Support road.cc

Like this site? Help us to make it better.

news

Dad stops kid from crashing bike into parked car (+ link to video)

Footage goes viral - after soparking helmet debate

A video of a father dashing after his son to prevent him from crashing his bike into a parked car has been grabbing a l;ot of attention on Reddit - but not for the reason you might think.

 The footage, which you can watch here,  shows the father steadying his son's bike on a quiet suburban street before giving him a little push to help him on his way.

The father is jogging alongside his son as the youngster makes his first pedal strokes - then suddenly sprints into action as the nipper veers towards a parked car.

For many commenting on the video on Reddit, however, the quick-thinking father's prompt action to prevent a crash wasn't the most striking thing about the video, with the first commenter observing, "That kid needs a helmet" - an opinion that inevitably has sparked a debate on the subject.

Simon joined road.cc as news editor in 2009 and is now the site’s community editor, acting as a link between the team producing the content and our readers. A law and languages graduate, published translator and former retail analyst, he has reported on issues as diverse as cycling-related court cases, anti-doping investigations, the latest developments in the bike industry and the sport’s biggest races. Now back in London full-time after 15 years living in Oxford and Cambridge, he loves cycling along the Thames but misses having his former riding buddy, Elodie the miniature schnauzer, in the basket in front of him.

Add new comment

422 comments

Avatar
ClubSmed replied to Rich_cb | 6 years ago
1 like

Rich_cb wrote:
ClubSmed wrote:

I think the issue we are having here is that there are not the historical matching data sets.
I believe that you cannot prove the correlation without them.
You believe that because the exact data sets matches do not exist you can throw any other similar pieces of data to fill the gap.

If you ignore the little details and just use the high level data then that is when you find that sharks are attracted by ice-cream as I mentioned earlier.

Also the "evidence" does not point to a "cyclist specific factor", as the pedestrian fatalities drop at the same rate, but earlier, factors that affects pedestrians earlier than cyclists are just as (or more) likely.

Just to throw another curve ball in here, there was a response to a 2002 study in Canada (data captured 1995-1999 after the introduction of amandatory cycle helmet law) that showed that the risk of head injuries fell, but by around the same number as the number of cyclists fell. It also showed that the risk of other injuries nearly doubled over the same period. This would seem to corroborate other hypothesis that the wearing of safety gear such as helmets make the individual less risk adverse and therefor more likely to take risks that can result in a more serious incident. This could actually point to the initial uptake in helmet wearing being the factor that delays the cyclist fatalities falling in line with the pedestrian decline........

 

The correlation between the rise in helmet use and the fall in cycling fatalities is in time. So you don't need other data. As you rightly said you do need more proof than just correlation. The fact that cycling injuries remained static after the rise in helmet use is evidence against your risk compensation theory. It is also evidence that whatever factor or factors caused the decline in fatalities did not do so by reducing the number of accidents but by reducing the severity of said accidents. The fact that head injuries declined faster amongst cyclists than pedestrians is evidence that there was a factor specific to cyclists. You have the decline in fatalities, the change in injury severity and the specific decline in cyclist head injuries all of which occurred at the same time that helmet use increased. It's not conclusive proof but each separate piece of evidence supports the hypothesis.

There is also a correlation between the rise in Helmet use and the reduction in coronary heart disease and the fall in price of ecstacy tabs but that does not prove a connection or causality.

Where is the evidence of a change in the injury severity, I do not recall seeing this?

I also can't recall the evidence for cycle injuries remaining static whilst head injuries increasing, in fact this data shows that the opposite is true.

 

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

Where is the evidence of a change in the injury severity, I do not recall seeing this?

I also can't recall the evidence for cycle injuries remaining static whilst head injuries increasing, in fact this data shows that the opposite is true.

 

I don't think I said head injuries had increased?

Head injuries decreasing is part of my argument.

KSIs were down while the overall injury rate was static so the proportion of injuries that are severe has decreased.

I'm not sure why you keep going on about spurious correlations.

The different pieces of evidence I've presented all support the hypothesis so it is more detailed than just a simple correlation.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
2 likes

Rich_cb wrote:
ClubSmed wrote:

Where is the evidence of a change in the injury severity, I do not recall seeing this?

I also can't recall the evidence for cycle injuries remaining static whilst head injuries increasing, in fact this data shows that the opposite is true.

 

I don't think I said head injuries had increased? Head injuries decreasing is part of my argument. KSIs were down while the overall injury rate was static so the proportion of injuries that are severe has decreased. I'm not sure why you keep going on about spurious correlations. The different pieces of evidence I've presented all support the hypothesis so it is more detailed than just a simple correlation.

Sorry, I meant decreasing head injuries. The data I found did not show that the cycle casualties per billion miles had decreased, it looks like an increase to me.

The paper you linked to for head injury analysis showed that pedestrian head injuries also significantly decreased over the same period and the subset of cyclists that saw the bigest decrease in head injuries were children and according to the helmet wearing stats you posted they did not show an increase in helmet wearing. How do you explain that?

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

Sorry, I meant decreasing head injuries. The data I found did not show that the cycle casualties per billion miles had decreased, it looks like an increase to me.

The paper you linked to for head injury analysis showed that pedestrian head injuries also significantly decreased over the same period and the subset of cyclists that saw the bigest decrease in head injuries were children and according to the helmet wearing stats you posted they did not show an increase in helmet wearing. How do you explain that?

The data showing a decrease in head injuries covers 1995-2001 when, as your graph shows, the overall injury rate was static.

Pedestrian head injuries did fall but there was a statistically significant difference between the fall in the pedestrian rate and the greater fall in the cyclist rate.

That is evidence of a cyclist specific factor.

As for the data on child cyclists it can't really be interpreted without a control group of child pedestrians. Unfortunately I don't think that data was included in the paper. It would be interesting to see it analysed.

Avatar
FluffyKittenofT... replied to Rich_cb | 6 years ago
3 likes

Rich_cb wrote:

That is evidence of a cyclist specific factor.

 

Or of a pedestrian-specific factor.  Or of multiple factors affecting both.

 

And that's without getting into the question of what 'statistically significant' actually means (it is, after all, rather an abritrary threshold, and nobody really knows what it truly means for something to be 'statistically significant', which is why medical studies in particular seem to be prone to find 'statistically significant' correlations that turn out to not be repeatable, hence all the press headlines about this-or-that causing or preventing cancer)

Avatar
Rich_cb replied to FluffyKittenofTindalos | 6 years ago
0 likes
FluffyKittenofTindalos wrote:

Or of a pedestrian-specific factor.  Or of multiple factors affecting both.

 

And that's without getting into the question of what 'statistically significant' actually means (it is, after all, rather an abritrary threshold, and nobody really knows what it truly means for something to be 'statistically significant', which is why medical studies in particular seem to be prone to find 'statistically significant' correlations that turn out to not be repeatable, hence all the press headlines about this-or-that causing or preventing cancer)

It could be a pedestrian specific factor that makes head injuries more likely in pedestrians.

It could also be a cyclist specific factor that makes head injuries less likely.

It can't be a factor affecting both groups unless it affects one group disproportionately in which case you could argue it was a specific factor anyway.

The fact that the difference exists is therefore evidence of a specific factor at work.

Cycle helmets are a plausible hypothesis to explain the difference.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
2 likes
Rich_cb wrote:
ClubSmed wrote:

Sorry, I meant decreasing head injuries. The data I found did not show that the cycle casualties per billion miles had decreased, it looks like an increase to me.

The paper you linked to for head injury analysis showed that pedestrian head injuries also significantly decreased over the same period and the subset of cyclists that saw the bigest decrease in head injuries were children and according to the helmet wearing stats you posted they did not show an increase in helmet wearing. How do you explain that?

The data showing a decrease in head injuries covers 1995-2001 when, as your graph shows, the overall injury rate was static.

Pedestrian head injuries did fall but there was a statistically significant difference between the fall in the pedestrian rate and the greater fall in the cyclist rate.

That is evidence of a cyclist specific factor.

As for the data on child cyclists it can't really be interpreted without a control group of child pedestrians. Unfortunately I don't think that data was included in the paper. It would be interesting to see it analysed.

So the fact that you can't find the corresponding data set for the children cyclists means we should ignore it because it doesn't fit your hypotheses. All the other data that does fit your hypotheses but doesn't have the corresponding data set we just use the high level data. Is that right?

Actually the study does cover pedestrian children, but it doesn't support your hypotheses:
"A total of 53 207 emergency pedestrian admissions occurred in the six years, of which 13 193 (24.8%) were due to head injury. Pedestrian head injuries declined significantly from 26.9% (n = 2256) in 1995/96 to 22.8% (n = 1792) in 2000/01, an estimated change of –4.94% (95% CI –3.79 to –6.10) (fig 1). The decline was similar among both adults and children, from 24.7% to 21% among adults and 33.2% to 29.2% among children."

As for cycling casualties, if the total number is static, but head injuries have decreased, then that's a rise in all other injuries by my calculations. Am I wrong?

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

So the fact that you can't find the corresponding data set for the children cyclists means we should ignore it because it doesn't fit your hypotheses. All the other data that does fit your hypotheses but doesn't have the corresponding data set we just use the high level data. Is that right?
As for cycling casualties, if the total number of static, but head injuries have decreased, then that's a rise in all other injuries by my calculations. Am I wrong?

No it means I'm basing my hypothesis on the data that is available.

We don't have comparable data by road type so I'm using the data available.

We don't have case-control data for child cyclists so I'm using the data available.

I think you are right about other injuries increasing, we don't know what type of injuries those are.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
1 like
Rich_cb wrote:
ClubSmed wrote:

So the fact that you can't find the corresponding data set for the children cyclists means we should ignore it because it doesn't fit your hypotheses. All the other data that does fit your hypotheses but doesn't have the corresponding data set we just use the high level data. Is that right?
As for cycling casualties, if the total number of static, but head injuries have decreased, then that's a rise in all other injuries by my calculations. Am I wrong?

No it means I'm basing my hypothesis on the data that is available.

We don't have comparable data by road type so I'm using the data available.

We don't have case-control data for child cyclists so I'm using the data available.

I think you are right about other injuries increasing, we don't know what type of injuries those are.

I just updated my post to say that the study does refer to child pedestrians so there is control data:
"A total of 53 207 emergency pedestrian admissions occurred in the six years, of which 13 193 (24.8%) were due to head injury. Pedestrian head injuries declined significantly from 26.9% (n = 2256) in 1995/96 to 22.8% (n = 1792) in 2000/01, an estimated change of –4.94% (95% CI –3.79 to –6.10) (fig 1). The decline was similar among both adults and children, from 24.7% to 21% among adults and 33.2% to 29.2% among children."
How do you a explain that?
As for the other injuries, we don't need to know what they are to see that they support the helmet making cyclists take more risks hypotheses

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

I just updated my post to say that the study does refer to child pedestrians so there is control data:
"A total of 53 207 emergency pedestrian admissions occurred in the six years, of which 13 193 (24.8%) were due to head injury. Pedestrian head injuries declined significantly from 26.9% (n = 2256) in 1995/96 to 22.8% (n = 1792) in 2000/01, an estimated change of –4.94% (95% CI –3.79 to –6.10) (fig 1). The decline was similar among both adults and children, from 24.7% to 21% among adults and 33.2% to 29.2% among children."
How do you a explain that?
As for the other injuries, we don't need to know what they are to see that they support the helmet making cyclists take more risks hypotheses

I did not see that pedestrian data, sorry.

One possible explanation is that children derive more benefit from helmets than adults. There could, of course, be another cycling specific factor affecting the results but the results alone do not disprove the hypothesis that helmets prevent head injury.

The static injury data doesn't necessarily support the hypothesis that helmets increase risk taking.

If a helmet stopped somebody suffering a serious head injury but they still suffered other minor injuries then the data would show no change in overall casualties but the proportion of non head injuries would rise.

There would however have been no increase in the number of accidents and therefore no evidence of increased risk taking.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
2 likes
Rich_cb wrote:
ClubSmed wrote:

I just updated my post to say that the study does refer to child pedestrians so there is control data:
"A total of 53 207 emergency pedestrian admissions occurred in the six years, of which 13 193 (24.8%) were due to head injury. Pedestrian head injuries declined significantly from 26.9% (n = 2256) in 1995/96 to 22.8% (n = 1792) in 2000/01, an estimated change of –4.94% (95% CI –3.79 to –6.10) (fig 1). The decline was similar among both adults and children, from 24.7% to 21% among adults and 33.2% to 29.2% among children."
How do you a explain that?
As for the other injuries, we don't need to know what they are to see that they support the helmet making cyclists take more risks hypotheses

I did not see that pedestrian data, sorry.

One possible explanation is that children derive more benefit from helmets than adults. There could, of course, be another cycling specific factor affecting the results but the results alone do not disprove the hypothesis that helmets prevent head injury.

The static injury data doesn't necessarily support the hypothesis that helmets increase risk taking.

If a helmet stopped somebody suffering a serious head injury but they still suffered other minor injuries then the data would show no change in overall casualties but the proportion of non head injuries would rise.

There would however have been no increase in the number of accidents and therefore no evidence of increased risk taking.

Sorry, I must have missed it when you posted data showing that "children derive more benefit from helmets than adults". Could you repost it please?

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

Sorry, I must have missed it when you posted data showing that "children derive more benefit from helmets than adults". Could you repost it please?

What part of "one possible explanation" are you struggling with?

You are falling back on your previous tactic of demanding data that just doesn't exist.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
4 likes
Rich_cb wrote:
ClubSmed wrote:

Sorry, I must have missed it when you posted data showing that "children derive more benefit from helmets than adults". Could you repost it please?

What part of "one possible explanation" are you struggling with?

You are falling back on your previous tactic of demanding data that just doesn't exist.

I am not struggling with anything, you on the other hand seem to be confusing the meaning of "one possible explanation" with "one plucked out of the air, based on nothing, statement"
If you had said "One possible explanation is that children MIGHT derive more benefit from helmets than adults." I would have understood that you were just thinking out loud, but you did not use the word "might" leaving it to look like a statement of fact that could explain it. So I asked for that data foolishly believing that you were referring back to something you had found and posted on another thread rather than making stuff up.
Nothing wrong with the way I read it, just the way you wrote it.

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

I am not struggling with anything, you on the other hand seem to be confusing the meaning of "one possible explanation" with "plucked out of the air, based on nothing, statement"
I asked for that data because I foolishly believed that you were referring back to something you had found and posted on another thread rather than making stuff up.

Is it a possible explanation?

Yes.

It doesn't change the overall picture anyway. The group that wore helmets showed a significantly greater decline in serious head injury rate than the non helmet wearing group.

That's the pattern you'd expect to see if helmets reduced head injuries.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
2 likes
Rich_cb wrote:
ClubSmed wrote:

I am not struggling with anything, you on the other hand seem to be confusing the meaning of "one possible explanation" with "plucked out of the air, based on nothing, statement"
I asked for that data because I foolishly believed that you were referring back to something you had found and posted on another thread rather than making stuff up.

Is it a possible explanation?

Yes.

It doesn't change the overall picture anyway. The group that wore helmets showed a significantly greater decline in serious head injury rate than the non helmet wearing group.

That's the pattern you'd expect to see if helmets reduced head injuries.

Is it a possible explanation? It has had about the same amount of research and thought (probably less) put into it as the One Direction theory.

What picture are you seeing? The one I'm seeing shows that the group of cyclists with no change in helmet wearing trends (children) showed the greater decline in head injuries.

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

Is it a possible explanation? It has had about the same amount of research and thought (probably less) put into it as the One Direction theory.

What picture are you seeing? The one I'm seeing shows that the group of cyclists with no change in helmet wearing trends (children) showed the greater decline in head injuries.

It is a possible explanation but it's also a needless distraction.

The difference between the data for adults and children is interesting.

The TRL noted that they found far higher rates of helmet wearing amongst children on recreational routes than on roads.

If there has been a trend towards children cycling more miles on such routes and fewer on the roads it could explain the discrepancy as the helmet wearing rate for children would have been underestimated.

The research definitely points to a cycling specific factor for both children and adults but the evidence for helmets is stronger for adults than children.

Avatar
Helmut D. Bate replied to Rich_cb | 6 years ago
6 likes

Rich_cb wrote:

The group that wore helmets showed a significantly greater decline in serious head injury rate than the non helmet wearing group.

No.

If you take most periods that fall within the range of your graph, there is either a bigger fall among pedestrian deaths, or a 90s variation that you're pinning your entire argument on. That's the eyeball test that everyone is doing. Why don't you put the figures into a stats package and post the results? Let's see a trend analysis. We can all see it but maybe if R or maybe even Excel told you, you would listen.

You're aligning variation in the overall trend with a helmet increase in another graph, but that helmet wearing graph doesn't cover the same period. You might tell yourself that that variation is statistically significant - and it might be. But the link to the increase in helmet wearing is not established. The crucial question: what happens with the helmet wearing trend prior to your graph? I'm going to make the most logical assumption that the trend continues to the left of your graph, which smooths the spike and damages your argument. Now it's back on you to show that that assumption is incorrect.

As it is, you're not just comparing apples with oranges, you're trying to compare them using two different scales too. You're truncating the larger, central dataset and fitting it to your hypothesis dataset, rather than get the correct dataset for your hypothesis. Can you see that that is THE WRONG WAY ROUND? Shrugging your shoulders and saying that's all you've got is admitting defeat, not winning the argument.

You don't yet have the data to draw a significant correlation - much less, the evidence for cause/effect - to make your claim. Get better data, or stop making the claim.

Avatar
Rich_cb replied to Helmut D. Bate | 6 years ago
0 likes
Helmut D. Bate wrote:

Rich_cb wrote:

The group that wore helmets showed a significantly greater decline in serious head injury rate than the non helmet wearing group.

No.

If you take most periods that fall within the range of your graph, there is either a bigger fall among pedestrian deaths, or a 90s variation that you're pinning your entire argument on. That's the eyeball test that everyone is doing. Why don't you put the figures into a stats package and post the results? Let's see a trend analysis. We can all see it but maybe if R or maybe even Excel told you, you would listen.

You're aligning variation in the overall trend with a helmet increase in another graph, but that helmet wearing graph doesn't cover the same period. You might tell yourself that that variation is statistically significant - and it might be. But the link to the increase in helmet wearing is not established. The crucial question: what happens with the helmet wearing trend prior to your graph? I'm going to make the most logical assumption that the trend continues to the left of your graph, which smooths the spike and damages your argument. Now it's back on you to show that that assumption is incorrect.

As it is, you're not just comparing apples with oranges, you're trying to compare them using two different scales too. You're truncating the larger, central dataset and fitting it to your hypothesis dataset, rather than get the correct dataset for your hypothesis. Can you see that that is THE WRONG WAY ROUND? Shrugging your shoulders and saying that's all you've got is admitting defeat, not winning the argument.

You don't yet have the data to draw a significant correlation - much less, the evidence for cause/effect - to make your claim. Get better data, or stop making the claim.

Seriously?

Read the paper that I posted.
That's where that conclusion is from.

There isn't enough data to prove causation and I've never said there is, the data that is available does support the hypothesis that helmets are reducing head injury/death.

You might not like that but that doesn't make it wrong.

Avatar
Helmut D. Bate replied to Rich_cb | 6 years ago
0 likes

Rich_cb wrote:
Helmut D. Bate wrote:

Rich_cb wrote:

The group that wore helmets showed a significantly greater decline in serious head injury rate than the non helmet wearing group.

No. If you take most periods that fall within the range of your graph, there is either a bigger fall among pedestrian deaths, or a 90s variation that you're pinning your entire argument on. That's the eyeball test that everyone is doing. Why don't you put the figures into a stats package and post the results? Let's see a trend analysis. We can all see it but maybe if R or maybe even Excel told you, you would listen. You're aligning variation in the overall trend with a helmet increase in another graph, but that helmet wearing graph doesn't cover the same period. You might tell yourself that that variation is statistically significant - and it might be. But the link to the increase in helmet wearing is not established. The crucial question: what happens with the helmet wearing trend prior to your graph? I'm going to make the most logical assumption that the trend continues to the left of your graph, which smooths the spike and damages your argument. Now it's back on you to show that that assumption is incorrect. As it is, you're not just comparing apples with oranges, you're trying to compare them using two different scales too. You're truncating the larger, central dataset and fitting it to your hypothesis dataset, rather than get the correct dataset for your hypothesis. Can you see that that is THE WRONG WAY ROUND? Shrugging your shoulders and saying that's all you've got is admitting defeat, not winning the argument. You don't yet have the data to draw a significant correlation - much less, the evidence for cause/effect - to make your claim. Get better data, or stop making the claim.

Seriously? Read the paper that I posted. That's where that conclusion is from. There isn't enough data to prove causation and I've never said there is, the data that is available does support the hypothesis that helmets are reducing head injury/death. You might not like that but that doesn't make it wrong.

 

Oh OK: we've moved on from those first graphs then...

With all the time you spend on these threads, could you not just crunch it all together in Excel and post that?

Avatar
Rich_cb replied to Helmut D. Bate | 6 years ago
0 likes
Helmut D. Bate wrote:

Oh OK: we've moved on from those first graphs then...

With all the time you spend on these threads, could you not just crunch it all together in Excel and post that?

As I've said multiple times I can't prove causation.

If it was possible to draw all the data together and statistically analyse it I would have done.

I've posted links to the statistical analysis that has been done.

Avatar
Bluebug replied to Rich_cb | 6 years ago
2 likes
Rich_cb wrote:
ClubSmed wrote:

Sorry, I must have missed it when you posted data showing that "children derive more benefit from helmets than adults". Could you repost it please?

What part of "one possible explanation" are you struggling with?

You are falling back on your previous tactic of demanding data that just doesn't exist.

Then why make conclusions like that from it?

Anyway your entire method of doing statistical analysis is wrong.

You do realise you have p*ssed off people who do wear helmets as well as those who don't simply because of your poor statistical analysis.

Avatar
Rich_cb replied to Bluebug | 6 years ago
0 likes
Bluebug wrote:
Rich_cb wrote:
ClubSmed wrote:

Sorry, I must have missed it when you posted data showing that "children derive more benefit from helmets than adults". Could you repost it please?

What part of "one possible explanation" are you struggling with?

You are falling back on your previous tactic of demanding data that just doesn't exist.

Then why make conclusions like that from it?

Anyway your entire method of doing statistical analysis is wrong.

You do realise you have p*ssed off people who do wear helmets as well as those who don't simply because of your poor statistical analysis.

I've already addressed that point. That was a possible suggestion to explain the variation, maybe I could have worded it more specifically by I clarified afterwards.

The statistical analysis I've referred to is from a published study in a respected journal.

Avatar
Bluebug replied to Rich_cb | 6 years ago
7 likes

Rich_cb wrote:
Bluebug wrote:
Rich_cb wrote:
ClubSmed wrote:

Sorry, I must have missed it when you posted data showing that "children derive more benefit from helmets than adults". Could you repost it please?

What part of "one possible explanation" are you struggling with? You are falling back on your previous tactic of demanding data that just doesn't exist.

Then why make conclusions like that from it? Anyway your entire method of doing statistical analysis is wrong. You do realise you have p*ssed off people who do wear helmets as well as those who don't simply because of your poor statistical analysis.

I've already addressed that point. That was a possible suggestion to explain the variation, maybe I could have worded it more specifically by I clarified afterwards. The statistical analysis I've referred to is from a published study in a respected journal.

The Lancet is a respected journal and they still published that the MMR vaccine causes autism.  Further analysis found the methodology was completely flawed, the author is no longer a medical doctor, and it has caused and is still causing major worldwide health scares.

The BMJ is a respected journal and still have been pressurised to publish that statins are good for everyone and greatly prolong life.  Further analysis of data by different people has found this stance is flawed and the arguments are still ongoing.

The point I'm making is don't take other people's statistical analysis at face value even from respected journals. 

 

 

Avatar
Rich_cb replied to Bluebug | 6 years ago
0 likes
Bluebug wrote:

The Lancet is a respected journal and they still published that the MMR vaccine causes autism.  Further analysis found the methodology was completely flawed, the author is no longer a medical doctor, and it has caused and is still causing major worldwide health scares.

The BMJ is a respected journal and still have been pressurised to publish that statins are good for everyone and greatly prolong life.  Further analysis of data by different people has found this stance is flawed and the arguments are still ongoing.

The point I'm making is don't take other people's statistical analysis at face value even from respected journals. 

 

 

Nobody said that journals were infallible but respected journals are a hell of a lot more trustworthy than most sources of information.

Avatar
ClubSmed replied to Rich_cb | 6 years ago
2 likes
Rich_cb wrote:

One possible explanation is that children derive more benefit from helmets than adults. There could, of course, be another cycling specific factor affecting the results but the results alone do not disprove the hypothesis that helmets prevent head injury.

Nothing about the above post suggests that the statement "children derive more benefit from helmets than adults" isn't being presented by you as a fact!

Rich_cb wrote:

The static injury data doesn't necessarily support the hypothesis that helmets increase risk taking.

If a helmet stopped somebody suffering a serious head injury but they still suffered other minor injuries then the data would show no change in overall casualties but the proportion of non head injuries would rise.

There would however have been no increase in the number of accidents and therefore no evidence of increased risk taking.

Good point, but the number of "helmet saved life and I walked away unscathed" stories would suggest otherwise. What you would need here to disprove the more risk taking theory is data on the other injuries patients with head injuries pre-1995 had and if they would warrant hospital admission

Avatar
ClubSmed replied to Rich_cb | 6 years ago
4 likes

Rich_cb wrote:
ClubSmed wrote:

So the fact that you can't find the corresponding data set for the children cyclists means we should ignore it because it doesn't fit your hypotheses. All the other data that does fit your hypotheses but doesn't have the corresponding data set we just use the high level data. Is that right? As for cycling casualties, if the total number of static, but head injuries have decreased, then that's a rise in all other injuries by my calculations. Am I wrong?

No it means I'm basing my hypothesis on the data that is available. We don't have comparable data by road type so I'm using the data available. We don't have case-control data for child cyclists so I'm using the data available. I think you are right about other injuries increasing, we don't know what type of injuries those are.

Let's be honest here, I very much doubt that you have based your hypothesis on the data that is available. I find it far more likely that you had a belief that cycle helmets reduced cycling fatalities and went out in search of data that you believed proved this point. Attempting to make out that you are some neutral entity that just decided to look at all the data available and draw a hypotheses from it is not likely. Especialy given that the corresponding child pedestrian data was available yet your hypothesis did not change.

Avatar
Rich_cb replied to ClubSmed | 6 years ago
0 likes
ClubSmed wrote:

Let's be honest here, I very much doubt that you have based your hypothesis on the data that is available. I find it far more likely that you had a belief that cycle helmets reduced cycling fatalities and went out in search of data that you believed proved this point. Attempting to make out that you are some neutral entity that just decided to look at all the data available and draw a hypotheses from it is not likely. Especialy given that the corresponding child pedestrian data was available yet your hypothesis did not change.

And what exactly is your hypothesis?

That there is absolutely no difference between the injuries suffered by pedestrians and cyclists?

What evidence have you based your position on?

Avatar
FluffyKittenofT... replied to Rich_cb | 6 years ago
2 likes

Rich_cb wrote:
ClubSmed wrote:

Let's be honest here, I very much doubt that you have based your hypothesis on the data that is available. I find it far more likely that you had a belief that cycle helmets reduced cycling fatalities and went out in search of data that you believed proved this point. Attempting to make out that you are some neutral entity that just decided to look at all the data available and draw a hypotheses from it is not likely. Especialy given that the corresponding child pedestrian data was available yet your hypothesis did not change.

 

And what exactly is your hypothesis? That there is absolutely no difference between the injuries suffered by pedestrians and cyclists? What evidence have you based your position on?

 

Perhaps their position is that there isn't any good evidence on which to base a position, therefore the matter should be left up to individual choice?  And that those who have a dogged and fanatical commitment to a pro-helmet stance despite that absence of evidence, might have some sort of pre-existing bias?

Avatar
ClubSmed replied to Rich_cb | 6 years ago
1 like

Rich_cb wrote:
ClubSmed wrote:

Let's be honest here, I very much doubt that you have based your hypothesis on the data that is available. I find it far more likely that you had a belief that cycle helmets reduced cycling fatalities and went out in search of data that you believed proved this point. Attempting to make out that you are some neutral entity that just decided to look at all the data available and draw a hypotheses from it is not likely. Especialy given that the corresponding child pedestrian data was available yet your hypothesis did not change.

 

And what exactly is your hypothesis? That there is absolutely no difference between the injuries suffered by pedestrians and cyclists? What evidence have you based your position on?

I do not have any hypothesis based on the data available. What I do have is a belief based on nothing more than my own perception of personal experiences. That belief is that cycle helmets help reduce harm in most cycling collisions which I am likely to find myself and that is why I wear a helmet.
There is no compelling evidence to support either for or against argument, I wish there was then I would know which way I need to go to keep myself and my loved ones safest. Until that happens I am in the cycle helmet wearing camp but I am happy for others to make their own choice based on whatever belief system they have.

Avatar
davel replied to Rich_cb | 6 years ago
2 likes
Rich_cb wrote:
Jimmy Ray Will wrote:

Is this for real?

 

The graphs, more or less, show a very similar trend. Ok, at certain points one is decreasing faster than the other, but generally speaking they follow a very similar trend. 

Therefore, to me at least, it would appear unarguable to use these graphs as demonstration of helmet use reducing numbers. 

The only way this would be potentially useable is if cycling casualty numbers had reduced significantly greater than pedestrian, as then there would be an unexplained influencer. However this is not the case. 

There is no need to provide a counter argument as you have failed, in my opinion at least, to present a plausible argument. 

 

Explain the pre 1995 figures.

We don't have to.

Being able to explain the ped difference doesn't defeat your argument.

Your fallacious logic defeats your argument.

Pages

Latest Comments