Self-Harm Inventory
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Self-Harm Inventory

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Purpose

A 22-item self-report questionnaire that assesses patients’ history of self-harm behaviors.

Link to Instrument

Instrument Details

Acronym SHI

Area of Assessment

Mental Health
Depression
Negative Affect
Stress & Coping

Assessment Type

Patient Reported Outcomes

Administration Mode

Paper & Pencil

Cost

Free

Actual Cost

$0.00

Populations

Healthy Adults
Non-Specific Patient Population
Mixed Populations
Mental Health

Key Descriptions

  • Each item requires a “yes” or “no” response.
  • The SHI is scored by counting a point for every “yes” response.
  • Scores range from 0, indicating no self-harm behavior, to 22, indicating every self-harm behavior addressed in the inventory.

Number of Items

22

Equipment Required

  • None

Time to Administer

5 minutes

Required Training

No Training

Age Ranges

Adult

18 - 64

years

Older adult

+

years

Instrument Reviewers

Allison C Johnson

Zhemeng Cui

Reina Yano

ICF Domain

Activity

Measurement Domain

General Health
Emotion

Considerations

  • The SHI may function as a useful screening tool in large mental health clinics or in settings where the prevalence of Borderline Personality Disorder is fairly high.
  • The SHI is available in English, German, and Dutch.

Mental Health

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Cut-Off Scores

Participants involuntarily hospitalized in a psychiatric facility: (Sansone et. al, 1998; N = 32; 50% female; mean (SD) age = 36.2 (13.33) years)

 

    • Scores greater than or equal to 5 on the SHI are indicative of Borderline Personality Disorder. The SHI was 78.1% correct in classifying all research participants (Kappa = .33).
      • The SHI was 60% correct in classifying research participants without Borderline Personality Disorder.
      • The SHI was 81.5% correct in classifying research participants with Borderline Personality Disorder according to the DSM-IV criteria.

Normative Data

Participants with Borderline Personality Disorder: (Sansone et. al, 2008; N = 120; 61% female; mean age (SD) = 38.69 (11.74) years; 81.5% White, 15.1% Black, 1.7% Native American, 0.8% Asian, 0.8% race not otherwise specified)

 

  • Mean (SD) score: 7.41 (4.82)

 

Participants involuntarily hospitalized in a psychiatric facility: (Sansone et. al, 1998; N = 32; 50% female; mean (SD) age = 36.2 (13.33) years)

 

  • Mean (SD) scores of participants with Borderline Personality Disorder: 8.48 (4.11)
  • Mean (SD) scores of participants without Borderline Personality Disorder: 3.80 (2.17)

 

Inpatient Psychiatric Sample: (Selbom et al. 2017, N = 145; 61% female; mean (SD) age = 38.06 (13.06) years; 73.6% White participants, 16% Black, 10.1% race not otherwise specified; 64.3% of participants reported at least one previous psychiatric hospitalization)

  • Mean (SD) score: 7.31 (4.80)

Internal Consistency

Inpatient Psychiatric Sample: (Selbom et al. 2017, N = 145; 61% female; mean (SD) age = 38.06 (13.06) years; 73.6% White participants, 16% Black, 10.1% race not otherwise specified; 64.3% of participants reported at least one previous psychiatric hospitalization)

 

Excellent internal consistency (Cronbach’s alpha = 0.84)

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

 

Participants with Borderline Personality Disorder: (Sansone et. al, 2008; N = 120; 61% female; mean age (SD) = 38.69 (11.74) years; 81.5% White, 15.1% Black, 1.7% Native American, 0.8% Asian, 0.8% race not otherwise specified)

  • Adequate correlation between SHI scores and self-reported numbers of medically self-sabotaging behaviors (r = .55)

 

Participants involuntarily hospitalized in a psychiatric facility: (Sansone et. al, 1998; N = 32; 50% female; mean (SD) age = 36.2 (13.33) years)

Excellent correlation between SHI and PDQ-R scores (r = 0.71)

 

Construct Validity

Convergent validity:

Inpatient Psychiatric Sample: (Selbom et al. 2017, N = 145; 61% female; mean (SD) age = 38.06 (13.06) years; 73.6% White participants, 16% Black, 10.1% race not otherwise specified; 64.3% of participants reported at least one previous psychiatric hospitalization)

 

  • Excellent correlation between SHI and PDQ-4 scores (r = 0.62)
  • Excellent correlation between SHI and SCID-2-PQ scores (r = 0.70)
  • Excellent correlation between SHI and MSI-BPD scores (r = 0.68)

Non-Specific Patient Population

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Cut-Off Scores

Development Study: (Sansone et. al, 1998; N = 221; primary care setting; 28% consulted for obesity, 51% for eating disorders or substance abuse, 19% for other non-emergency concerns)

    • “Using a cutoff score of 5 on the SHI appears to best balance diagnostic sensitivity with false-identification of BPD.”
    • “Using a cutoff score of 5 on each measure resulted in… a Kappa of .61 for the SHI.”

Normative Data

Development Study: (Sansone et. al, 1998; N = 221; primary care setting; 28% consulted for obesity, 51% for eating disorders or substance abuse, 19% for other non-emergency concerns)

  • Mean (SD) for participants with Borderline Personality Disorder: 10.15 (4.57)
  • Mean (SD) for participants without Borderline Personality Disorder: 2.30 (2.51)

Internal Consistency

Development Study: (Sansone et. al, 1998; N = 221; primary care setting; 28% consulted for obesity, 51% for eating disorders or substance abuse, 19% for other non-emergency concerns)

  • Excellent internal consistency (Cronbach’s alpha = 0.80)

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

 

Development Study: (Sansone et. al, 1998; N = 221; primary care setting; 28% consulted for obesity, 51% for eating disorders or substance abuse, 19% for other non-emergency concerns)

  • Excellent correlation between SHI and PDQ-R scores (r = .74)
  • Excellent correlation between SHI and DIB scores (r = .76)
    • Distribution of SHI Scores and their relationship to a Borderline Personality Disorder diagnosis by the DIB:

SHI Score

BPD Diagnosis

n (%)

No BPD diagnosis

n (%)

0

0 (0)

62 (36.9)

1

1 (1.9)

17 (10.1)

2

1 (1.9)

27 (16.1)

3

2 (3.8)

12 (7.1)

4

2 (3.8)

20 (11.9)

5

5 (9.4)

7 (4.2)

6

1 (1.9)

9 (5.4)

7

4 (7.5)

6 (3.6)

8

1 (1.9)

4 (2.4)

9

7 (13.2)

3 (1.8)

10 or greater

29 (54.7)

1 (0.06)

Total N

53 (100)

168 (100)

Content Validity

Development Study: (Sansone et. al, 1998; N = 221; primary care setting; 28% consulted for obesity, 51% for eating disorders or substance abuse, 19% for other non-emergency concerns)

  • “The proportion of respondents who endorsed each of the 22 remaining SHI items ranged from a low of 4.7% for item ‘burned yourself’, to a high of 37.6% for the item ‘abused alcohol’.”

Healthy Adults

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Cut-Off Scores

Non-clinical Population: (Latimer et al. 2009; N = 423; 81% female; 53% between 17-19 years, 27% between 20-30 years; Australian undergraduate students)

  • ≥ 5 is indicative of Borderline Personality Disorder (sensitivity 88.7%, specificity 82.1%)

Normative Data

Non-Clinical Population: (Latimer et al. 2009; N = 423; 81% female; 53% between 17-19 years, 27% between 20-30 years; Australian undergraduate students)

  • Mean (SD) = 5.16 (3.6)
  • Female participants endorsed more items than male participants.
    • Mean (SD) scores for female participants: 5.75 (3.75)
    • Mean (SD) scores for male participants: 4.31 (2.79)
  • Older participants (20-30 years) endorsed more items than younger participants (17-19 years).
    • Mean (SD) scores for older participants: 6.08 (3.92)
    • Mean (SD) scores for younger participants: 4.39 (3.34)

General Population: (Müller et al., 2016; N = 2,507; 56% female; German participants)

  • 48% of participants endorsed at least one SHI item.
    • Mean (SD) scores for men: 1.33 (2.03)
    • Mean (SD) scores for women: 1.20 (2.05)

Internal Consistency

General Population: (Müller et al., 2016; N = 2,507; 56% female; German participants)

  • Adequate internal consistency (Cronbach’s alpha = 0.78)
  • Adequate internal consistency among male participants (Cronbach’s alpha = 0.75)
  • Excellent internal consistency among female participants (Cronbach’s alpha = 0.80)

Criterion Validity (Predictive/Concurrent)

 

Concurrent validity:

 

Non-Clinical Population: (Latimer et al. 2009; N = 423; 81% female; 53% between 17-19 years, 27% between 20-30 years; Australian undergraduate students)

  • Excellent correlation with the DIB (r = 0.76)
  • Excellent correlation with the PDQ-R (r = 0.73)

 

General Population: (Müller et al., 2016; N = 2,507; 56% female; German participants)

  • Poor correlation between SHI and BIS-15 scores (Spearman correlation = 0.23)
    • Poor correlation for male participants (Spearman correlation = 0.26)
    • Poor correlation for female participants (Spearman correlation = 0.20)
  • Adequate correlation between SHI and PHQ-4 scores (Spearman correlation = 0.37)
    • Adequate correlation for male participants (Spearman correlation = 0.36)
    • Adequate correlation for female participants (Spearman correlation = 0.40)

 

Construct Validity

Convergent validity:

 

Non-Clinical Population: (Latimer et al. 2009; N = 423; 81% female; 53% between 17-19 years, 27% between 20-30 years; Australian undergraduate students)

  • Relationship between SHI scores and depression, anxiety, and stress scores on the DASS-21 for participants who endorsed at least one item:

SHI scores

Mean (SD) depression scores

Mean (SD) anxiety scores

Mean (SD) stress scores

Low (1-4)

9.53 (8.15)

7.09 (6.53)

11.67 (6.40)

Medium (5-10)

11.58 (8.60)

11.41 (8.24)

16.52 (9.22)

High (11 or higher)

17.00 (10.51)

16.86 (11.39)

23.29 (9.53)

Mixed Populations

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Cut-Off Scores

Meta-analysis: (Sansone et al., 2015)

  • “the SHI demonstrated an accuracy in diagnosis of 84% at a cut-off score of 5, and 85% and 88% at cut-off scores of 6 and 7, respectively”

Test/Retest Reliability

Meta-analysis: (Sansone et al., 2015)

  • Adequate test-retest reliability of psychiatric inpatient samples (ICC = .61)
  • Adequate test-retest reliability of internal medicine outpatient samples (ICC = .68)

Internal Consistency

Meta-analysis: (Sansone et al., 2015)

  • Excellent internal consistency (Cronbach’s alpha = .85)

Bibliography

Latimer, S; Covic, T; Cumming, Sr; Tennant, A. (2009). Psychometric analysis of the Self-Harm Inventory using Rasch modelling. BMC Psychiatry, 2009 Aug 19, Vol.9 DOI: 10.1186/1471-244X-9-53

Latimer, S., Meade, T., & Tennant, A. (2013). Measuring engagement in deliberate self-harm behaviours: Psychometric evaluation of six scales. BMC Psychiatry, 13(1). doi:10.1186/1471-244x-13-4

Müller, A., Claes, L., Smits, D., Brähler, E., & De Zwaan, M. (2016). Prevalence and Correlates of Self-Harm in the German General Population. PLOS ONE, 11(6). doi:10.1371/journal.pone.0157928

Sansone, R. A., McLean, J. S., & Wiederman, M. W. (2008). The relationship between medically self-sabotaging behaviors and borderline personality disorder among psychiatric inpatients. Primary Care Companion to the Journal of Clinical Psychiatry, 10(6), 448–452. https://doi.org/10.4088/pcc.v10n0604

Sansone, R. A., & Sansone, L. A. (2010). Measuring self-harm behavior with the Self-Harm Inventory. Psychiatry, 7(4), 16–19.

Sansone, R. A., & Wiederman, M. W. (1998). The Self-Harm Inventory (SHI): Development of a scale for identifying self-destructive behaviors.and borderline personality disorder. Journal of Clinical Psychology, 54(7), 973–983.

Sansone, R. A., & Wiederman, M. W. (2015). The self-harm inventory: A meta-analysis of its relationship to the personality diagnostic questionnaire-4 as a measure of borderline personality disorder. International Journal of Psychiatry in Clinical Practice, 19(4), 290–293.

Sellbom, M., Sansone, R. A., & Songer, D. A. (2017). Elucidating the association between the self-harm inventory and several borderline personality measures in an inpatient psychiatric sample. International Journal of Psychiatry in Clinical Practice, 21(3), 231-235. doi:10.1080/13651501.2017.1306628

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