Self Harm in Prisons:

England & Wales

"Understanding how frequently self-harm is followed by suicide, and in which prisoners this progression is most likely to happen, is important." - Hawton, K et al

Self-harm in prisons in England and Wales: an epidemiological study of prevalence, risk factors, 

clustering, and subsequent suicide(2013) 

The Problem

Deaths and self-harm in prison rise sharply, 28 Jan 2016, Owen Bowcott, The Guardian

The number of self-harm incidents, assaults on inmates and deaths in prison all rose sharply last year, according to figures released by the Ministry of Justice.

There were a total of 257 prisoner deaths compared with 153 in 2006. Part of the rise is due to a steady increase in both suicides and killings behind bars; 89 of the deaths in 2015 were self-inflicted. 

Potentially Aggravating Factors

record prison population 

budget cuts

poor performance ratings

closed probation trusts

drop in sex offender treatment programmes 

fewer drug rehabilitation courses

longer terms

indeterminate sentences for public protection

Source: TBC

Part One

ARE WE ASKING

USEFUL QUESTIONS?

We ask, "Who Will Self Harm?"

We can already spot self harmers!  The nomsData highlights repeat self harmers in column -

 Ask not

"Who will self harm?" 

[In accordance with the terms of the hackathon run by the Ministry of Justice, we deleted the column name at the conclusion of the hackathon.]

Ask, "Who is on the verge?"

Which inmates will commit self harm for

the first time?

A justifiable answer to this question requires additional contextual data beyond what is contained within the nomsData

Sample Contextual Approach

Additional Contextual Parameters

• evidence of an underlying drugs culture 

• access to basic amenities, mental healthcare

• efficiency of the ‘app’ (application) system

• the number of dark corners, et al

Also ask, "Who is Suicidal?"

Which self harmers will evenutally

commit suicide?

A robust answer to this question requires longitudinal data not present in the nomsData

Sample Longitudinal Model

A Bayesian approach to look at clustering of people who self-harmed.

Prisoners who self-harmed and subsequently died by suicide in prison can be compared with other inmates who self-harmed

See Hawton et al

Part Two

WHAT CAN THE NOMSDATA TELL US?

Our Hypothesis

The standard profile of a 

self harming, male inmate

points to less useful

variables and characteristics

The Standard Profile

Self-harm is typically associated with the following:

Source: Hawton, H et al

Methodology

Cluster people who self-harm, based on the following additional variables and characteristics

Further Questions

Is there comraderie amongst high incidence self harmers; e.g., group self harming?

Are officers  consistently reporting incidences?

What can be done to ensure clean and consistent data?

Can mental health counseling be broken out by the therapists' approach; e.g., cognitive/behavioural versus postmodern?

A View from the US

According to Human Rights Watch:

• No national or state-wide statistics on the prevalence of self-mutilation in prison
• Self harm is often treated as 'disciplinary issues'
• Self harm is prevalent in segregated, high security settings
• Suicide attempts resulted in being placed naked for days in cold, barren observation cells
• "In 100 percent of cases in about 16 different institutions I have found that successful suicides are preceded by a note in the [medical] chart saying this individual is just malingering or is manipulating or is an antisocial personality; don’t pay any attention." -  Dr. Terry Kupers 

References

Deaths and self-harm in prison rise sharply

Deliberate self-harm in sentenced male prisoners in England and Wales: some ethnic factors

Prison crisis: Cameron brands his own record 'shameful'​

Self-harm in prisons in England and Wales: an epidemiological study of prevalence, risk factors, clustering, and subsequent suicide

Self-Harm: the Unseen Prison Epidemic

Self Harm Categories

In accordance with the terms of the hackathon run by the Ministry of Justice, we deleted the data on this page at the conclusion of the hackathon.

Thank You!

MobiCycle Ltd

info@mobicycle.co.uk