters exist, the most commonly assessed for athlete monitoring include:

  • The log transformed root mean square of successive R-R interval differences (lnRMSSD),
  • High frequency spectral power (HF)
  • Low frequency spectral power (LF)
  • The LF to HF ratio (LF:HF)

LnRMSSD and HF are both representative of parasympathetic activity and tend to correlate quite well with each other. What LF reflects is less clear. It was initially thought that LF reflects sympathetic activity and thus LF:HF provides a nice indication of the balance between sympathetic (LF) and parasympathetic (HF) activity. However, this doesn’t appear to be the case. LF is influenced by both parasympathetic and sympathetic activity and particularly by the baroreflex, which functions to help regulate blood pressure. Therefore, what exactly the LF and LF:HF means is not entirely clear.

For athlete monitoring purposes, parasympathetic activity, assessed via RMSSD or HF, is of primary interest for assessing recovery status and physiological adaptation to training.

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Chris: That’s an amazingly comprehensive introduction to HRV, Andrew, thank you. Many reviewers of HRV have recommended using 5 – 10 minutes of resting time for accurate measurements. Do you think shorter measurement durations of HRV can be performed and still tell us something?

Andrew: The topic of HRV recording methodology, specifically as it pertains to measurement duration, has been an area that my colleague Dr. Michael Esco and I have been investigating. Standardized guidelines recommend that a recording period of 5 minutes preceded by a 5-minute stabilization period be used to establish short-term HRV.

These guidelines were primarily developed for clinical/laboratory purposes and assume that a variety of HRV indexes will be included for analysis as some indexes require several minutes for determination (e.g, LF). This may not be a big issue if HRV was assessed only periodically. However, it’s quite clear that daily HRV measures are preferred over weekly, or less frequent measures to be meaningful for athletes. It would therefore be unreasonable for coaches to expect athletes to spend 10 minutes each morning performing an HRV measurement. In light of this, we wanted to determine: a) how short of an HRV recording we get away with that is still valid, and b) how long it takes HRV to stabilize before we should start recording a measure.

To try and answer some of these questions we directed our focus on lnRMSSD. lnRMSSD has been suggested to be the preferred HRV index for athlete monitoring for a variety of reasons. Compared to HF, lnRMSSD is less influenced by breathing rate and provides a lower coefficient of variation across measures, thus making it a more reliable marker. Remember that we have to rely on our athletes to take proper HRV recordings for the data to be useful, so eliminating potential issues such as breathing rate may be helpful.

Since lnRMSSD is a statistical measure, it can be easily calculated in Excel if the R-R interval data is available. In addition, the lnRMSSD is easily interpretable for the end user, particularly when it is modified on a ~100 point scale (done in popular smart phone apps) by simply multiplying the lnRMSSD value by 20. Therefore, when individuals are performing self-measures of HRV at home with a field tool (e.g., smart phone application), the lnRMSSD appears to be the most practical and appropriate.

Our research indicates that lnRMSSD can be accurately assessed in athletes in only 60-seconds and that lnRMSSD stabilization appears to occur within about one minute. This research was done with collegiate athletes and involved ECG measures in the supine position. We are continuing to explore this area with a fellow colleague, Dr. Fabio Nakamura where we are assessing the agreement between 60-second lnRMSSD measures with traditional 5-minute recordings in addition to the time-course for lnRMSSD stabilization.

This work in collaboration with Dr. Nakamura involves elite team sport athletes who self-recorded HRV with a field tool in the seated position. This is an important next step because field tools require less subject preparation for HRV measurement compared to ECG and the seated position may be preferred over supine measures, particularly in highly fit individuals. Based on our recent findings and preliminary analysis from our more current project, I am confident that meaningful HRV data can be collected in much shorter than 10 minutes.

In a recent case study,  we monitored HRV with a smart phone app using a 55-second HRV recording after waking in a seated position in a collegiate endurance athlete. We found that the weekly CV correlated almost perfectly with weekly 8 km race times.

In another case study currently being written up, we found that weekly mean HRV related well to training load during competition preparation in a high level powerlifter with cerebral palsy. HRV was recorded with the same app under the same conditions (i.e., waking, seated). Taken with all of the other data I’ve collected on myself and other athletes I’ve worked with, I’m quite confident that meaningful HRV data can be collected with ultra-short measures and minimal stabilization periods for lnRMSSD.

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Chris: Great insights into HRV, again, thank you Andrew. Interpretation of HRV measurements seems very complex. Do you have any general rules of thumb for what HRV metrics to measure and what different movements mean?

Andrew: The problem with providing general guidelines for HRV interpretation is that this would assume a homogenous group of individuals who do not differ by training level (elite, amateur), age, fitness level, race, gender, sport, exercise modality (resistance training, intervals, steady state) and so forth. HRV responses are largely individual which increases the complexity of interpretation, but at the same time, provides a unique physiological marker to consider when assessing training status and responses.

Some very important review papers on this topic (see references) have been written by researchers who are both athletes and coaches. I would encourage people to read these. Based on the available research and my own experimentation, there are 3 main values that I use for HRV (all of which use lnRMSSD) interpretation with athletes:

  1. Acute or daily HRV change
  2. Weekly mean HRV change
  3. Weekly coefficient of variation (CV) change

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#1. Acute changes

Once a baseline is established (a one-week mean works well for this), it is easy to determine when a daily change is well above or below baseline. Intense training sessions or novel training stimuli (new exercises, set/rep schemes, conditioning, etc.) will generally result in an acute decrease in HRV that can take between 48-72 hours to return to baseline.

Over the course of a training cycle, acute changes will generally become smaller (smaller decrease in HRV, faster return to baseline), which I interpret to mean positive adaptation to the training (more on this below with discussion of CV).

Moderate aerobic exercise tends to have a stimulatory effect on parasympathetic activity and therefore it is common to see increases in HRV 24 hours after this type of exercise and thus has been suggested as an effective active recovery tool.

It’s important to understand however that HRV is sensitive to a wide variety of physical, chemical and psychological stimuli, and therefore an acute HRV measure can be obscured by non-training related stressors. For example, alcohol, poor sleep, nutrition, pharmaceuticals and so forth can all impact HRV.

Therefore, though the acute changes in HRV are meaningful, I would suggest that coaches use caution when trying to determine training prescription solely based on an acute change. Another prime example of this is the anxiety/excitement experienced by athletes on the day of competition which often results in a low HRV score. This certainly does not mean however that they are fatigued or not prepared to perform. Context is very important when interpreting acute changes.

HRV has primarily been researched in endurance athletes. Adjusting training on a daily basis according HRV changes is likely most effective in that population. There has yet to be any research that evaluates HRV guided training for strength/power athletes. An acute increase or decrease in HRV likely will not differentiate strength power/performance except for in obvious situations, like when HRV is low due to heavy drinking the night before, or because of very intense training. In this case, the low HRV score will likely relate to reduced performance.

HRV may still be useful for strength/power athletes, though serving more as a global marker. For example, during overload weeks (high volume resistance training) there will definitely be some HRV changes compared to lower load weeks. The question really is whether HRV data provides any additional useful information that other training load and performance data does not provide. This is an area my colleague and I will explore in the future.

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#2. Weekly mean changes

The weekly mean provides the coach with a simple value that may provide a good indication of the weekly load experienced by the athlete. An increase in the weekly mean for the most part is reflective of positive adaptation or quality recovery.

In some cases however, increases in the weekly mean can be indicative of high fatigue, although this is generally in response to very high volumes of endurance training. Taken into context of the weekly training load and other markers of training status (e.g., wellness, performance), it should be easy to determine if the mean HRV change indicates positive or maladaptive responses.

The weekly mean is influenced by the content of aerobic exercise performed in that week. Moderate to high levels of aerobic work will generally increase mean values (up to a point) since this type of work has that stimulatory effect on parasympathetic activity. Therefore, decreases in a weekly mean value may be reflective of reductions in aerobic activity. Higher intensity exercise can result in greater acute HRV responses decreases and thus effect the weekly mean. Therefore, coaches should use caution when trying to asses fitness based on weekly mean HRV. Again, context is key.

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#3. Weekly CV changes

The CV reflects the variance in HRV scores across the week that is not captured in the weekly mean value. The CV is easily calculated as the standard deviation divided by the mean and expressed as a percentage. Higher CV values indicate higher variance in scores across the week, and lower CV values indicate less variation in scores across the week.

High variation in day to day scores may indicate the fatigue (low scores) and recovery (return to or above baseline) process from a week of training. A higher CV likely reflects a higher training load, or a more stressful week (perhaps due to travel schedules, etc.).

In my experience, a gradual reduction in the CV throughout training is indicative of positive adaptation. In our case study of the collegiate runner, lower CV values were almost perfectly related to his 8km run times, where his worst performances occurred on weeks with the higher CV and his best performances occurred on the weeks with the lowest CV.

In a female collegiate soccer team, we are seeing that CV changes are relating to training load and performance changes. It should be noted that a reduced CV was related to the development of overtraining in an elite female triathlete in a case comparison study by Daniel Plews and colleagues. Therefore, as with each of the other values, the CV must be taken into context.

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Chris: That’s a really helpful how-to guide for HRV measurements, thank you Andrew. Is there any other practical guidance would you offer a coach who was looking to start implementing monitoring HRV measurements with a team of athletes?

Andrew: Here are some final suggestions to coaches who are interested in using HRV with their athletes.

Experiment with a handful of athletes before you try and attempt to implement HRV monitoring with an entire team. This will be much more manageable in terms of data collection and analysis. Consider this a trial run to determine if HRV will be practical in your situation. This includes assessing a) if you think your athletes can reliably perform self-measures at home, and b) if the data you are collecting is actually meaningful.

Don’t start using HRV if you currently do not monitor any other training status markers. For one, HRV is much less meaningful when taken alone. It would be difficult to put an HRV score into context if you do not know what training load (sRPE, tonnage, distance, etc.) was or how wellness scores are evolving. Start with the basics first.

When assessing team HRV data, use the team mean to assess the general responses of the team as a whole. But understand that it is the individual responses that are more important. Some athletes will be responding favorably while others will not. HRV can be useful for helping determine which athletes fall into which category and thus may influence decision making for intervention.

Although smartphone apps conveniently display a nice visual of the HRV trend, you will likely need to also perform some further analysis in Excel, specifically for assessing mean and CV. Most apps have an “export” function that allows you to download a spreadsheet of the data. Specific statistical procedures for determining meaningful changes in HRV from such downloaded data can be found in Martin Buchheit’s paper (see references).

Also, if you want to compare your data from a smartphone download to published lnRMSSD values, you will need to divide your score by 20 (if using the ithlete or BioForce apps). For example, An HRV score of 83 with ithlete or Bioforce is actually an lnRMSSD value of 4.15 (83/20 = 4.15). These values are multiplied by 20 in the smartphone apps to transform the lnRMSSD value to fit onto an approximately 100-point scale for more intuitive interpretation by the casual end user. Also, be sure to note what position HRV is measured in when comparing to published data as supine values will be different than seated or standing values.

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Chris: Thanks for your time, Andrew!

If you are interested in learning more about HRV and would like to contact or follow Andrew Flatt, please follow him on Twitter or check out his blog.

If you would like to do graduate work exploring HRV, the University of Alabama has a dedicated laboratory with the latest equipment, making it the place to go. Contact Andrew on hrvtraining(at)gmail.com for more details.

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References

  1. Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome? Front Physiol (2014); 5.
  2. Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. Training adaptation and heart rate variability in elite endurance athletes: Opening the door to effective monitoring. Sports Med (2013); 43; 773-781.
  3. Stanley, J., Peake, J. M., & Buchheit, M. Cardiac parasympathetic reactivation following exercise: implications for training prescription. Sports Med, 43:1259-1277, 2013.

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INTERVIEW: Michael Hartman on Olympic Weightlifting

Michael Hartman Olympic Weightlifting

Chris Beardsley (@SandCResearch) interviews Michael Hartman (@doctorhartman), a researcher, published author, and S&C coach who has worked on the USA Olympic Weightlifting Performance Enhancement Team.

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Chris: Thanks for the interview, Michael, we really appreciate your time. Considering the research that has been performed into training for the sport of Olympic weightlifting, where do you think the literature is strong and where is it weak?

Michael: The strongest areas of Olympic Weightlifting research are the large amounts of descriptive and analytical data which describes what has happened during a training cycle, competition or the characteristics of high-level competitors. The best examples of these studies are those that measure kinematics of the competition lifts. Researchers are able to collect data related to vertical and horizontal displacement, velocity and acceleration, external mechanical work and power output during the performance of the snatch and clean & jerk.

Similar descriptive data is available for physiological, and biochemical responses following a single sessions or longitudinally across a training program, injury rates from training and competition, and even psychological profiles of high-level competitors.

On the flip side, the research area that is weakest is experimental research related to the training ofOlympic Weightlifting. Very rarely have researchers been able to manipulate the training of athletes in a controlled setting.

Traditional experimental research involves control, randomization, and manipulation to measure outcomes. An independent variable is administered to an experimental group but not to a control group, and both groups are measured on the same results. For several reasons, this type of research is limited as it relates to Olympic Weightlifting. Finding enough qualified athletes to have multiple, homogenous groups is scarce. Even if a subject pool was available, convincing athletes (and coaches) to forego their normal program with extremely limited amount of training time per week and between competitions is difficult.

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Chris: In the weak areas of research into Olympic Weightlifting, what are the important questions that we still need to know answers to? What research could be done that would really drive the sport ofOlympic Weightlifting forwards?

Michael: In my opinion, the greatest research need for the development of high-level Olympic Weightlifting is in the area of skill acquisition. In most countries, athletes come to Olympic Weightlifting fairly late compared to other Olympic sports (i.e. gymnastics, swimming, athletics, etc.) and many times they require a fair amount of remedial work to correct and refine technique. Research that could provide a theoretical framework for the fastest way to correct faulty movement patterns in experienced athletes could be hugely beneficial.

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Chris: To what extent do you think it is valid to draw on the wider resistance-training literature to inform evidence-based programming for Olympic Weightlifting? What are the big limitations with doing this? Is there research in other areas that informs programming for Olympic Weightlifting?

Michael: At the beginner level, it is critical to rely on data from general resistance training. This information provides the foundation of training as it relates to intensity, progression and adaptation. For advanced Olympic Weightlifting athletes, it is important to understand the context of the research before applying the information. Data generated from single joint, isometric contractions may be beneficial in helping our understanding of motor units but in the context of Olympic Weightlifting it is not applicable.

It is also a fairly limited area – but research involving high-level throwers (especially hammer throw) is helpful as it relates to the training and development of Olympic Weightlifting athletes. Similar competition calendars and high force-high velocity sport requirements may help expand the data pool.

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Chris: What guidance can you offer to people who are involved in coaching Olympic Weightlifting to help them identify the best quality evidence and to implement it?

Michael: It is important to identify the subjects used in any research study and first understand if the group studied is applicable to your athletes. Kinematic analysis of world champions is great, but if you are coaching novice athletes is has to be used in context. My best advice is to utilize the published literature as a guide as you develop your athletes. The wealth of descriptive data provides a series of benchmarks that an athlete can reach as they progress through the ranks.

Implementation of any research data is critical and I highly suggest finding appropriate mentorship to improve as a coach. An experienced mentor will be able to assist in terms of feedback and interpreting if ideas from the research literature have application in competitive Olympic Weightlifting athletes.

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Chris: Thanks for your time, Michael! We appreciate your expertise in applying the research to Olympic Weightlifting.

If you would like to contact or follow Michael Hartman and learn more about Olympic Weightlifting, please follow him on Twitter and check out his Amazon author page.

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