Positive and Negative Affect Schedule (PANAS)

Dr David Hegarty

The Positive and Negative Affect Schedule (PANAS; Watson et al., 1988) is a 20-item self- report measure to assess positive affect (PA) and negative affect (NA). PA is associated with pleasurable engagement with the environment, whereas NA reflects a dimension of general distress summarising a variety of negative states such as anger, guilt, or anxiety. The PANAS is a useful tool for therapists who are interested in tracking changes in positive and negative emotions for clients from week to week as they engage in day-to-day life. The PANAS is sensitive to momentary changes in affect and can be used to chart the immediate effects of therapy sessions as well as outcomes associated with positive psychological interventions, exercises, or activities.

Psychometric Properties

The PANAS has been reported to have very good internal consistency reliability, with alphas ranging from 0.85 to 0.90 for Positive Affect and from 0.84 to 0.87 for Negative Affect (Crawford & Henry, 2004; Heubeck & Wilkinson, 2019). Test–retest reliability is good over an 8-week time period, with correlations of 0.54 for momentary Positive Affect, 0.45 for momentary Negative Affect.

Since the introduction of the PANAS, many studies examined its factorial validity using exploratory (EFA) or confirmatory factor analysis (CFA) and have come to different conclusions about which measurement model fits best (Wedderhoff et al., 2021). A meta- analysis from 47 independent studies using over 54,000 participants (Wedderhoff et al., 2021) found a correlated two-factor model including error correlations within content categories provided the best fit for all samples.

Based upon a large sample of non-clinical Australian adult (18 to 50 years old) respondents on both the state (n = 1059) version of the PANAS (Heubeck & Wilkinson, 2019), means and standard deviations were determined:

  • Positive Affect: 26.48 (8.1)
  • Negative Affect: 14.80 (5.49)

Scoring and Interpretation 

The PANAS score is separated into the Positive Affect (PA) and Negative Affect (NA) scores, with a higher score indicating more positive or negative affect respectively. Note, that although a very high score on the PA scale is worthy of attention (i.e. manic patients will typically score very highly on PA), the principal clinical concern will be with patients who show very low levels of positive affect (i.e. are anhedonic) and thus obtain low percentile ranks. In contrast, a high score on the NA (and a high percentile) is an indicator of psychological distress.

Normative data was collected from over 1,000 Australian adults and is used to calculate percentiles. A percentile rank of 50 indicates an average level of positive or negative affectivity in comparison to the normative group.

There are two subscales of the PANAS:

  1. Positive Affect (items 1, 3, 5, 9, 10, 12, 14, 16, 17, and 19). Higher scores represent higher levels of PA and are associated with pleasurable engagement with the environment.
  2. Negative Affect Sore (items 2, 4, 6, 7, 8, 11, 13, 15, 18, and 20). Higher scores represent higher levels of NA and reflect a dimension of general distress summarising a variety of negative states such as anger, guilt, or anxiety.

Developer

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063

References

Crawford, J. R., & Henry, J. D. (2004). The positive and negative affect schedule (PANAS): construct validity, measurement properties and normative data in a large non-clinical sample. The British Journal of Clinical Psychology / the British Psychological Society, 43(Pt 3), 245–265. https://doi.org/10.1348/0144665031752934

Heubeck, B. G., & Wilkinson, R. (2019). Is all fit that glitters gold? Comparisons of two, three and bi-factor models for Watson, Clark & Tellegen’s 20-item state and trait PANAS. Personality and Individual Differences, 144, 132–140. https://doi.org/10.1016/j.paid.2019.03.002

Tinnitus Handicap Inventory (THI)

Dr David Hegarty

The Tinnitus Handicap Inventory (THI; Newman et al., 1996) is a 25-item self-report measure to determine perceived tinnitus handicap severity. The THI is a useful measure for determining the efficacy of psychological treatment for tinnitus (Zeman et al., 2011).

The THI comprises 25 items grouped into three subscales:

  1. Functional: this deals with limitations caused by tinnitus in the areas of mental, social, and physical functioning.
  2. Emotional: concerns affective responses to tinnitus, e.g. anger, frustration, depression, anxiety.
  3. Catastrophic: probes the most severe reactions to tinnitus, such as loss of control, inability to escape from tinnitus, and fear of having a terrible disease.    

Psychometric Properties

Studies concerning psychometric properties of THI report Cronbach’s alpha for the total score as very high, mostly above 0.90 (Gos et al., 2020). Alpha for the Functional and Emotional subscales ranged from 0.8 to 0.9, while for the Catastrophic subscale it was lower, about 0.6–0.7 (Gos et al., 2020). Although all three subscale scores are frequently used and reported, emphasis should be placed upon the total score (Gos et al., 2020).

In a validation study by Got et al. (2020), 1115 adult patients presenting at a tinnitus clinic (49.8% females, age range = 19 – 84; period of suffering tinnitus = 1 month – 50 years) were assessed using the THI and means (and standard deviations) were obtained:

  1. Functional: Mean = 20.53 (11.71)
  2. Emotional: Mean = 16.84 (10.30)
  3. Catastrophic: Mean = 10.81 (5.17)
  4. Total Score: Mean = 48.18 (25.27)

These means and standard deviations are used to calculate percentiles for the THI total score and subscale scores.   

Scoring and Interpretation 

The THI total score ranges from 0 to 100 where a higher score indicates more tinnitus handicap severity. In addition, a percentile is presented that shows the respondents scores in comparison to tinnitus patients. A percentile rank of 50 indicates that the individual has an average severity of tinnitus compared to other people suffering tinnitus.

Three three subscales are calculated:

  1. Functional (items 1, 2, 4, 7, 9, 12, 13, 15, 18, 20, 24) – role limitations in the areas of mental, social/occupational, and physical functioning
  2. Emotional (items 3, 6, 10, 14, 16, 17, 21, 22, 25) – affective reactions to tinnitus
  3. Catastrophic (items 5, 8, 11, 19, 23) – catastrophic thinking about the symptoms of tinnitus, including a sense of lack of control

A grading system, as determined by the British Association of Otolaryngologists, Head and Neck Surgeons, is also used for the THI total score (McCombe et al., 2001):

  • Very mild (score 0–16). Tinnitus is perceived only in silence and is easily masked. It does not interfere with sleep or with daily activities.
  • Mild (score 18–36). Tinnitus is easily masked by environmental sounds and forgotten during daily activities. It can occasionally interfere with sleep but not with daily activities.
  • Moderate (score 38–56). Tinnitus is perceived even in the presence of environmental sound; however, daily activities are not impaired. It is perceived less under concentration. Interference with sleep and relaxing activities is not infrequent.
  • Severe (score 58–76). Tinnitus is continuously perceived and hardly masked by external noise. It alters the sleep cycle and can interfere with the subject’s daily activities. Relaxing activities are compromised. Subjects with this level of tinnitus often require medical consultations.
  • Catastrophic (78–90). All side effects caused by tinnitus are present at a very severe level. The subject requires medical assistance very frequently, including neuropsychiatric help.

A change score of at least seven points has been considered to denote reliable clinically significant improvement on the THI (Zeman et al., 2011).  

Developer

Newman, C. W., Jacobson, G. P., & Spitzer, J. B. (1996). Development of the Tinnitus Handicap Inventory. Archives of Otolaryngology–Head & Neck Surgery, 122(2), 143–148. https://doi.org/10.1001/archotol.1996.01890140029007

References

McCombe, A., Baguley, D., Coles, R., McKenna, L., McKinney, C., Windle-Taylor, P., & British Association of Otolaryngologists, Head and Neck Surgeons. (2001). Guidelines for the grading of tinnitus severity: the results of a working group commissioned by the British Association of Otolaryngologists, Head and Neck Surgeons, 1999. Clinical Otolaryngology and Allied Sciences, 26(5), 388–393. https://doi.org/10.1046/j.1365-2273.2001.00490.x

Gos, E., Sagan, A., Skarzynski, P. H., & Skarzynski, H. (2020). Improved measurement of tinnitus severity: Study of the dimensionality and reliability of the Tinnitus Handicap Inventory. PloS One, 15(8), e0237778. https://doi.org/10.1371/journal.pone.0237778

Zeman, F., Koller, M., Figueiredo, R., Aazevedo, A., Rates, M., Coelho, C., Kleinjung, T., de Ridder, D., Langguth, B., & Landgrebe, M. (2011). Tinnitus handicap inventory for evaluating treatment effects: which changes are clinically relevant? Otolaryngology–Head and Neck Surgery, 145(2), 282–287. https://doi.org/10.1177/0194599811403882

Multidimensional Assessment of Interoceptive Awareness – Youth Version (MAIA-Y)

Dr David Hegarty

The Multidimensional Assessment of Interoceptive Awareness – Youth Version (MAIA-Y) is an 8-scale state-trait questionnaire with 32 items to measure multiple dimensions of interoception (body awareness). The MAIA-Y is suitable for use with youths between 7 – 17 years of age. There is a parallel adult version (MAIA-2) for use with individuals 18+ years of age.

Interoception refers to the sensation, interpretation, and integration of internal somatic signals (Eggart et al., 2021). There is compelling evidence demonstrating links between poor interoceptive awareness and difficulties with emotion regulation (Price & Hooven, 2018). Therefore, it can be beneficial to measure interoception in a therapeutic setting because effective emotion regulation involves the ability to accurately detect and evaluate cues related to physiological reactions to stressful events. The therapist and client can then work together on appropriate regulation strategies that temper and influence the emotional response.

The MAIA consists of 8 scales (addressing 5 dimensions of body awareness):

  1. Noticing (Awareness of Body Sensations)
  2. Not-Distracting (Emotional Reaction and Attentional Response to Sensations)
  3. Not-Worrying (Emotional Reaction and Attentional Response to Sensations)
  4. Attention Regulation (Capacity to Regulate Attention)
  5. Emotional Awareness (Awareness of Mind-Body Integration)
  6. Self-Regulation (Awareness of Mind-Body Integration)
  7. Body Listening (Awareness of Mind-Body Integration)
  8. Trust (Trusting Body Sensations)     

Psychometric Properties

The MAIA-Y (Jones et al., 2020) is based on the original MAIA (Mehling et al., 2012), with modifications made to simplify the language of each statement. Cronbach’s alpha ranged from 0.36 – 0.78, with the Not-Distracting (0.36), Noticing (0.43), Not-Worrying (0.47), and Body Listening (0.69) scales being below 0.70 (Jones et al., 2020).

A validation study by Jones et al. (2020), based upon a convenience sample of children aged 7–10 years (n= 212) and adolescents aged 11–17 years (n= 217), provided means and standard deviations for all 8 scales for each age (7 – 15+). Age is an important component in the MAIA-Y as results from Jones et al. (2020) found a negative linear relationship between the trusting scale and age, suggesting that youths may lose trust in their body as they age.   

Scoring and Interpretation 

The results from the MAIA-Y focuses upon the individual scale scores (between 0 and 5), where higher score equates to more awareness of bodily sensation. A percentile is also calculated, indicating how the responded scored in comparison to an age related normative sample. Interpretation using percentiles helps contextualise scores. For example, percentile below 50 indicate that the individual scored below what is typical. Extreme percentile scores (below 10 or above 90) are of particular clinical significance.

The MAIA consists of eight scales:

  1. Noticing (Items 1-4): Awareness of uncomfortable, comfortable, and neutral body sensations
  2. Not-Distracting (Items 5-7): Higher scores suggest a more tuned in relationship to unpleasant sensations, and is typically considered to be adaptive. Lower scores indicate the tendency to ignore or distract oneself from sensations of pain or discomfort
  3. Not-Worrying (Items 8-10): Higher scores indicate less rumination about discomfort. Low scores indicate emotional distress or worry with sensations of pain or discomfort
  4. Attention Regulation (Items 11-17): Ability to sustain and control attention to body sensation
  5. Emotional Awareness (Items 18-22): Awareness of the connection between body sensations and emotional states
  6. Self-Regulation (Items 23-26): Ability to regulate psychological distress by attention to body sensations
  7. Body Listening (Items 27-29): Actively listens to the body for insight
  8. Trust (Items 30-32): Experiences one’s body as safe and trustworthy  

Developer

Jones, A., Silas, J., Todd, J., Stewart, A., Acree, M., Coulson, M., & Mehling, W. E. (2021). Exploring the Multidimensional Assessment of Interoceptive Awareness in youth aged 7-17 years. Journal of Clinical Psychology, 77(3), 661–682. https://doi.org/10.1002/jclp.23067

References

Eggart, M., Todd, J., & Valdés-Stauber, J. (2021). Validation of the Multidimensional Assessment of Interoceptive Awareness (MAIA-2) questionnaire in hospitalized patients with major depressive disorder. PloS One, 16(6), e0253913. https://doi.org/10.1371/journal.pone.0253913

Mehling, W. E., Price, C., Daubenmier, J. J., Acree, M., Bartmess, E., & Stewart, A. (2012). The Multidimensional Assessment of Interoceptive Awareness (MAIA). PloS One, 7(11), e48230. https://doi.org/10.1371/journal.pone.0048230

Price, C. J., & Hooven, C. (2018). Interoceptive Awareness Skills for Emotion Regulation: Theory and Approach of Mindful Awareness in Body-Oriented Therapy (MABT). Frontiers in psychology, 9, 798. https://doi.org/10.3389/fpsyg.2018.00798

Multidimensional Assessment of Interoceptive Awareness – Version 2 (MAIA-2)

Dr David Hegarty

The Multidimensional Assessment of Interoceptive Awareness – Version 2 (MAIA-2) is an 8-subscale state-trait self-report questionnaire to measure multiple dimensions of interoception (awareness of bodily sensations). The MAIA-2 is suitable for adults (18+) and has 37 items. There is a parallel youth version (MAIA-Y) for use with individuals 7 – 17 years of age.

Interoception refers to the sensation, interpretation, and integration of internal somatic signals (Eggart et al., 2021). There is compelling evidence demonstrating links between poor interoceptive awareness and difficulties with emotion awareness and emotion regulation (Price & Hooven, 2018). Interoception may be of clinical importance for individuals presenting with autism, eating disorders, alexithymia or chronic pain.

It can be beneficial to measure interoception in a therapeutic setting because effective emotion regulation involves the ability to accurately detect and evaluate cues related to physiological reactions to stressful events. The therapist and client can then work together on appropriate regulation strategies that temper and influence the emotional response.

The MAIA consists of 8 scales (addressing 5 dimensions of body awareness):

  1. Noticing (Awareness of Body Sensations)
  2. Not-Distracting (Emotional Reaction and Attentional Response to Sensations)
  3. Not-Worrying (Emotional Reaction and Attentional Response to Sensations)
  4. Attention Regulation (Capacity to Regulate Attention)
  5. Emotional Awareness (Awareness of Mind-Body Integration)
  6. Self-Regulation (Awareness of Mind-Body Integration)
  7. Body Listening (Awareness of Mind-Body Integration)
  8. Trust (Trusting Body Sensations)    

Psychometric Properties

The original MAIA (Mehling et al., 2012) was 32 questions and had some internal consistency weaknesses (Mehling et al., 2018). To improve upon the original the MAIA-2 added additional items (Mehling et al., 2018), yielding higher Cronbach alphas and improved psychometrics. Two subscales were below the standard Cronbach alpha criterion of 0.70 – Noticing (.64) and Not Worrying (.67). The eight MAIA-2 scales are sensitive to change and so can detect the effects of interventions aimed at improving interoception (Eggart et al., 2021).

A validation study by Mehling et al. (2018), based upon a convenience sample of 1,090 individuals between 18 and 69 years old, provided means and standard deviations for all 8 scales. The mean score (between 0 – 5) for each scale was: 1. Noticing (M = 3.34, SD = 0.90) 2. Not-Distracting (M = 2.06, SD = 0.80) 3. Not-Worrying (M = 2.52, SD = 0.85) 4. Attention Regulation (M = 2.84, SD = 0.86) 5. Emotional Awareness (M = 3.44, SD = 0.96) 6. Self-Regulation (M = 2.78, SD = 1.01) 7. Body Listening (M = 2.20, SD = 1.17) 8. Trust (M = 3.37, SD = 1.11)    

Scoring and Interpretation 

Scores are between 0 and 5, where higher score equates to more awareness of bodily sensation. A percentile is also calculated, indicating how the responded scored in comparison to a normative sample. Interpretation using percentiles helps contextualise scores. For example, percentile below 50 indicate that the individual scored below what is typical. Extreme percentile scores (below 10 or above 90) are of particular clinical significance.

The MAIA-2 consists of eight scales:

  1. Noticing (Items 1-4): Awareness of uncomfortable, comfortable, and neutral body sensations
  2. Not-Distracting (Items 5-10): Higher scores suggest a more tuned in relationship to unpleasant sensations, and is typically considered to be adaptive. Lower scores indicate the tendency to ignore or distract oneself from sensations of pain or discomfort.
  3. Not-Worrying (Items 11-15): Higher scores indicate less rumination about discomfort. Low scores indicate emotional distress or worry with sensations of pain or discomfort
  4. Attention Regulation (Items 16-22): Ability to sustain and control attention to body sensation
  5. Emotional Awareness (Items 23-27): Awareness of the connection between body sensations and emotional states
  6. Self-Regulation (Items 28-31): Ability to regulate psychological distress by attention to body sensations
  7. Body Listening (Items 32-34): Actively listens to the body for insight
  8. Trust (Items 35-37): Experiences one’s body as safe and trustworthy

The results from the MAIA-2 focus upon the individual scale scores as a total score is not meaningful (Mehling et al., 2012).   

Developer

Mehling WE, Acree M, Stewart A, Silas J, Jones A (2018) The Multidimensional Assessment of Interoceptive Awareness, Version 2 (MAIA-2). PLoS ONE 13(12): e0208034. https://doi.org/10.1371/journal.pone.0208034

References

Eggart, M., Todd, J., & Valdés-Stauber, J. (2021). Validation of the Multidimensional Assessment of Interoceptive Awareness (MAIA-2) questionnaire in hospitalized patients with major depressive disorder. PloS One, 16(6), e0253913. https://doi.org/10.1371/journal.pone.0253913

Mehling, W. E., Price, C., Daubenmier, J. J., Acree, M., Bartmess, E., & Stewart, A. (2012). The Multidimensional Assessment of Interoceptive Awareness (MAIA). PloS One, 7(11), e48230. https://doi.org/10.1371/journal.pone.0048230

Price, C. J., & Hooven, C. (2018). Interoceptive Awareness Skills for Emotion Regulation: Theory and Approach of Mindful Awareness in Body-Oriented Therapy (MABT). Frontiers in psychology, 9, 798. https://doi.org/10.3389/fpsyg.2018.00798

Ritvo Autism Asperger Diagnostic Scale – Revised (RAADS-R)

Dr David Hegarty

The Ritvo Autism Asperger Diagnostic Scale – Revised (RAADS–R) is an 80-item clinician-administered questionnaire designed to identify adults with Autism. The assessment is suitable for adult (age 18+) males and females with average or above-average intelligence (i.e. IQ above 80).

There are four symptom-areas assessed by the RAADS-R:

  1. Social Relatedness Problems
  2. Circumscribed Interests
  3. Language
  4. Sensory Motor

With high prevalence of Autism in mental health settings and the fact that adults are being referred for diagnosis with increasing frequency, this instrument is a useful clinical tool to assist clinicians with diagnosis (Ritvo et al., 2011).

The RAADS-R is best used in conjunction with clinical expertise and/or other assessment procedures to establish a diagnosis. The self-report nature (with clinician supervision/administration) of this assessment may mean that individuals with low reflective capacity score low on the RAADS-R despite having diagnosable Autism.

Psychometric Properties

Questions on the original RAADS (Ritvo et al. 2008) assessed developmental pathology in three symptom areas: language, social relatedness, and sensory-motor. After critical review of the original RAADS and the results of a factor analysis, the revised 80-item RAADS-R was developed with the addition of a fourth symptom area (circumscribed interests), two questions, and several wording clarifications.

The RAADS–R is a valid and reliable instrument to assist the diagnosis of autistic adults. A validation study (Ritvo et al., 2011) with a sample of 201 adults with Autism and 578 neurotypical adults from the USA and Australia (Ritvo et al., 2011) defined the optimum cutoff score of 65. At this level, no one without Autism scored above the threshold (specificity = 100%) and only 3% of the autistic group did not score over the cutoff score (sensitivity = 97%). Test–retest reliability was high (0.987) and it had high concurrent validity (96%) with the SRS-A.

The Autism norms which are used to calculate Autistic percentiles are based on the validation study by Ritvo, et al. (2011). A sample of 201 individuals with a confirmed DSM-IV-TR diagnosis of Autism or Aspergers had a mean RAADS-R score of 133.81 (SD = 37.72). This combined Autism and Aspergers group had an average age of 31, IQ of 119 and were 28% female. The Autism group alone had a mean RAADS-R score of 138.46 (SD = 41.4), however the combined group was used in calculating percentiles given it is most representative of DSM-5-TR diagnostic criteria.

The neurotypical percentile is based on a sample of 578 individuals who did not have a diagnosis of Autism, Aspergers or PDD NOS, however did include people with other high prevalence clinical diagnoses, making it representative of a neurotypical population. The sample had an average age of 42, IQ of 114 and 57% percent were female. The normative sample’s mean RAADS-R score was 25.95 (SD = 16.04) and is used to calculate the normative percentile.

Scoring and Interpretation 

The total score of the RAADS-R ranges from 0 – 240, with a higher score more indicative of behaviours and symptoms consistent with Autism. Scores at or above 65 are consistent with Autism.

There is also a neurotypical and Autism percentile calculated that compares the respondent’s score with a comparison control group of neurotypical adults (Mean = 25.95, SD = 16.04) and adults with an Autism diagnosis (Mean = 133.81, SD = 37.72; Ritvo et al., 2011). The graph shows the respondent’s pattern of responding compared with the neurotypical sample, with the 50th percentile marking the average response for someone without Autism.

These percentiles can be helpful for interpretation as they contextualise scores in comparison to a typical pattern of responding for neurotypical adults and adults with Autism. For example, a normative percentile of 80 indicates the individual scored higher than 80 percent of the neurotypical comparison group. The cutoff raw score of 65 is above the 99th percentile on the neurotypical percentile, whereas this is at about the 3rd percentile for adults with Autism.

There are four subscales:

  1. Social Relatedness Problems: how well the individual relates to others (e.g. sympathy, empathy, politeness, relationship skills).
    Scores above 30 are considered to be of significance.
    39 questions: 1, 3, 5, 6, 8, 11, 12, 14, 17, 18, 20, 21, 22, 23, 25, 26, 28, 31, 37, 38, 39, 43, 44, 45, 47, 48, 53, 54, 55, 60, 61, 64, 68, 69, 72, 76, 77, 79, 80
  2. Circumscribed Interests: how broad-ranging the individual’s interests are and how much they talk about these interests.
    Scores above 14 are considered to be of significance.
    14 questions: 9, 13, 24, 30, 32, 40, 41, 50, 52, 56, 63, 70, 75, 78:
  3. Language: how often the individual uses words and phrases from movies or television in conversations and the ability to understand language nuances (e.g. metaphor).
    Scores above 3 are considered to be of significance.
    7 questions: 2, 7, 15, 27, 35, 58, 66
  4. Sensory Motor: a measure of how much the individual struggles with sensory sensitivities, how often they engage in self-stimulatory behaviours, and the individual’s atypical speech patterns and tone of voice.
    Scores above 15 are considered to be of significance.
    20 questions: 4, 10, 16, 19, 29, 33, 34, 36, 46, 42, 49, 51, 57, 59, 62, 65, 67, 71, 73, 74

The self-report nature of this assessment may mean that individuals with low reflective capacity/insight score low on the RAADS-R despite having diagnosable Autism. It is therefore recommended that clinician’s inspect individual responses to items to judge the veracity of self-reported problems.

Developer

Ritvo, R. A., Ritvo, E. R., Guthrie, D., Ritvo, M. J., Hufnagel, D. H., McMahon, W., Tonge, B., Mataix-Cols, D., Jassi, A., Attwood, T., & Eloff, J. (2011). The Ritvo Autism Asperger Diagnostic Scale-Revised (RAADS-R): a scale to assist the diagnosis of Autism Spectrum Disorder in adults: an international validation study. Journal of Autism and Developmental Disorders, 41(8), 1076–1089. https://doi.org/10.1007/s10803-010-1133-5  

References

Ritvo, R., Ritvo, E., Guthrie, D., Yuwiler, A., Ritvo, M., & Weisbender, L. (2008). A scale to assist the diagnosis of Autism and Asperger’s disorder in Adults (RAADS): A pilot study. Journal of Autism and Developmental Disorders, 38(2), 213–223.

Borderline Symptom List (BSL-23)

Dr David Hegarty

The Borderline Symptom List – Short Version (BSL-23) is a 23-item self-rating instrument for specific assessment of borderline personality disorder (BPD) symptomatology in adults (18+). The scale assesses DSM BPD diagnostic criteria (e.g., affective instability, recurrent suicidal behaviour, gestures, or threats, or self-mutilating behaviour, and transient dissociative symptoms) in addition to items that are based on borderline-typical empirical findings regarding self-criticism, problems with trust, emotional vulnerability, and proneness to shame, self-disgust, loneliness, and helplessness (Kleindienst et al., 2020).

Individuals with high scores on the BSL-23 are more likely to have BPD and associated challenges with managing emotions, self-image, relationship issues, and general functioning in everyday life.

Psychometric Properties

The BSL-23 items are based on criteria of the DSM-5, on the revised version of the Diagnostic Interview for Borderline Personality Disorder, and on the experiences of both clinical experts and input from BPD (Kleindienst et al., 2020). The BSL-23 has a single factor structure and has excellent psychometric properties, with high internal consistency with a Cronbach’s of 0.97 and test-retest reliability of 0.82 within 1 week (Bohus, 2009). These properties have been replicated in several studies that validated the translations of the BSL-23 into 18 foreign languages (Kleindienst et al., 2020). The BSL-23 also has strong convergent validity with correlations between the BSL-23 and depression as measured by the BDI (r = 0.87), as well as general severity of psychopathology as measured by the SCL-90-R GSI (r = 0.89; Bohus, 2009).

Kleindienst et al. (2020) tested the BSL-23 on over 1,000 adults and developed cut-off scores and severity levels (none or low, mild, moderate, high, very high, and extremely high) for clients with BPD. They found that individuals with a severity grade of “none or low” were virtually free from diagnostic BPD-criteria and had a high level of global functioning corresponding to few or no symptoms. Severity grades indicating “high” to “extremely high” levels of BPD symptoms were observed at a much higher rate in treatment-seeking patients (70.0%) than in a healthy control group with no prior psychopathology history (0.0%)

Scoring and Interpretation 

The average score of items (range 0 to 4, sum of scores divided by 23) is calculated, with a higher score indicating more impairment. Six grades of symptom severity were defined by Kleindienst et al. (2020) based upon the average score:

  • None/Low: 0 – 0.3
  • Mild: 0.3 – 0.7
  • Moderate: 0.7 – 1.7
  • High: 1.7 – 2.7
  • Very High: 2.7 – 3.5
  • Extremely High: 3.5 – 4

Scores of 1.50 or higher indicates the responses are consistent with BPD, with empirical data showing this cutoff score is able to discriminate between BPD patients and clients with other clinical psychopathology (e.g. anxiety disorders, major depressive disorders, schizophrenia, etc.; Kleindienst et al., 2020).

Percentiles are also presented comparing the respondents scores to a healthy group (n = 356; with no history of psychopathology) and a BPD group (n = 317; met DSM-V diagnostic criteria for BPD; Kleindienst et al. 2020). A percentile of 50 means that the client has scored at the typical level compared with the comparative group. An average score of 1.5 corresponds to a percentile of 17 compared to the BPD group, and a percentile of 99.9 compared to the healthy control group. These metrics indicate that a score of 1.5 is typical for someone with BPD but highly extreme compared to someone without a psychiatric diagnosis.

There is an additional question (24) that provides an indication of the client’s perspective on their overall well-being, but it is not included in the overall score. The rating on this last question (from 0 to 100) is strongly correlated with specific indicators of wellbeing for BPD patients, including self-perception, affect regulation, self-destruction, dysphoria, loneliness, intrusions, and hostility (Bohus, et al., 2007).  

Developer

Bohus, M., Kleindienst, N., Limberger, M. F., Stieglitz, R.-D., Domsalla, M., Chapman, A. L., Steil, R., Philipsen, A., & Wolf, M. (2009). The short version of the Borderline Symptom List (BSL-23): development and initial data on psychometric properties. Psychopathology, 42(1), 32–39. https://doi.org/10.1159/000173701  

References

Bohus, M., Limberger, M. F., Frank, U., Chapman, A. L., Kühler, T., & Stieglitz, R.-D. (2007). Psychometric properties of the Borderline Symptom List (BSL). Psychopathology, 40(2), 126–132. https://doi.org/10.1159/000098493

Kleindienst, N., Jungkunz, M., & Bohus, M. (2020). A proposed severity classification of borderline symptoms using the borderline symptom list (BSL-23). Borderline Personality Disorder and Emotion Dysregulation, 7, 11. https://doi.org/10.1186/s40479-020-00126-6  

Mood Disorder Questionnaire (MDQ)

Dr David Hegarty

The Mood Disorder Questionnaire (MDQ) is a 15-item self-report screening instrument that can be used to identify clients most likely to have bipolar disorder. The MDQ assists in identifying bipolar disorder and distinguishing it from other mood disturbances in clinical populations.

Past research has found that MDQ total scores are associated with anxiety, trauma-related, substance use, eating, and impulse control disorders, in addition to BD (Paterniti & Bisserbe, 2018; Zimmerman et al., 2011). As a result, there have been two subscales identified (Carpenter et al., 2020):

  • Positive Activation: increased energy/activity, grandiosity, and decreased need for sleep. This subscale is specific to BD.
  • Negative Activation: irritability, racing thoughts, levels of negative affectivity, and distractibility. This subscale is more broadly related to emotion dysregulation and transdiagnostic personality traits.

Research indicates that effective treatment of bipolar disorder (BD) differs significantly from that of other related disorders, such as unipolar depression (Carpenter et al., 2020). This underscores the importance of screening for bipolar disorder (BD) in patients who present to mental health services so that they can receive an effective intervention. For example, the use of antidepressants in BD treatment is controversial (Sidor & MacQueen, 2011) and psychotherapy treatment more often involves addressing issues such as unrealistic goal-setting and impulsivity in patients with BD than in others (Geddes & Miklowitz, 2013; Miklowitz & Johnson, 2006). As BD is associated robustly with significant psychosocial impairment (e.g., poor work and relationship functioning), failing to detect cases of BD can lead to suboptimal treatment approaches and, thereby, exacerbate personal and societal costs associated with BD (Conus, Macneil, & McGorry, 2014).  

Psychometric Properties

The internal reliability for the MDQ is strong (Cronbach’s alpha = 0.88; Stanton & Watson, 2017).

Traditionally, a positive screen on the MDQ requires endorsement of (a) 7 or more of 13 symptom items, (b) multiple symptoms occurring at the same time, and (c) symptoms causing notable psychosocial impairment (Hirschfeld et al., 2000). The first thirteen questions on the MDQ are based upon bipolar symptoms and a score of 7 or more is the optimal cutoff, as it provides good sensitivity (73%) and very good specificity for a diagnosis of BD (90%; Hirschfeld et al., 2000). However, results from a number of studies suggest that the MDQ is not unidimensional (Ruggero et al., 2014; Stanton & Watson, 2017).

Carpenter et al. (2020) and Stanton and Watson (2017) investigated the structure of the MDQ’s 13 symptom items and found that the MDQ was best represented by two factors, which they termed Positive Activation (e.g., “had much more energy”; “was much more confident”) and Negative Activation (e.g., “thoughts raced”; “felt very irritable”) symptom dimensions. Three of the MDQ symptoms (items 5, 10, and 11) loaded highly onto both Positive and Negative Activation factors and were removed from the final model. Carpenter et al. (2020) found that Positive Activation was uniquely associated with BD diagnosis, whereas Negative Activation was associated with a range of diagnoses. Thus, a 4-item Positive Activation subscale (α = .82) and a 6-item Negative Activation subscale (α = .73) was created.  

Scoring and Interpretation 

A total score is calculated for questions 1-13 where a “Yes” provides a score of 1 and “No” is 0. The percentage of items endorsed (raw score / number of items multiplied by 100) is included to provide an indication of the proportion of symptoms identified with by the respondent.

In order to meet the threshold for bipolar disorder the traditional scoring method is as follows:

  • A score of 7 or more for questions 1-13 (53% of items endorsed) AND
  • Check “yes” for the item asking if the symptoms clustered in the same time period (question 14) AND
  • Symptoms caused either “moderate” or “serious” problems (question 15).

Subscale scores were also developed (Carpenter et al., 2020, Stanton & Watson, 2017) using 10 of the 13 items in the symptom questions:

  • Positive Activation (items 3, 4, 8, 9): assesses increased energy/activity, grandiosity, and decreased need for sleep. Individuals endorsing symptoms defining Positive Activation are not likely to report significant levels of negative affect and are likely to be energetic and extraverted. Individuals scoring high on Positive Activation may be less likely to rate their symptoms as impairing given that increased levels of energy and activity may be experienced as advantageous to some degree, especially if they are mild in nature. This factor is strongly associated with a BD diagnosis.
  • Negative Activation (items 1, 2, 6, 7, 12, 13): assesses irritability, racing thoughts, levels of negative affectivity, and distractibility. This factor is strongly associated with BD as well as a a range of other disorders, many of them (e.g. depressive disorders, PDs, PTSD, GAD, substance use disorders) characterised by emotion dysregulation and/or transdiagnostic personality traits such as neuroticism and disinhibition. Clients high in Negative Activation may be at risk for engaging in impulsive behavior in emotional situations.

Clinical percentiles are also presented for the two subscales as developed by Carpenter et al. (2020) on over 1,700 outpatients (for a variety of diagnoses). A percentile of 50 means that the client has scored at the average level compared with the clinical group for that subscale.  

Developer

Hirschfeld, R. M., Williams, J. B., Spitzer, R. L., Calabrese, J. R., Flynn, L., Keck, P. E., Jr, Lewis, L., McElroy, S. L., Post, R. M., Rapport, D. J., Russell, J. M., Sachs, G. S., & Zajecka, J. (2000). Development and validation of a screening instrument for bipolar spectrum disorder: the Mood Disorder Questionnaire. The American Journal of Psychiatry, 157(11), 1873–1875. https://doi.org/10.1176/appi.ajp.157.11.1873  

References

Carpenter, R. W., Stanton, K., Emery, N. N., & Zimmerman, M. (2020). Positive and Negative Activation in the Mood Disorder Questionnaire: Associations With Psychopathology and Emotion Dysregulation in a Clinical Sample. Assessment, 27(2), 219–231. https://doi.org/10.1177/1073191119851574

Hirschfeld, R. M., Williams, J. B., Spitzer, R. L., Calabrese, J. R., Flynn, L., Keck, P. E., Jr, Lewis, L., McElroy, S. L., Post, R. M., Rapport, D. J., Russell, J. M., Sachs, G. S., & Zajecka, J. (2000). Development and validation of a screening instrument for bipolar spectrum disorder: the Mood Disorder Questionnaire. The American Journal of Psychiatry, 157(11), 1873–1875. https://doi.org/10.1176/appi.ajp.157.11.1873 

Stanton, K., & Watson, D. (2017). Explicating the structure and relations of the Mood Disorder Questionnaire: Implications for screening for bipolar and related disorders. Journal of Affective Disorders, 220, 72–78. https://doi.org/10.1016/j.jad.2017.05.046  

Vanderbilt ADHD Diagnostic Parent Rating Scale (VADPRS)

Dr David Hegarty

The Vanderbilt ADHD Diagnostic Parent Rating Scale is used to help in the diagnostic process of Attention Deficit/Hyperactivity Disorder (ADHD) in children between the ages of 6 and 12. It has a total of 55 questions, includes all 18 of the DSM-IV criteria for ADHD and should be completed by a parent of the child. As well as identifying inattentive, hyperactive/impulsive, or combined subtypes of ADHD, it can also be used to identify symptoms of frequent comorbidities, including oppositional defiance, conduct disorder, anxiety and depression.  

Psychometric Properties

Concurrent validity has been established through comparing parent rating with teacher ratings and those independently diagnosed with ADHD (Mark et al., 2003). Confirmatory factor analysis confirmed four factors that fitted with the theoretical formulation of inattention, hyperactivity/impulsivity, ODD-CD, and anxiety-depression subscales.

Becker et al. (2011) validated the subscales but reformulated the scoring method for the comorbid sub-scales by using the total sum of scores. In this scoring system the total sum of the subscales (rather than when a parents rates either 2 or 3 on the Likert scale), ODD is ruled out at <10, CD at <4, Anxiety at <5 and Depression at <5. Nevertheless, the overall scale was validated and found to have high reliability and clinical utility.  

Scoring and Interpretation 

Scores are presented for the three subtypes of ADHD:

  • Predominately Inattentive Subtype. A child meets the diagnostic criteria if they have six or more “Often” or “Very Often” on items 1 to 9, plus a performance problem (scores of 1 or 2) on questions 48 to 55.
  • Predominately Hyperactive/Impulsive Subtype. A child meets diagnostic criteria if they have six or more “Often” or “Very Often” on items 10 through 18, plus a performance problem (scores of 1 or 2) on questions 48 to 55.
  • Combined Subtype. A child meets the diagnostic criteria if they meet the above criteria for both Inattentive and Hyperactive/Impulsive subtypes.

In addition to the ADHD scales, scores are presented for frequently comorbid difficulties. Children with scores below the clinical cutoff are highly unlikely to meet the diagnostic criteria for that disorder. Children above the cutoff on the ODD, CD, Anxiety/Depression sub-scales should be further evaluated, as these sub-scales are only designed as a cursory screening measure for such problems.

  • Oppositional Defiant Disorder = items 19 to 26. To be above the clinical cutoff score of 2 or 3 on 4(or more) out of 8 behaviors on questions 19–26 AND score a 1 or 2 on any of the performance questions 48–55.
  • Conduct Disorder = items 27 to 40. To be above the clinical cutoff scores a 2 or 3 on 3(or more) out of 14 behaviors on questions 27–40 AND score a 1 or 2 on any of the performance questions 48–55
  • Anxiety/ Depression = items 41 to 47. To be above the clinical cutoff scores a 2 or 3 on 3(or more) out of 7 behaviors on questions 41–47 AND score a 1 or 2 on any of the performance questions 48–55.  

Developer

Wolraich, M. L., Hannah, J. N., Baumgaertel, A., & Feurer, I. D. (1998). Examination of DSM-IV critieria for attention deficit/hyperactivity disorder in a county-wide sample. Journal of Developmental and Behavioral Pediatrics, 19, 162– 168. https://doi.org/10.1097/00004703-199806000-00003 

References

Wolraich, M, Lambert, W., Doffing, M., Bickman, L., Simmons, T., Worley, K., (2003). Psychometric Properties of the Vanderbilt ADHD Diagnostic Parent Rating Scale in a Referred Population, Journal of Pediatric Psychology, Volume 28, Issue 8, 1, Pages 559–568. https://doi.org/10.1093/jpepsy/jsg046

Becker, S. P., Langberg, J. M., Vaughn, A. J., & Epstein, J. N. (2012). Clinical utility of the Vanderbilt ADHD diagnostic parent rating scale comorbidity screening scales. Journal of Developmental and Behavioral Pediatrics, 33(3), 221. https://doi.org/10.1097/dbp.0b013e318245615b

Compassion Motivation and Action Scales – Self-Compassion (CMAS-self)

Dr David Hegarty

The Compassion Motivation and Action Scales (CMAS) encompass two dimensions assessing self-compassion (CMAS-self) and compassion to others (CMAS-other). This is the CMAS-self, which is an 18-item self-report measure designed to assess compassion for oneself (Steindl et al., 2021).

The CMAS-self has three subscales:

  1. self-compassion intention – measuring the intent to be compassionate towards oneself
  2. self-compassion distress tolerance – measuring the ability to tolerate distress by oneself when experiencing suffering
  3. self-compassionate action – measuring self-compassionate actions and behaviours

It can be important to measure self-compassion given that the development of compassionate motivation has been found to be associated with benefits physiologically (Kim et al., 2020; Klimecki et al., 2014; Matos et al., 2017), psychologically (Kirby, 2016; MacBeth & Gumley, 2012), and relationally (Crocker & Canevello, 2012; Kirby & Laczko, 2017; Seppala et al., 2012). It has been found that compassion-based interventions are effective at increasing self-reported compassion, self-compassion and mindfulness, reducing depression, anxiety and psychological distress symptoms, and improving well-being (Kirby et al., 2017). The CMAS-self was designed to be specifically used as a measure of the change in compassionate motivation and action over time in clinical practice and intervention research.

Psychometric Properties

The CMAS-self was developed using an initial item pool that was generated on the basis of a review of existing measures in combination with the dimensions of motivational language in motivational interviewing. The initial item pool was disseminated to six international experts who were researchers and clinicians each with over 20 years experience in the compassion and/or motivational interviewing literature for feedback and to ensure that wording and content were culturally relevant. Following the development and consultation process, the initial pool of items was evaluated via exploratory and confirmatory factor analysis to reduce the items further.

There was very good internal consistency present for the CMAS-self with an overall Chronbach’s alpha of 0.94 and subscale consistencies of 0.92 (Intention), 0.95 (Distress tolerance), and 0.94 (Action).

For 621 adults from Australia, USA, UK, and New Zealand, the mean score was 90.79 (SD = 17.52) for the CMAS-self, 30.95 (SD = 4.72) for the Intention subscale, 34.13 (SD = 9.14) for the Distress Tolerance subscale, and 25.70 (SD = 8.38) for the Action subscale (Steindl et al., 2021).

Scoring and Interpretation 

All items are summed to provide an overall score, with higher scores indicative of more self-compassion. Subscale scores are also provided to enable a comparison between subscales:

  1. self-compassion intention (items 1, 2, 3, 4, 5) – measuring the intent to be compassionate towards oneself
  2. self-compassion distress tolerance (items 6, 7, 8, 9, 10, 11, 12) – measuring the ability to tolerate distress by oneself when experiencing suffering
  3. self-compassionate action (items 13, 14, 15, 16, 17, 18) – measuring self-compassionate actions and behaviours

A normative percentile for the total score and subscales are calculated based on a sample from Australia, USA, UK, and New Zealand (Steindl et al., 2021), indicating how the respondent scored in relation to a typical pattern of responding for adults. For example, a percentile of 83 or less indicates the individual has more self-compassion than 83 percent of the normal population.

Results are presented in a graph, which indicates the percentile for total self-compassion and sub-scales compared to a normative sample, with a dotted line at 50 indicating average self-compassion..

Developer

Steindl, S. R., Tellegen, C. L., Filus, A., Seppälä, E., Doty, J. R., & Kirby, J. N. (2021). The Compassion Motivation and Action Scales: a self-report measure of compassionate and self-compassionate behaviours. Australian Psychologist, 56(2), 93–110. https://doi.org/10.1080/00050067.2021.1893110  

Camouflaging Autistic Traits Questionnaire (CAT-Q)

Dr David Hegarty

The Camouflaging Autistic Traits Questionnaire (CAT-Q) is a 25-item self-report measure of social camouflaging behaviours for individuals of age 16 and above. It is used to identify individuals who compensate for or mask autistic characteristics during social interactions and who might not immediately present with autistic traits due to their ability to mask. This can be especially relevant for women with Autism.

The CAT-Q measures the degree of use of camouflaging strategies among people with Autism. The more an individual can camouflage, the more of their autistic inclinations they are likely able to suppress. As such, a high camouflaging score can also account for lower scores on standard Autism psychometric scales.

Importantly, there are significant differences between males and females, so interpretation of scores should be considered in light of gender factors.

The CAT-Q measures camouflaging in general, as well as three subscales:

  1. Compensation
  2. Masking
  3. Assimilation

Psychometric Properties

Research shows robust psychometric support for the CAT-Q. High internal consistency was found for the total scale (Cronbach’s alpha = 0.94), and the Compensation (0.91), Masking (0.85), and Assimilation (0.92) factors (Hull et al., 2019).

Test–retest reliability was good for the total scale (0.77) and no significant differences were found between scores at both times (3 months apart; Hull et al., 2019). The stability was good for the Compensation factor (0.78), while moderate stability was found for the Masking (0.70) and Assimilation factors (0.73; Hull et al., 2019).

The CAT-Q was validated on 306 autistic and 472 non-autistic individuals between the ages of 16 and 82 years of age (Hull et al., 2020). The means and standard deviations are as follows and are used to calculate percentiles:

  • Autistic Individuals (Mean (SD)):
    • Total Score (Female 124.35 (23.27); Male 109.64 (26.50))
    • Compensation (Female 41.85 (11.11); Male 36.81 (12.14))
    • Masking (Female 37.87 (10.54); Male 32.90 (10.57)
    • Assimilation (Female 44.63 (7.82); Male 39.93 (11.26))
  • Neurotypical Individuals (Mean (SD)):
    • Total Score (Female 90.87 (27.67); Male 96.89 (24.22))
    • Compensation (Female 27.18 (11.5); Male 30.06 (10.92))
    • Masking (Female 34.69 (9.05); Male 36.34 (8.13))
    • Assimilation (Female 29.00 (11.73); Male 30.48 (10.33))

Scoring and Interpretation 

The total score ranges from 25–175 with higher scores reflecting greater camouflaging.

There are three subscales:

  1. Compensation — (items 1, 4, 5, 8, 11, 14, 17, 20, and 23)
    Strategies used to actively compensate for difficulties in social situations. Examples: copying body language and facial expressions, learning social cues from movies and books.
  2. Masking — (items 2, 6, 9, 12, 15, 18, 21, and 24)
    Strategies used to hide autistic characteristics or portray a non-autistic persona. Examples: adjusting face and body to appear confident and/or relaxed, forcing eye contact.
  3. Assimilation — (items 3, 7, 10, 13, 16, 19, 22, and 25)
    Strategies used to try to fit in with others in social situations. Examples: Putting on an act, avoiding or forcing interactions with others.

Percentiles are calculated, comparing scores against neurotypical and Autistic males, females, or combined males/females (if your client’s gender is not specified; Hull et al., 2020), indicating how the respondent scored in relation to a typical pattern of responding for neurotypical and autistic adults.

For example, an Autism percentile of 50 for females indicates the individual has typical Camouflaging compared to the Autistic population, which corresponds to an approximate 89th percentile compared with a neurotypical population i.e., what is “normal” for someone with Autism is unusual compared to people without Autism.

Below are some considerations relevant for interpreting scores:

  • High total scores correlate with social anxiety in both individuals with Autism and neurotypicals. Therefore, high percentile scores relative to the normative sample (i.e. above 84) indicates either neurotypical social anxiety or camouflaging of autistic traits.
  • Autistic females demonstrate higher total camouflaging scores than autistic males, but there is no camouflaging gender difference for non-autistic people.
  • Autistic males score lower on Masking than their neurotypical counterparts, but do score higher in Compensation and Assimilation.
  • In individuals with Autism, the total score and the Assimilation score negatively correlate with well-being.
  • In neurotypical people, all scores negatively correlate with well-being.
  • In individuals with Autism, all scores were correlated with depression and generalised anxiety.

Developer

Hull, L., Mandy, W., Lai, M.-C., Baron-Cohen, S., Allison, C., Smith, P., & Petrides, K. V. (2019). Development and Validation of the Camouflaging Autistic Traits Questionnaire (CAT-Q). Journal of Autism and Developmental Disorders, 49(3), 819–833. https://doi.org/10.1007/s10803-018-3792-6

References

Hull, L., Lai, M.-C., Baron-Cohen, S., Allison, C., Smith, P., Petrides, K. V., & Mandy, W. (2020). Gender differences in self-reported camouflaging in autistic and non-autistic adults. Autism: The International Journal of Research and Practice, 24(2), 352–363. https://doi.org/10.1177/1362361319864804

Compassion Motivation and Action Scales – Compassion (CMAS-other)

Dr David Hegarty

The Compassion Motivation and Action Scales (CMAS) encompass two dimensions assessing self-compassion (CMAS-self) and compassion to others (CMAS-other; Steindl et al., 2021). In clinical practice it can be helpful to use the CMAS as an aid for formulation, given that compassionate motivation has been found to be associated with many benefits for wellbeing, including physiologically (Kim et al., 2020; Klimecki et al., 2014; Matos et al., 2017), psychologically (Kirby, 2016; MacBeth & Gumley, 2012), and relationally (Crocker & Canevello, 2012; Kirby & Laczko, 2017; Seppala et al., 2012).

The CMAS-other has three subscales:

  1. compassion intention – measuring the intent to be compassionate towards others
  2. compassion distress tolerance – measuring the ability to tolerate distress when others are experiencing suffering
  3. compassionate action – measuring compassionate actions and behaviours towards others
This measure can be integrated into compassion-based interventions, where there is a substantial research base showing improvements in compassion leads to a reduction in depression, anxiety and psychological distress symptoms, improving well-being and is associated with increased mindfulness (Kirby et al., 2017). The CMAS-other was designed to be specifically used as a measure of the change in compassionate motivation and action over time in clinical practice and intervention research.

Psychometric Properties

The CMAS-other was developed by Steindl et al. (2021) using an initial item pool that was generated on the basis of a review of existing measures in combination with the dimensions of motivational language in motivational interviewing. The initial item pool was disseminated to international experts in compassion and/or motivational interviewing literature for feedback and to ensure that wording and content were culturally relevant. Following this process, the initial pool of items was evaluated via exploratory and confirmatory factor analysis to reduce the items further.

There was very good internal consistency present for the CMAS-other with an overall Chronbach’s alpha of 0.88 and subscale consistencies of 0.87 (Intention), 0.88 (Distress tolerance), and 0.96 (Action).

For 621 adults from Australia, USA, UK, and New Zealand, the mean score was 61.16 (SD = 10.22) for the CMAS-other, 17.19 (SD = 3.24) for the Intention subscale, 17.08 (SD = 3.27) for the Distress Tolerance subscale, and 26.90 (SD = 7.43) for the Action subscale (Steindl et al., 2021).

Scoring and Interpretation 

All items are summed to provide an overall score, with higher scores indicative of more self-compassion. Subscale scores are also provided to enable a comparison between subscales:

  1. compassion intention (items 1, 2, 3) – measuring the intent to be compassionate towards others
  2. compassion distress tolerance (items 4, 5, 6) – measuring the ability to tolerate distress when others are experiencing suffering
  3. compassionate action (items 7, 8, 9, 10, 11, 12) – measuring compassionate actions and behaviours

A normative percentile for the total score and subscales are calculated based on a normative sample (Steindl et al., 2021), indicating how the respondent scored in relation to a typical pattern of responding for adults. For example, a percentile of 83 or less indicates the individual has more self-compassion than 83 percent of the normal population.

Results are presented in a graph, which indicates the percentile for total compassion and sub-scales compared to the normative sample, with a dotted line at 50 indicating average compassion towards others.

Developer

Steindl, S. R., Tellegen, C. L., Filus, A., Seppälä, E., Doty, J. R., & Kirby, J. N. (2021). The Compassion Motivation and Action Scales: a self-report measure of compassionate and self-compassionate behaviours. Australian Psychologist, 56(2), 93–110. https://doi.org/10.1080/00050067.2021.1893110  

Adverse Childhood Experiences Questionnaire (ACE-Q)

Dr David Hegarty

The Adverse Childhood Experiences Questionnaire (ACE-Q) is a 10-item measure to quantify instances of adverse or traumatic experiences that the client has had before the age of 18. The ACE-Q checks for the client’s exposure to childhood psychological, physical, and sexual abuse as well as household dysfunction including domestic violence, substance use, and incarceration.

The ACE-Q can be administered in a self-report manner (for adults or teenagers) or can be reported by parents to indicate the experiences of their child. Given some of the questions may be triggering for trauma clients, some clinicians opt to read the questions to the client and answer the ACE-Q in a collaborative way rather than request self-report.

Clinically, the ACE-Q can be used to help inform treatment because of the connection between adverse childhood experiences, social issues, and adult mental and physical health. The ACE-Q can also help those who have a high score become more informed about their increased risk factor for health issues as well as validate their experiences. People with high scores are likely to benefit from interventions that support their mental health and promote the development of adaptive behaviours.

The ACE-Q was used in the Adverse Childhood Experiences (ACE) Study (Felitti et al., 1998), which found that the ACE-Q score is correlated with later life mental health challenges as well as health risk behaviours (including substance abuse) and serious health problems. These include increased risk for depression, suicide attempts, alcoholism, drug abuse, smoking, 50 or more sexual partners, physical inactivity, severe obesity, sexually transmitted disease, increased risk for broken bones, heart disease, lung disease, liver disease, and multiple types of cancer (Felitti et al., 1998).

Psychometric Properties

The ACE Study was completed on over 9,500 individual adults ranging in age from 19 to 92 years of age (Felitti et al., 1998). The ACE Study found that the higher someone’s ACE-Q score – the more types of childhood adversity a person experienced – the higher their risk of chronic disease, mental illness, violence, being a victim of violence and several other consequences.

A graded dose-response association has been found between ACE-Q score and risk for depression, risk for PTSD, relationship problems, emotional distress, worker performance, financial problems, current family problems, high stress, and inability to control anger (Anda et al., 2004; Hillis et al., 2004; Nurius, Logan-Greene, & Green, 2012; Ramiro et al., 2010). High ACE-Q scores also predict risk for homelessness which is especially prevalent in individuals with comorbid substance use disorders and mental illness (Patterson, Moniruzzaman, & Somers, 2014). Findings also suggest that people cannot merely “age out” of the mental health effects of ACEs; adults over the age of 65 with higher ACEs have increased odds of mood and personality disorders (Raposo, Mackenzie, Henriksen, & Afifi, 2014). Compared to people with an ACE-Q score of 0, people with an ACE-Q score of 6 are more likely to have a shorter lifespan by 20 years.

Scoring and Interpretation 

A response of Yes for each question is summed to provide an overall ACE-Q score (out of 10). The higher the score, the more adverse childhood experiences the client has had and the higher the risk for social, mental, or other wellbeing problems. The majority of all adults (52%–75%) score one or higher on the ACE-Q (CDC, 2010; Edwards et al., 2007; Ford et al., 2011; Ramiro et al., 2010; Rothman, Bernstein, & Strunin, 2010).

Scores of 4 or more are considered clinically significant. A minority (5%–10%) of the general population score 4 or more, where the general long-term health consequences become most pronounced (Hughes et al., 2017).

Compared with people who have an ACE-Q score of 0, people with an ACE-Q score of 4 are twice as likely to be smokers, 5 times more likely to have depression, 7 times more likely to be alcoholic, 10 times more likely to take illicit drugs, and 12 times more likely to attempt suicide.

Developer

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. https://doi.org/10.1016/s0749-3797(98)00017-8

References

Anda, R. F., Fleisher, V. I., Felitti, V. J., Edwards, V. J.,Whitfield, C. L., Dube, S. R., & Williamson, D. F. (2004).Childhood abuse, household dysfunction, and indicators of impaired adult worker performance. The Permanente Journal, 8(1), 30–38.

CDC.(2010). Adverse childhood experiences reported by adults—Five states, 2009. MMWR. Morbidity and Mortality Weekly Report, 59(49), 1609–1613.

Edwards, V. J., Anda, R. F., Gu, D., Dube, S. R., & Felitti, V. J.(2007). Adverse childhood experiences and smoking persistence in adults with smoking-related symptoms and illness. The Permanente Journal, 11(2), 5–13.

Ford, E. S., Anda, R. F., Edwards, V. J., Perry, G. S., Zhao, G.,Li, C., & Croft, J. B. (2011).Adverse childhood experiences and smoking status in five states. Preventive Medicine, 53(3), 188–193. https://doi.org/10.1016/j.ypmed.2011.06.015

Hillis, S. D., Anda, R. F., Dube, S. R., Felitti, V. J.,Marchbanks, P. A., & Marks, J. S. (2004). The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial con-sequences, and fetal death. Pediatrics, 113(2),320–327.

Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D.,Butchart, A., Mikton, C.,…Dunne, M. P. (2017). The effect of multiple adverse childhood experiences on health: A systematic review and meta-analysis. Lancet Public Health,2(8), e356–e366. https://doi.org/10.1016/S2468-2667(17)30118-4

Nurius, P. S., Logan-Greene, P., & Green, S. (2012). Adverse childhood experiences (ACE) within a social disadvantage framework: Distinguishing unique, cumulative, and moderated contributions to adult mental health. Journal of Prevention & Intervention in theCommunity, 40(4), 278–290. https://doi.org/10.1080/10852352.2012.707443

Patterson,M. L., Moniruzzaman, A., & Somers, J. M. (2014).Setting the stage for chronic health problems:Cumulative childhood adversity among homeless adults with mental illness in Vancouver, British Columbia. BMC Public Health, 14, 350. https://doi.org/10.1186/1471-2458-14-350

Ramiro, L. S., Madrid, B. J., & Brown, D. W. (2010). Adverse childhood experiences (ACE) and health-risk behaviors among adults in a developing country setting. Child Abuse & Neglect, 34(11), 842–855. https://doi.org/10.1016/j.chiabu.2010.02.012

Raposo, S. M., Mackenzie, C. S., Henriksen, C. A., &Afifi, T. O. (2014). Time does not heal all wounds:Older adults who experienced childhood adversities have higher odds of mood, anxiety, and personality disorders. The American Journal of Geriatric Psychiatry: Official Journal of the American Association for Geriatric Psychiatry, 22(11),1241–1250. https://doi.org/10.1016/j.jagp.2013.04.009

Rothman, E. F., Bernstein, J., & Strunin, L. (2010). Why might adverse childhood experiences lead to under-age drinking among US youth? Findings from an emergency department-based qualitative pilot study. Substance Use & Misuse,45(13), 2281–2290. https://doi.org/10.3109/10826084.2010.482369

Fatigue Assessment Scale (FAS)

Dr David Hegarty

The Fatigue Assessment Scale (FAS) is a 10-item self-report scale evaluating symptoms of chronic fatigue. The FAS treats fatigue as a unidimensional construct and does not separate its measurement into different factors. However, in order to ensure that the scale evaluates all aspects of fatigue, it measures both physical and mental symptoms.

Fatigue is a major problem in a wide range of (chronic) diseases and is the most frequently described symptom and is globally recognised as a disabling symptom. Fatigue is defined as “an experience of tiredness, dislike of present activity, and unwillingness to continue”, or as a “disinclination to continue performing the task at hand and a progressive withdrawal of attention” from environmental demands.

As a gradual and cumulative process, fatigue reflects vigilance decrement and decreased capacity to perform, along with subjective states that are associated with this decreased performance. It is a general psychophysiological phenomenon that diminishes the ability of the individual to perform a particular task by altering alertness and vigilance, together with the motivational and subjective states that occur during this transition. Consequently, there is reduced competence and willingness to develop or maintain goal directed behaviour aimed at adequate performance.

This scale can be useful in tracking fatigue over time in the context of psychiatric conditions, physical illness or chronic fatigue syndrome.

Psychometric Properties

The FAS has an internal consistency of .90 (Michielsen, De Vries, & Van Heck, 2003). Results on the scale also correlated highly with the fatigue-related subscales of other measures like the Checklist Individual Strength (Vercoulen et al., 1999).

For 351 adults between the ages of 21 and 65 who worked 20 or more hours per week, the mean score was 19.26 (SD = 6.52) (Michielsen et al., 2003).

Scoring and Interpretation 

The total score ranges from 10 to 50, with a higher score indicating more severe fatigue.

A normative percentile for the total score is calculated based on an adult sample (Michielsen et al., 2003), indicating how the respondent scored in relation to a typical pattern of responding for adults. For example, a percentile of 90 indicates the individual has more fatigue than 90 percent of the normal population.

Scores above 22 represent significant fatigue (De Vries et al., 2004), which corresponds to a normative percentile of 65. A horizontal dotted line is indicated on the Total Percentile graph for this cutoff score.

A description of the fatigue experienced is presented for the total score where:

  • less than 22 indicates “normal” (i.e. healthy) levels of fatigue
  • between 22 and 34 indicates mild-to-moderate fatigue
  • 35 or more indicates severe fatigue (Hendricks et al., 2018).

There are two subscales:

  1. Mental fatigue (sum of items 3, 6, 7, 8, and 9) – a measure of the cognitive impacts of fatigue for the client (e.g. lack of motivation, problems beginning tasks, problems thinking).
  2. Physical fatigue (sum of items 1, 2, 4, 5 and 10) – a measure of the physical impacts of fatigue for the client (e.g. physical exhaustion, lack of energy).

Developer

Michielsen, H. J., De Vries, J., & Van Heck, G. L. (2003). Psychometric qualities of a brief self-rated fatigue measure the fatigue assessment scale. Journal of Psychosomatic Research, 54, 345–352.

References

De Vries, Michielsen H, Van Heck GL, Drent M. Measuring fatigue in sarcoidosis: the Fatigue Assessment Scale (FAS). Br J Health Psychol 2004; 9: 279-91. http://www.ncbi.nlm.nih.gov/pubmed/15296678

Hendriks, C., Drent, M., Elfferich, M., & De Vries, J. (2018). The Fatigue Assessment Scale: quality and availability in sarcoidosis and other diseases. Current Opinion in Pulmonary Medicine, 24(5), 495–503. https://doi.org/10.1097/MCP.0000000000000496

Vercoulen J. H. M. M., Alberts, M., & Bleijenberg, G. (1999). De checklist individual strength (CIS). Gedragstherapie, 32, 131-136.

Release of The World Health Organisation Disability Assessment Schedule (WHODAS 2.0)

NovoPsych’s assessment library has been updated with the gold-standard measure for the impact disability is having on a person’s daily functioning. The World Health Organisation Disability Assessment Schedule (WHODAS 2.0) may be especially helpful in the context of assessments related to the National Disability Insurance Scheme (NDIS), and can provide a comprehensive measure of functional impacts. The WHODAS is a practical, generic assessment instrument that can measure health and disability at population level or in clinical practice. 

There are three versions of the WHODAS included in the NovoPsych test library: 

  1. The self-report version, which can be completed by individuals 18 years of age and over.
  2. The proxy version, which can be completed by a relative, carer, or friend.
  3. The interviewer version, which can be completed by a clinician.

WHODAS captures the level of functioning in six domains of life:

  1. Cognition – understanding and communicating
  2. Mobility – moving and getting around
  3. Self-care – attending to one’s hygiene, dressing, eating and staying alone
  4. Getting along – interacting with other people
  5. Life activities – domestic responsibilities, leisure, work and school
  6. Participation – joining in community activities, participating in society

Disability is a major health issue. When global assessments are made for burden of disease, more than half of the burden of premature mortality is due to overall disability. People generally seek psychological services because a disease makes it difficult for them to do what they used to do beforehand (i.e. because they are disabled) rather than because they have a disease. As outlined by the World Health Organisation (WHO, 2010), diagnosis and assessment of disability is valuable because it can predict the factors that medical diagnosis alone fails to predict; these include:

  • service needs – What are the patient’s needs?
  • level of care – Should the patient be in primary care, specialty care, rehabilitation or another setting?
  • outcome of the condition – What will the prognosis be?
  • length of hospitalisation – How long will the patient stay as an inpatient?
  • receipt of disability benefits – Will the patient receive any funding?
  • work performance – Will the patient return to work and perform as before?
  • social integration – Will the patient return to the community and perform as before?

Disability assessment is thus useful for client care, especially in the context of NDIS funding applications, in terms of:

  • identifying needs
  • matching treatments and interventions
  • measuring outcomes and effectiveness
  • setting priorities
  • allocating resources

WHODAS provides a common metric of the impact of any health condition in terms of functioning. Being a generic measure, the instrument does not target a specific disease – it can thus be used to compare disability due to different diseases. WHODAS also makes it possible to design and monitor the impact of health and health-related interventions. The instrument has proven useful for assessing health and disability levels in the general population and in specific groups (e.g. people with a range of different mental and physical conditions). Furthermore, WHODAS makes it easier to design health and health related interventions, and to monitor their impact.

Cognitive Flexibility Inventory (CFI)

Dr David Hegarty

The Cognitive Flexibility Inventory (CFI) is a 20-item self-report measure to monitor how often individuals engaged in cognitive behavioural thought challenging interventions (Dennis & Vander Wal, 2010). Cognitive flexibility enables individuals to think adaptively when encountering stressful life events, and is a core skill that helps individuals avoid becoming stuck in maladaptive patterns of thinking. The CFI measures two aspects of cognitive flexibility:

  1. Alternatives – the adaptive ability to perceive multiple alternative explanations for life occurrences and the ability to generate multiple alternative solutions to difficult situations.
  2. Control – having an internal locus of control, or the tendency to perceive difficult situations as somewhat controllable.

Individuals with high cognitive flexibility are more likely to react adaptively in response to difficult life experiences, while cognitively inflexible individuals are more susceptible to experiencing pathological reactions. The CFI has been shown to differentiate between a clinical group (anxiety and depression) and a non-clinical sample (Johnco, Wuthrich, & Rapee, 2014), with a clinical group showing significantly lower CFI total and subscale scores than the non-clinical group.

When administered multiple times during a course of cognitive behavioural therapy the scale can be useful in indicating treatment response.

Psychometric Properties

The 20-item CFI showed high test-retest reliability for the full score (r = .81), Alternatives subscale (r = .75), and Control subscale (r = .77; Dennis & Vander Wal, 2010). Cronbach’s alpha ranged from good to excellent, for the Alternatives subscale (alpha = .91), Control subscale (alpha = .86), and the full score (alpha = .90; Dennis & Vander Wal, 2010). Furthermore, evidence was obtained for the convergent construct validity of the CFI and its two subscales via their associations with other measures of cognitive flexibility, depressive symptomatology, and coping (Dennis & Vander Wal, 2010).

In a sample of 196 university students (Dennis & Vander Wal, 2010), the mean scores where as follows:

  • CFI total – 102.98 (SD = 13.91)
  • Alternatives Subscale – 67.59 (SD = 9.41)
  • Control Subscale 35.35 (SD = 7.02)

Scoring and Interpretation 

Scores consist of a total CFI score and two subscale scores. The total score ranges between 20 and 140, where higher scores indicate more cognitive flexibility.

A normative percentile for the total score and subscales are calculated, comparing the respondents scores to a sample of university students (Dennis & Vander Wal, 2010). Percentiles help contextualise how the respondent scored in relation to a typical pattern of responding. For example, a percentile of 50 indicates the individual has more cognitive flexibility than 50 percent of the normal population. i.e. is average.

Percentiles below approximately 25 represent clinically significant inflexibility, which would be important to target within cognitive behavioural therapy (CBT). According to the CBT framework, cognitive inflexibility underpins the development and maintenance of depression and anxiety.

A graph is presented of average scores (between 1 and 7), indicating the typical response on the likert scale and normalising scores between subscales.

The two subscales measuring important aspects of cognitive flexibility are:

  • Alternatives: measuring the ability to perceive multiple alternative explanations for life occurrences and human behaviour and the ability to generate multiple alternative solutions to difficult situations.
    Range = 13 to 91
    Sum items 1, 3, 5, 6, 8, 10, 12, 13, 14, 16,18, 19, 20
  • Control: measuring the tendency to perceive difficult situations as controllable.
    Range = 7 to 49
    Sum items 2, 4, 7, 9, 11, 15, 17

Note that items 2, 4, 7, 9, 11, & 17 are reverse scored.

Developer

Dennis, J. P., & Vander Wal, J. S. (2010). The cognitive flexibility inventory: Instrument development and estimates of reliability and validity. Cognitive Therapy and Research, 34(3), 241–253. https://doi.org/10.1007/s10608-009-9276-4

References

Johnco, C., Wuthrich, V. M., & Rapee, R. M. (2014). Reliability and validity of two self-report measures of cognitive flexibility. Psychological Assessment, 26(4), 1381–1387. https://doi.org/10.1037/a0038009

Automatic Thoughts Questionnaire – Believability (ATQ-B)

Dr David Hegarty

The Automatic Thoughts Questionnaire – Believability (ATQ-B-15) (Netemeyer et al., 2002) is a 15-item self-report measure designed to assess the degree of believability of cognitions associated with depression. The scale does not measure the frequency of unhelpful thoughts, but rather measures the extent to which the client believes the thoughts to be true.

The ATQ-B is a frequently used tool in Acceptance and Commitment Therapy (ACT; Hayes, Strosahl, & Wilson, 1999). Consistent with the ACT concept of fusion, the ATQ-B asks how much the client believed a thought when they felt depressed/sad. Given that changes in believability of unhelpful thoughts occur independently of reductions in their frequency (Zettle & Hayes, 1986), the believability and fusion of thoughts is an important aspect to target in therapy (Zettle, Rains & Hayes, 2011).

The scale can also be integrated into treatment using Cognitive Behaviour Therapy.

The ATQ has been found to be a reliable measure of cognitive change in depression in response to ACT and can therefore be a useful measure of progress in therapy (Zettle et al., 2011).

Psychometric Properties

Psychometric evaluation of the ATQ-B 30-item version showed that it had good internal stability in both clinical (n = 177) and nonclinical (n = 249) populations (Cronbach’s alpha = .95 and .97, respectively; Zettle, 2010, as cited in Zettle et al., 2011). Test–retest reliability for the ATQ-B over 3 months with a non-clinical sample was .85 and it correlated significantly with the BDI for both populations (r = .53 and .58, respectively), providing evidence of the measure’s construct validity.

The ATQ-15 was developed by Netemeyer et al. (2002) from the original 30-item version (Hollon & Kendall, 1980). Netemeyer et al. (2002) assessed the ATQ-15 using two samples (N=434 and N=419) and found that it had a single factor, with an alpha of .96. Two additional cross-validation samples (N=163 and N=91) also showed support for the 15-item reduced version (Netemeyer et al.,2002).

The ATQ-15 was found to be negatively correlated with self-esteem (r = -.63) and childhood wellbeing (r = -.38) and positively correlated to social anxiety (r = .56), neurotic / obsessive thoughts (r = .70) , and pathological gambling (r = .46; Netemeyer et al., 2002).

Scoring and Interpretation 

The respondent is asked to rate how much he/she BELIEVED a given thought when they had it on a 5-point scale (1 = Not at all, to 5 = Totally). Scores are summed across the 15 items to form an ATQ-B index ranging from 15 to 75. A higher score indicates a higher level of cognitive fusion with depressive thoughts.

A descriptor is provided to give an overall indication of how ‘fused’ the client is to these thoughts. This descriptor is determined by the average response to the questions.

ATQ-B scores can be used to track progress in therapy over time. Successful therapy should see ATQ-B scores reduce over time, reflecting a reduction in fusion.

Based on ACT theory, a client’s ability to distance themselves from depressive thoughts would decrease the control exerted by these thoughts and result in a reduction of depression symptomatology.

Note that the ATQ-B does not measure the frequency of unhelpful thoughts, but rather the extent to which unhelpful thoughts are believed.

Developer

Netemeyer, R. G., Williamson, D. A., Burton, S., Biswas, D., Jindal, S., Landreth, S., Mills, G., & Primeaux, S. (2002). Psychometric properties of shortened versions of the automatic thoughts questionnaire. Educational and Psychological Measurement, 62(1), 111–129. https://doi.org/10.1177/0013164402062001008

References

Hayes, S. C., Strosahl, K., & Wilson, K. G. (1999). Acceptance and Commitment Therapy: An experiential approach to behavior change. New York: Guilford Press. 

Hollon, S. D., & Kendall, P. C. (1980). Cognitive self-statements in depression: Development of an Automatic Thoughts Questionnaire.Cognitive Therapy and Research,4, 383-395.

Netemeyer, R. G., Williamson, D. A., Burton, S., Biswas, D., Jindal, S., Landreth, S., Mills, G., & Primeaux, S. (2002). Psychometric properties of shortened versions of the automatic thoughts questionnaire. Educational and Psychological Measurement, 62(1), 111–129. https://doi.org/10.1177/0013164402062001008

Zettle, R. D., & Hayes, S. C. (1986). Dysfunctional control by client verbal behavior: The context of reason-giving. The Analysis of Verbal Behavior, 4, 30–38. https://doi.org/10.1007/BF03392813

Zettle, R. D., Rains, J. C., & Hayes, S. C. (2011). Processes of change in acceptance and commitment therapy and cognitive therapy for depression: a mediation reanalysis of Zettle and Rains. Behavior Modification, 35(3), 265–283. https://doi.org/10.1177/0145445511398344

World Health Organisation Disability Assessment Schedule 2.0 – Interview (WHODAS-interview)

Dr David Hegarty

The World Health Organisation Disability Assessment Schedule (WHODAS 2.0) is a practical, generic assessment instrument that can measure health and disability at population level or in clinical practice (World Health Organisation (WHO), 2010). This is the interview version of the WHODAS 2.0, which can be completed by a clinician for interviewing individuals 18 years of age and over. There is also a proxy version, which can be completed by a relative, carer, or friend, or a self-report version.

WHODAS 2.0 captures the level of functioning in six domains of life:

  1. Cognition – understanding and communicating
  2. Mobility – moving and getting around
  3. Self-care – attending to one’s hygiene, dressing, eating and staying alone
  4. Getting along – interacting with other people
  5. Life activities – domestic responsibilities, leisure, work and school
  6. Participation – joining in community activities, participating in society.

WHODAS 2.0 provides a common metric of the impact of any health condition in terms of functioning. Being a generic measure, the instrument does not target a specific disease – it can thus be used to compare disability due to different diseases. WHODAS 2.0 also makes it possible to design and monitor the impact of health and health-related interventions. The instrument has proven useful for assessing health and disability levels in the general population and in specific groups (e.g. people with a range of different mental and physical conditions). Furthermore, WHODAS 2.0 makes it easier to design health and health related interventions, and to monitor their impact.

Disability is a major health issue. When global assessments are made for burden of disease, more than half of the burden of premature mortality is due to overall disability. People generally seek health services because a disease makes it difficult for them to do what they used to do beforehand (i.e. because they are disabled) rather than because they have a disease. Health-care providers consider a case to be clinically significant when it limits a person’s daily activities, and they use disability information as the basis of their evaluation and planning.

Psychometric Properties

WHODAS 2.0 has excellent psychometric properties. Test–retest studies of the 36-item scale in countries across the world found it to be highly reliable, with an intra-class coefficient of 0.69–0.89 at item level; 0.93– 0.96 at domain level; and 0.98 at overall level. Cronbach’s alpha levels were generally very high (0.94 – 0.96 for domains and 0.98 for total score; WHO, 2010).

All items were selected on the basis of item-response theory and the instrument as a whole showed a robust factor structure that remained constant across cultures and different types of patient populations. Confirmatory factor analysis showed a rigorous association between the factor structure of the items and the domains, and between the domains and a general disability factor. These results support the unidimensionality of domains.The validation studies also showed that WHODAS 2.0 compared well with other measures of disability or health status, and with clinician and proxy ratings.

The WHODAS 2.0 shows sensitivity to change in people who have certain health conditions (e.g. cataract, hip or knee problems, depression, schizophrenia or alcohol problems), as it can pick up improvements in functioning following treatment.

Scoring and Interpretation 

There are three scoring methods used for the WHODAS 2.0:

  1. Simple score
  2. Complex score (and its percentile)
  3. Average score (and its descriptor)

In simple scoring, the scores assigned to each of the items (1-36) are simply added up without recoding or collapsing of response categories; thus, there is no weighting of individual items. Simple scoring of WHODAS is specific to the sample at hand and should not be assumed to be comparable across populations. The simple sum of the scores of the items across all domains constitutes a statistic that is sufficient to describe the degree of functional limitations. The domain scores provide more detailed information than the summary score and may be useful for comparing individuals or groups against one another or against population standards, and across time (e.g. before and after interventions or other comparisons).

The more complex method of scoring is called “item-response-theory” (IRT) based scoring; it takes into account multiple levels of difficulty for each WHODAS 2.0 item (1-36). This type of scoring for WHODAS 2.0 allows for more fine-grained analyses that make use of the full information of the response categories for comparative analysis across populations or subpopulations. It takes the coding for each item response as “none”, “mild”, “moderate”, “severe” and “extreme” separately, and then summarises the score by differentially weighting the items and the levels of severity. Converting the summary score into a metric ranging from 0 to 100 (where 0 = no disability; 100 = full disability). A percentile is provided that allows for a comparison to a large sample (n = 1,431) from a wide variety of populations (general population, populations with physical problems, populations with mental or emotional problems, populations with alcohol and drug use problems) from over 21 countries (WHO, 2010). A percentile of 50 indicates that an individual is experiencing an average level of disability when compared to other members of the sample.

The average scores are comparable to the WHODAS 5-point scale, which allows the clinician to think of the individual’s disability in terms of none (0-0.49), mild (0.5-1.49), moderate (1.5-2.49), severe (2.5-3.49), or extreme (3.5-4). The average domain and general disability scores were found to be reliable, easy to use, and clinically useful to the clinicians in the DSM-5 Field Trials (APA, 2021). The average domain score is calculated by dividing the raw domain score by the number of items in the domain (e.g., if all the items within the “understanding and communicating” domain are rated as being moderate then the average domain score would be 18/6 = 3, indicating moderate disability). The average general disability score is calculated by dividing the raw overall score by number of items in the measure (i.e., 36).

The three scoring methods are used for each of the 6 domains:

  1. Cognition – Assesses communication and thinking activities; specific areas assessed include concentrating, remembering, problem solving, learning and communicating.
  2. Mobility – Assesses activities such as standing, moving around inside the home, getting out of the home and walking a long distance.
  3. Self-care – Assesses hygiene, dressing, eating and staying alone.
  4. Getting along – Assesses interactions with other people and difficulties that might be encountered with this life domain due to a health condition; in this context, “other people” includes those known intimately or well (e.g. spouse or partner, family members or close friends) and those not known well (e.g. strangers).
  5. Life activities – Assesses difficulty with day-to-day activities (i.e. those that people do on most days, including those associated with domestic responsibilities, leisure, work and school).
  6. Participation – Assesses social dimensions, such as community activities; barriers and hindrances in the world around the respondent; and problems with other issues, such as maintaining personal dignity.

Developer

Ustun, T.B, Kostanjsek, N., Chatterji, S., Rehm, J (Ed.). (2010). Measuring health and disability : manual for WHO Disability Assessment Schedule (‎WHODAS 2.0)‎. World Health Organization. https://www.who.int/publications/i/item/measuring-health-and-disability-manual-for-who-disability-assessment-schedule-(-whodas-2.0)

References

American Psychiatric Association. Online Assessment Measures. (n.d.). Retrieved November 6, 2021, from https://www.psychiatry.org/File%20Library/Psychiatrists/Practice/DSM/APA_DSM5_WHODAS-2-Self-Administered.pdf

World Health Organisation Disability Assessment Schedule 2.0 – Proxy (WHODAS-proxy)

Dr David Hegarty

The World Health Organisation Disability Assessment Schedule (WHODAS 2.0) is a practical, generic assessment instrument that can measure health and disability at population level or in clinical practice (World Health Organisation (WHO), 2010). This is the proxy version, which can be completed by a relative, carer, or friend, on behalf of individuals 18 years of age and over. There is also an interviewer version, which can be completed by a clinician, or a self-report version.

WHODAS 2.0 captures the level of functioning in six domains of life:

  1. Cognition – understanding and communicating
  2. Mobility – moving and getting around
  3. Self-care – attending to one’s hygiene, dressing, eating and staying alone
  4. Getting along – interacting with other people
  5. Life activities – domestic responsibilities, leisure, work and school
  6. Participation – joining in community activities, participating in society.

WHODAS 2.0 provides a common metric of the impact of any health condition in terms of functioning. Being a generic measure, the instrument does not target a specific disease – it can thus be used to compare disability due to different diseases. WHODAS 2.0 also makes it possible to design and monitor the impact of health and health-related interventions. The instrument has proven useful for assessing health and disability levels in the general population and in specific groups (e.g. people with a range of different mental and physical conditions). Furthermore, WHODAS 2.0 makes it easier to design health and health related interventions, and to monitor their impact.

Disability is a major health issue. When global assessments are made for burden of disease, more than half of the burden of premature mortality is due to overall disability. People generally seek health services because a disease makes it difficult for them to do what they used to do beforehand (i.e. because they are disabled) rather than because they have a disease. Health-care providers consider a case to be clinically significant when it limits a person’s daily activities, and they use disability information as the basis of their evaluation and planning.

Psychometric Properties

WHODAS 2.0 has excellent psychometric properties. Test–retest studies of the 36-item scale in countries across the world found it to be highly reliable, with an intra-class coefficient of 0.69–0.89 at item level; 0.93– 0.96 at domain level; and 0.98 at overall level. Cronbach’s alpha levels were generally very high (0.94 – 0.96 for domains and 0.98 for total score; WHO, 2010).

All items were selected on the basis of item-response theory and the instrument as a whole showed a robust factor structure that remained constant across cultures and different types of patient populations. Confirmatory factor analysis showed a rigorous association between the factor structure of the items and the domains, and between the domains and a general disability factor. These results support the unidimensionality of domains.The validation studies also showed that WHODAS 2.0 compared well with other measures of disability or health status, and with clinician and proxy ratings.

The WHODAS 2.0 shows sensitivity to change in people who have certain health conditions (e.g. cataract, hip or knee problems, depression, schizophrenia or alcohol problems), as it can pick up improvements in functioning following treatment.

Scoring and Interpretation 

There are three scoring methods used for the WHODAS 2.0:

  1. Simple score
  2. Complex score (and its percentile)
  3. Average score (and its descriptor)

In simple scoring, the scores assigned to each of the items (1-36) are simply added up without recoding or collapsing of response categories; thus, there is no weighting of individual items. Simple scoring of WHODAS is specific to the sample at hand and should not be assumed to be comparable across populations. The simple sum of the scores of the items across all domains constitutes a statistic that is sufficient to describe the degree of functional limitations. The domain scores provide more detailed information than the summary score and may be useful for comparing individuals or groups against one another or against population standards, and across time (e.g. before and after interventions or other comparisons).

The more complex method of scoring is called “item-response-theory” (IRT) based scoring; it takes into account multiple levels of difficulty for each WHODAS 2.0 item (1-36). This type of scoring for WHODAS 2.0 allows for more fine-grained analyses that make use of the full information of the response categories for comparative analysis across populations or subpopulations. It takes the coding for each item response as “none”, “mild”, “moderate”, “severe” and “extreme” separately, and then summarises the score by differentially weighting the items and the levels of severity. Converting the summary score into a metric ranging from 0 to 100 (where 0 = no disability; 100 = full disability). A percentile is provided that allows for a comparison to a large sample (n = 1,431) from a wide variety of populations (general population, populations with physical problems, populations with mental or emotional problems, populations with alcohol and drug use problems) from over 21 countries (WHO, 2010). A percentile of 50 indicates that an individual is experiencing an average level of disability when compared to other members of the sample.

The average scores are comparable to the WHODAS 5-point scale, which allows the clinician to think of the individual’s disability in terms of none (0-0.49), mild (0.5-1.49), moderate (1.5-2.49), severe (2.5-3.49), or extreme (3.5-4). The average domain and general disability scores were found to be reliable, easy to use, and clinically useful to the clinicians in the DSM-5 Field Trials (APA, 2021). The average domain score is calculated by dividing the raw domain score by the number of items in the domain (e.g., if all the items within the “understanding and communicating” domain are rated as being moderate then the average domain score would be 18/6 = 3, indicating moderate disability). The average general disability score is calculated by dividing the raw overall score by number of items in the measure (i.e., 36).

The three scoring methods are used for each of the 6 domains:

  1. Cognition – Assesses communication and thinking activities; specific areas assessed include concentrating, remembering, problem solving, learning and communicating.
  2. Mobility – Assesses activities such as standing, moving around inside the home, getting out of the home and walking a long distance.
  3. Self-care – Assesses hygiene, dressing, eating and staying alone.
  4. Getting along – Assesses interactions with other people and difficulties that might be encountered with this life domain due to a health condition; in this context, “other people” includes those known intimately or well (e.g. spouse or partner, family members or close friends) and those not known well (e.g. strangers).
  5. Life activities – Assesses difficulty with day-to-day activities (i.e. those that people do on most days, including those associated with domestic responsibilities, leisure, work and school).
  6. Participation – Assesses social dimensions, such as community activities; barriers and hindrances in the world around the respondent; and problems with other issues, such as maintaining personal dignity.

Developer

Ustun, T.B, Kostanjsek, N., Chatterji, S., Rehm, J (Ed.). (2010). Measuring health and disability : manual for WHO Disability Assessment Schedule (‎WHODAS 2.0)‎. World Health Organization. https://www.who.int/publications/i/item/measuring-health-and-disability-manual-for-who-disability-assessment-schedule-(-whodas-2.0)

References

American Psychiatric Association. Online Assessment Measures. (n.d.). Retrieved November 6, 2021, from https://www.psychiatry.org/File%20Library/Psychiatrists/Practice/DSM/APA_DSM5_WHODAS-2-Self-Administered.pdf

Perceived Stress Scale (PSS-10)

Dr David Hegarty

The Perceived Stress Scale (PSS-10; Cohen, Kamarch, & Mermelstein,1983) is a popular tool for measuring psychological stress. It is a self-reported questionnaire that was designed to measure the degree to which situations in one’s life are appraised as stressful. The PSS-10 determines how unpredictable, uncontrollable, and overloaded respondents find their lives. The scale also includes a number of direct queries about current levels of experienced stress. The PSS was designed for use in community samples with at least some high school education. The assessed items are general in nature rather than focusing on specific events or experiences.

Because levels of appraised stress are influenced by daily hassles, major events, and changes in coping resources, predictive validity of the PSS-10 falls off rapidly after four to eight weeks (Cohen et al., 1983).

Psychometric Properties

There have been three versions of the PSS developed. The original instrument is a 14-item scale (PSS-14) that was developed in English (Cohen et al.,1983), which was subsequently shortened to 10 items (PSS-10) using factor analysis based on data from 2,387 U.S. residents. A four-item PSS (PSS-4) was also introduced (Cohen & Williamson, 1988), but its psychometric properties are questionable (Lee, 2012; Taylor, 2015). According to Cohen’s Laboratory for the Study of Stress, Immunity, and Disease (2021), the PSS is currently translated into 25 languages other than English.

Lee (2012) conducted a review of the psychometric properties of all three versions of the PSS and found that the psychometric properties of the PSS-10 are superior to those of the PSS-14 and PSS-4. The Cronbach’s alpha of the PSS-10 was evaluated at >.70 in all 12 studies in which it was used. The test-retest reliability of the PSS-10 was assessed in four studies, and met the criterion of >.70 in all cases. The criterion validity of PSS-10 was evaluated and it was strongly correlated with the mental component of health status as measured by the Medical Outcomes Study – Short Form 36 (Ware, Snow, Kosinski, & Grandek, 1993). The PSS was either moderately or strongly correlated with the hypothesised emotional variables, such as depression or anxiety, as measured using the Center for Epidemiologic Studies Depression Scale (Radloff, 1977), Inventory to Diagnose Depression (Zimmerman & Coryell, 1987), Beck Depression Inventory (Beck, Steer, & Garbin, 1988), Hospital Anxiety and Depression Scale (Zigmond & Snaith, 1983), State-Trait Anxiety Inventory (Spielberger, 1983), General Health Questionnaire (Goldberg & Williams, 1991), Edinburgh Postnatal Depression Scale (Cox, Holden, & Sagovsky,1987), Thai Depression Inventory (Lotrakul & Sukanich, 1999), and Depression Anxiety Stress Scale – 21 (Lyrakos, Arvaniti, Smyrnioti, & Kostopanahiotou, 2011).

A CFA by Taylor (2015) found that a 2 factor model best describes the PSS-10:

  1. Perceived helplessness
  2. Lack of self-efficacy

Norms were determined for the total score (by age) for a sample of 2,000 community-based respondents in the US (Cohen & Janicki-Deverts, 2012):

  • < 25 years old (mean = 16.78, SD = 6.86)
  • 25-34 years old (mean = 17.46, SD = 7.31)
  • 35-44 years old (mean = 16.38, SD = 7.07)
  • 45-54 years old (mean = 16.94, SD = 7.83)
  • 55-64 years old (mean = 14.50, SD = 7.20)
  • > 64 years old (mean = 11.09, SD = 6.77)

Scoring and Interpretation 

A total PSS-10 score from 0 to 40 is presented, with higher scores representing higher levels of stress. Percentiles are also presented, comparing the results to a community sample (Cohen & Janicki-Deverts, 2012). A percentile of 50 indicates that an individual is experiencing an average level of stress when compared to other members of society. Average scores are also calculated by summing the scores divided by the number of items, and is a useful metric for ascertaining the general level of agreement on the likert scale (where 0 = Never and 4 = Very Often), as well as comparing sub-scale scores using a consistent metric.

There are two subscales in the PSS-10:

  1. Perceived helplessness (items 1, 2, 3, 6, 9, 10) – measuring an individual’s feelings of a lack of control over their circumstances or their own emotions or reactions.
  2. Lack of self-efficacy (items 4, 5, 7, 8) – measuring an individual’s perceived inability to handle problems.

Higher levels of psychological stress as measured by the PSS-10 have been associated with elevated markers of biological aging, higher cortisol levels, as well as suppressed immune function, greater infection-induced release of pro-inflammatory cytokines, greater susceptibility to infectious disease, slower wound healing, and higher prostate-specific antigen levels (Cohen & Janicki-Deverts, 2012). Persons who score higher on the PSS also report poorer health practices, such as sleeping fewer hours, skipping breakfast, and consuming greater quantities of alcohol (Cohen &Williamson, 1988).

Developer

Cohen, S., & Williamson, G. (1988). Perceived stress in a probability sample of the United States. In S. Spacapan & S. Oskamp (Eds.), The social psychology of health: Claremont Symposium on applied social psychology. Newbury Park, CA: Sage.

References

Cohen, S., & Janicki-Deverts, D. (2012). Who’s stressed? Distributions of psychological stress in the United States in probability samples from 1983, 2006, and 20091. Journal of Applied Social Psychology, 42(6), 1320–1334. https://doi.org/10.1111/j.1559-1816.2012.00900.x

Cohen, S., Kamarch, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 385.

Cohen’s Laboratory for the Study of Stress, Immunity and Disease. (2021). Dr.Cohen’s Scales. Retrieved Oct 9, 2021, from https://www.cmu.edu/dietrich/psychology/stress-immunity-disease-lab/scales/index.html

Cohen, S., & Williamson, G. (1988). Perceived stress in a probability sample of the United States. In S. Spacapan, & S. Oskamp (Eds.),The social psychology of health: Claremont symposium on applied social psychology. Newbury Park, CA: Sage.

Lee, E.-H. (2012). Review of the psychometric evidence of the perceived stress scale. Asian Nursing Research, 6(4), 121–127. https://doi.org/10.1016/j.anr.2012.08.004

Taylor, J. M. (2015). Psychometric analysis of the Ten-Item Perceived Stress Scale. Psychological Assessment, 27(1), 90–101. https://doi.org/10.1037/a0038100

Psychologist Norms for the Professional Quality of Life Scale (ProQOL)

Hegarty, D., Buchanan, B. ( 2021, November 29).  Psychologist Norms for the Professional Quality of Life Scale (ProQOL). NovoPsych

The Professional Quality of Life Scale (ProQOL) is a 30 item self-report questionnaire designed to measure compassion fatigue, work satisfaction and burnout in helping professionals. Helping professionals are defined broadly, from those in health care settings, such as psychologists, nurses and doctors, to social service workers, teachers, police officers, firefighters or other first responders. It is useful for workers who perform emotional labour as well as professionals who are exposed to traumatic situations. While the scale is useful for many professionals, this paper outlines how NovoPsych created norms specific to Australian Psychologists, so that they can compare their experiences  at work to peers. 

Professional Quality of Life is the quality one feels in relation to one’s work as a helper. Both the positive and negative aspects of doing one’s job influence one’s professional quality of life. The ProQOL measures three aspects of professional quality of life: 

  • Compassion Satisfaction (pleasure you derive from being able to do your work well) 
  • Burnout (exhaustion, frustration, anger and depression related to work) 
  • Secondary Traumatic Stress (feeling fear in relation to work‐related primary or secondary trauma) 

The scale is particularly useful for professionals to self-monitor their satisfaction and as a prompt for self-care. With burnout and compassion fatigue being workplace hazards for psychologists it is worth considering how these professionals can monitor workplace well-being and respond to the inevitable challenges.  

Method

To determine the level of compassion satisfaction and compassion fatigue (burnout and secondary trauma) for psychologists, NovoPsych emailed its users in November 2020 and asked them to complete the ProQOL for self evaluation and research purposes. As a result, 245 psychologists completed the assessment and contributed to our normative data. 

Data Cleaning

To validate the integrity of the data, various anomalies were identified. Firstly, overall scores were assessed to see if there were any results that were significantly different (i.e. > 3 S.D. outside the mean) to other scores. There was only one result that was significantly higher (4.8 S.D. above the mean) than other scores, but upon closer inspection, this response indicated a high score in the secondary trauma scale, whereas the other scales were similar to all other scores. Therefore, this data was assumed to be valid and was not removed. When looking at the time taken to complete the assessment, there were some outliers (n = 3) where respondents took significantly longer (> 3 S.D.) than the mean (236 seconds) to complete the assessment. However, upon closer examination, these responses did appear to be legitimate given there was variety in the response pattern and the scores themselves were not outliers. Therefore, it was assumed that this could have been a busy psychologist who started to self-administer the assessment, got distracted, and came back to finish the assessment at a later stage. As a result, the responses were considered to be valid and were not removed.

Therefore, there were no responses removed as a result of this data tidying process and the final sample size for the NovoPsych ProQOL psychologist data was 245. This final data presented as an approximate normal distribution for the total scores (see Figure 1), although the time taken to complete data was very right-skewed (see Figure 2).

Figure 1. Distribution of total raw scores for NovoPsych ProQOL psychologist data. A theoretical normal distribution is shown in red.

Figure 2. Distribution of time taken to complete the ProQOL.

Results

The distribution of the raw scores for each of the subscales for the NovoPsych psychologist data for the ProQOL were approximately normally distributed (see Figure 3). However, it can be seen that the Compassion Satisfaction subscale appeared to have a higher score than both the Burnout and Secondary Trauma scales.  

Figure 3. Distribution of raw scores for each subscale of the NovoPsych ProQOL psychologist data. 

When the distribution of the percentiles are shown (see Figure 4), it can be seen that the distribution for both the Burnout and Secondary Trauma subscales are skewed left. According to the standard ProQOL norms (Stamm, 2010)  for “helping professionals” in general, the psychologists who completed the ProQOL in this sample were quite ‘burnt out’ and were suffering from an extreme amount of secondary trauma, with only 2 respondents being below the 50th percentile. Significantly, over 22% (n = 56) of respondents scored above the 95th percentile and over 52% (n = 129) of respondents scored above the 90th percentile for the Secondary Trauma subscale. The Compassion Satisfaction percentiles were more evenly distributed. 

Using the standard ProQOL norms, the percentiles for the Burnout and Secondary Trauma subscales are slightly unusual, indicating that they are not representative of the typical experience of psychologists. The raw scores for both these scales are quite well distributed and there doesn’t appear to be any significant floor or ceiling effects, although there are a few low scores on the Secondary Trauma subscale. However, when these scores are converted into percentiles using the standard ProQOL norms, especially for the Secondary Trauma subscale, they are very skewed. There could be two possible explanations for these results.

Firstly, all the psychologists who responded to the ProQOL during this time period are bordering on burnout and are suffering from quite significant secondary trauma. We therefore looked at de-identified self-assessment data collected from January 2021 to November 2021 to see any impact of time (given lockdowns and COVID), and did not find a significant difference. We therefore concluded that the sample in November 2020 was a representative sample. 

Secondly, it could be that the standard norms used for the ProQOL are inappropriate for use by psychologists. That is, the standard norms published on the ProQOL manual convert into percentiles that are too high.

Figure 4. The distribution of percentiles for the NovoPsych ProQOL psychologist data. 

Given these unusual findings, it is questionable as to whether the existing standard norms of the ProQOL are suitable for use amongst psychologists to monitor their wellbeing. Therefore, it was decided to use our own norms for the purposes of giving psychologists a better understanding of their own levels of compassion satisfaction and compassion fatigue. As a result of this process, we can now present the means and standard deviations for each subscale of the NovoPsych ProQOL psychologist data (see Table 1).

We also developed a percentile table for all subscales (see Table 2). This was developed by the Nearest-Rank method. 

Discussion

The standard ProQOL norms (Stamm, 2010) appear to be unsuitable for use by psychologists in monitoring their own wellbeing in the form of compassion satisfaction and compassion fatigue. This is due to calculated percentiles providing an apparent inflated sense of potential problems, particularly on the Burnout and Secondary Trauma subscales. As a result, the new norms developed by NovoPsych allow psychologists to monitor their compassion fatigue in a more reliable, accurate, and useful manner. All this analysis and data is synthesized and presented when a NovoPsych user self-administers the ProQOL or administers it to a client. 

References

Stamm, B.H. (2010). The Concise ProQOL Manual, 2nd Ed. Pocatello, ID: ProQOL.org. Retrieved November 13, 2021, from https://www.researchgate.net/profile/Beth-Stamm/publication/340033923_The_Concise_ProQOL_Manual_The_concise_manual_for_the_Professional_Quality_of_Life_Scale_2_nd_Edition/links/5e73a313299bf134dafd884f/The-Concise-ProQOL-Manual-The-concise-manual-for-the-Professional-Quality-of-Life-Scale-2-nd-Edition.pdf

The World Health Organisation Disability Assessment Schedule (WHODAS 2.0) – Self-Report Version

Dr David Hegarty

The World Health Organisation Disability Assessment Schedule (WHODAS 2.0) is a practical, generic assessment instrument that can measure health and disability at population level or in clinical practice (World Health Organisation (WHO), 2010). This is the self-report version of the WHODAS 2.0 for use by individuals 18 years of age and over. There is also a proxy version, which can be completed by a relative, carer, or friend, or an interviewer version, which can be completed by a clinician.

WHODAS 2.0 captures the level of functioning in six domains of life:

  1. Cognition – understanding and communicating
  2. Mobility – moving and getting around
  3. Self-care – attending to one’s hygiene, dressing, eating and staying alone
  4. Getting along – interacting with other people
  5. Life activities – domestic responsibilities, leisure, work and school
  6. Participation – joining in community activities, participating in society.

WHODAS 2.0 provides a common metric of the impact of any health condition in terms of functioning. Being a generic measure, the instrument does not target a specific disease – it can thus be used to compare disability due to different diseases. WHODAS 2.0 also makes it possible to design and monitor the impact of health and health-related interventions. The instrument has proven useful for assessing health and disability levels in the general population and in specific groups (e.g. people with a range of different mental and physical conditions). Furthermore, WHODAS 2.0 makes it easier to design health and health related interventions, and to monitor their impact.

Disability is a major health issue. When global assessments are made for burden of disease, more than half of the burden of premature mortality is due to overall disability. People generally seek health services because a disease makes it difficult for them to do what they used to do beforehand (i.e. because they are disabled) rather than because they have a disease. Health-care providers consider a case to be clinically significant when it limits a person’s daily activities, and they use disability information as the basis of their evaluation and planning.  

Psychometric Properties

WHODAS 2.0 has excellent psychometric properties. Test–retest studies of the 36-item scale in countries across the world found it to be highly reliable, with an intra-class coefficient of 0.69–0.89 at item level; 0.93– 0.96 at domain level; and 0.98 at overall level. Cronbach’s alpha levels were generally very high (0.94 – 0.96 for domains and 0.98 for total score; WHO, 2010).

All items were selected on the basis of item-response theory and the instrument as a whole showed a robust factor structure that remained constant across cultures and different types of patient populations. Confirmatory factor analysis showed a rigorous association between the factor structure of the items and the domains, and between the domains and a general disability factor. These results support the unidimensionality of domains.The validation studies also showed that WHODAS 2.0 compared well with other measures of disability or health status, and with clinician and proxy ratings.

The WHODAS 2.0 shows sensitivity to change in people who have certain health conditions (e.g. cataract, hip or knee problems, depression, schizophrenia or alcohol problems), as it can pick up improvements in functioning following treatment.  

Scoring and Interpretation 

There are two scoring methods used for the WHODAS 2.0:

  1. Score (and its percentile)
  2. Average score (and its descriptor)

The first score is determined using “item-response-theory” (IRT), where it takes into account multiple levels of difficulty for each WHODAS 2.0 item (1-36). This type of scoring for WHODAS 2.0 allows for more fine-grained analyses that make use of the full information of the response categories for comparative analysis across populations or subpopulations. It takes the coding for each item response as “none”, “mild”, “moderate”, “severe” and “extreme” separately, and then summarises the score by differentially weighting the items and the levels of severity. Converting the summary score into a metric ranging from 0 to 100 (where 0 = no disability; 100 = full disability). A percentile is provided that allows for a comparison to a large sample (n = 1,431) from a wide variety of populations (general population, populations with physical problems, populations with mental or emotional problems, populations with alcohol and drug use problems) from over 21 countries (WHO, 2010). A percentile of 50 indicates that an individual is experiencing an average level of disability when compared to other members of the sample.

The average scores are comparable to the WHODAS 5-point scale, which allows the clinician to think of the individual’s disability in terms of none (0-0.49), mild (0.5-1.49), moderate (1.5-2.49), severe (2.5-3.49), or extreme (3.5-4). The average domain and general disability scores were found to be reliable, easy to use, and clinically useful to the clinicians in the DSM-5 Field Trials (APA, 2021). The average domain score is calculated by dividing the raw domain score by the number of items in the domain. The average general disability score is calculated by dividing the raw overall score by number of items in the measure (i.e., 36).

The two scoring methods are used for each of the 6 domains:

  1. Cognition – Assesses communication and thinking activities; specific areas assessed include concentrating, remembering, problem solving, learning and communicating.
  2. Mobility – Assesses activities such as standing, moving around inside the home, getting out of the home and walking a long distance.
  3. Self-care – Assesses hygiene, dressing, eating and staying alone.
  4. Getting along – Assesses interactions with other people and difficulties that might be encountered with this life domain due to a health condition; in this context, “other people” includes those known intimately or well (e.g. spouse or partner, family members or close friends) and those not known well (e.g. strangers).
  5. Life activities – Assesses difficulty with day-to-day activities (i.e. those that people do on most days, including those associated with domestic responsibilities, leisure, work and school).
  6. Participation – Assesses social dimensions, such as community activities; barriers and hindrances in the world around the respondent; and problems with other issues, such as maintaining personal dignity.  

Developer

Ustun, T.B, Kostanjsek, N., Chatterji, S., Rehm, J (Ed.). (2010). Measuring health and disability : manual for WHO Disability Assessment Schedule (‎WHODAS 2.0)‎. World Health Organization. https://www.who.int/publications/i/item/measuring-health-and-disability-manual-for-who-disability-assessment-schedule-(-whodas-2.0)  

References

American Psychiatric Association. Online Assessment Measures. (n.d.). Retrieved November 6, 2021, from https://www.psychiatry.org/File%20Library/Psychiatrists/Practice/DSM/APA_DSM5_WHODAS-2-Self-Administered.pdf  

Self-Compassion Scale – Short Form (SCS-SF)

Dr David Hegarty

The Self-Compassion Scale – Short Form (SCS-SF) is a 12-item self-report measure that is used by adults to measure their capacity for self-compassion – the ability to hold one’s feelings of suffering with a sense of warmth, connection and concern. 

Research has shown that self-compassion is associated with psychological well-being and is an important protective factor that fosters emotional resilience (Raes et al., 2011). For example, higher levels of self-compassion are typically related to greater psychological health as demonstrated by less depression and anxiety and greater happiness and optimism (Raes, 2011; Raes et al., 2011). Scores on the SCS-SF are related to measures of psychological distress, social support, perfectionism, suicide and self-harm (Hayes et al., 2016). It was also found that clients who had previously seriously considered suicide, made a suicide attempt, or engaged in other self-injurious behaviour evidenced more self-disparagement and less self-care, as measured by the SCS-SF, than clients without such histories (Hayes et al., 2016).

The SCS-SF has two subscales:

  1. Self-disparagement 
  2. Self-care 

Clinicians could administer the SCS-SF repeatedly over the course of treatment to determine if scores are changing. One would hope that the unconditional positive regard that clinicians demonstrate toward clients might be internalised by clients, thereby fostering more accepting and less critical attitudes toward the self.

Psychometric Properties

The SCS–SF demonstrated adequate internal consistency (Cronbach’s alpha ≥ 0.86) and a strong correlation with the long form SCS (r = 0.97; Raes et al., 2011). CFA by Raes et al. (2011) supported the same six-factor structure as found in the long form (Self-Kindness, Self-Judgement, Common Humanity, Isolation, Mindfulness, Over-Identification), as well as a single higher-order factor of self-compassion. However, the internal consistencies for the SCS–SF subscales were relatively low (ranging between 0.54 and 0.75) and it was therefore not recommended to use subscale interpretation for the SCS-SF. For total score information, however, the SCS–SF has good internal consistency and a near-perfect correlation with the long SCS. The test–retest reliability over a span of five months was found to be .71 (Raes et al., 2011).

Hayes et al. (2016) determined, using PCA and CFA with over 1,600 university students who sought psychotherapy, that the SCS-SF has two factors; Self-Care and Self-Disparagement

Percentiles are calculated based on comparison to a clinical sample with no previous suicidal ideation (n = 1054):

  • Total Score: mean = 2.94, SD = 0.72
  • Self-Disparagement: mean = 3.23, SD = 1.01
  • Self-Care: mean = 3.11, SD = 0.76

Scoring and Interpretation 

“Average Scores” are presented, which is the sum of all items divided by the number of items. The total score is an overall indication of self-compassion, with a higher score indicating more self-compassion.

Two subscales are presented:

  • Self-Disparagement (Items 1, 4, 8, 9, 11, 12): an indication of how the client views themselves with regard to impatience, disapproval, and judgment toward oneself.  A higher score indicates more self-disparagement and self-criticism.
  • Self-Care (Items 2, 3, 5, 6, 7, 10): an indication of compassion and how the client views themselves with regard to tenderness, patience, and empathy. A higher score indicates more self-care and self-compassion.

The total score is calculated by summing Self-Care and the inverse of the Self-Disparagement score. High levels of Total Self Compassion are characterised by high Self-Care and low Self-Disparagement.

Norms are presented in comparisons to a clinical sample who were seeking psychotherapy, but who had no previous suicidal ideation (Hayes et al., 2016). A “Clinical Percentile” of 50 indicates an average level of self-compassion, self-disparagement, or self-care compared to this sample of people seeking psychotherapy.

Developer

Raes, F., Pommier, E., Neff,K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the Self-Compassion Scale. Clinical Psychology & Psychotherapy. 18, 250-255.

References

Bratt, A., & Fagerström, C. (2020). Self-compassion in old age: confirmatory factor analysis of the 6-factor model and the internal consistency of the Self-compassion scale-short form. Aging & Mental Health, 24(4), 642–648. https://doi.org/10.1080/13607863.2019.1569588

Hayes, J. A., Lockard, A. J., Janis, R. A., & Locke, B. D. (2016). Construct validity of the Self-Compassion Scale-Short Form among psychotherapy clients. Counselling Psychology Quarterly, 29(4), 405–422. https://doi.org/10.1080/09515070.2016.1138397

Kotera, Y., & Sheffield, D. (2020). Revisiting the Self-compassion Scale-Short Form: Stronger Associations with Self-inadequacy and Resilience. SN Comprehensive Clinical Medicine, 2(6), 761–769. https://doi.org/10.1007/s42399-020-00309-w

Raes, F. (2011). The Effect of Self-Compassion on the Development of Depression Symptoms in a Non-clinical Sample. Clinical Psychology & Psychotherapy, 2, 33–36. https://doi.org/10.1007/s12671-011-0040-y

Sutton, E., Schonert-Reichl, K. A., Wu, A. D., & Lawlor, M. S. (2018). Evaluating the Reliability and Validity of the Self-Compassion Scale Short Form Adapted for Children Ages 8–12. Child Indicators Research, 11(4), 1217–1236. https://doi.org/10.1007/s12187-017-9470-y

Preschool Anxiety Scale (PAS)

Dr David Hegarty

The Preschool Anxiety Scale (PAS) is a 28 item scale that is completed by a parent / guardian and which assesses anxiety in children between the ages of 2 ½ and 6 ½ years old. The 28 anxiety items provide an overall measure of anxiety, in addition to scores on five subscales assessing a specific aspect of child anxiety:

  1. Generalised anxiety
  2. Social anxiety
  3. Obsessive compulsive disorder
  4. Physical injury fears
  5. Separation anxiety

The PAS is intended to provide an indicator of the number and severity of anxiety symptoms experienced by younger children (Spence et al., 2001). It is not designed to be a diagnostic instrument for use in isolation although it provides important information to inform the assessment process. Where a clinical diagnosis is required the PAS should be used as an adjunct to clinical interview. It may also be used for identification of young children who have elevated symptoms of anxiety and for whom further assessment is recommended to determine whether there is a need for intervention. Similarly, it provides an indicator of response to treatment. It can also be used to identify children for whom early intervention or prevention is warranted on the basis of elevated anxiety symptoms being a risk factor for the development of future emotional and mental health problems.

Psychometric Properties

The scale was initially developed through extensive review of the literature relating to preschool anxiety problems, use of diagnostic criteria, structured clinical interviews, existing measures of childhood anxiety, and input from the authors, all of whom have extensive experience in research and clinical practice relating to preschool anxiety problems (Spence et al., 2001). Several questions were drawn from the Spence Children’s Anxiety Scale (Spence, 1997, 1998), but reworded for preschool situations. Pilot versions of the questionnaire were then completed by groups of parents of preschoolers, who provided feedback about the relevance and understandability of the items and the questionnaire was then piloted with a sample of 600 parents of children aged between 3 and 5 years. 

Factor analysis from the pilot data resulted in a five factor model for anxiety, reflecting dimensions of social phobia, separation anxiety, obsessive compulsive disorder, fears of physical injury, and generalised anxiety (Spence et al., 2001). The five factors were strongly inter-correlated and this strong covariance was well explained by a single, higher-order factor of anxiety in general. Although the five first-order factors loaded strongly upon the higher-order anxiety factor, there was sufficient unique variance (between 40 and 60%) explained by three of the first order factors (social anxiety, obsessive compulsive disorder and fears of physical injury) to justify regarding them as dimensions worthy of independent consideration. The picture was less clear for separation anxiety and generalized anxiety, as these dimensions accounted for only a small percent of unique variance in mothers’ ratings of preschooler anxiety symptoms (12 and 19%, respectively). No significant differences were found between boys and girls in a large sample of 3- to 5-year olds for the total symptom ratings or any of the factor scores (Spence et al., 2001).

Construct validity was moderate with a significant correlation between PAS total score and the CBCL Internalizing total score (r = 0.68). Each PAS subscale also correlated significantly with the CBCL Internalizing total score (GAD, r = 0.60; Social Anxiety r = 0.57; Separation Anxiety r = 0.50; OCD r = 0.42; and Physical Injury Fears r = 0.43). The total scale and subscales showed strong internal consistency (alphas = .72–.92), 12-month stability (r = .60–.75) and maternal/paternal agreement (rs = .60–.75; Edwards et al., 2010). Scores on the scale also showed expected correlations with a measure of emotional distress, diagnosed anxiety disorders, and behavioral indicators of anxiety (Edwards et al., 2010).

Scoring and Interpretation 

Each item is rated on a 5-point scale from 0 ‘not at all’ to 4 ‘very often true’. Question 29 is an open-ended, non-scored item relating to the child’s experience of a traumatic event. This is followed by 5 items relating to whether the child exhibits behaviour indicative of post-traumatic stress reactions following the trauma. These items are not included in the scoring and are for clinical interest only.

The subscale scores are computed by adding the individual item scores on the set of items as follows:

  • Generalised Anxiety (sum of items 1, 4, 8, 14, 28)
  • Social Anxiety (sum of items 2, 5, 11, 15, 19, 23)
  • Obsessive Compulsive Disorder (sum of items 3, 9, 18, 21, 27)
  • Physical Injury Fears (sum of items 7, 10, 13, 17, 20, 24, 26)
  • Separation Anxiety (sum of items 6, 12, 16, 22, 25)
  • Total Score (sum of items 1-28)

Parents may report elevated scores on the PAS in two ways: in terms of elevated total scores and high scores on one or more subscale scores. Although the majority of children who show a high total score also show a high score on one or more subscales, this is not always the case. Thus, for clinical assessments, we recommend examining the total and subscale scores. For screening purposes in community samples, it may be sufficient to use the total score for identification of children at risk.

Normative percentiles were obtained from a community sample (Spence et al., 2001), indicating how the respondent scored in relation to a typical pattern of responding for children. For example, a percentile of 50 indicates the child has average levels of anxiety when compared to non-clinical preschool aged children

Developer

Spence, S. H., Rapee, R., McDonald, C., & Ingram, M. (2001). The structure of anxiety symptoms among preschoolers. Behaviour Research and Therapy, 39(11), 1293–1316. https://doi.org/10.1016/s0005-7967(00)00098-x

References

Edwards, S. L., Rapee, R. M., Kennedy, S. J., & Spence, S. H. (2010). The assessment of anxiety symptoms in preschool-aged children: the revised Preschool Anxiety Scale. Journal of Clinical Child and Adolescent Psychology: The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53, 39(3), 400–409. https://doi.org/10.1080/15374411003691701

Spence, S. H. (1997). The structure of anxiety symptoms among children: A confirmatory factor analytic study. Journal of Abnormal Psychology, 106, 280297. https://doi.org/10.1037//0021-843x.106.2.280 

Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36, 545566. https://doi.org/10.1016/S0005-7967(98)00034-5

Depression Anxiety Stress Scale (DASS-10)

Dr David Hegarty

The Depression Anxiety Stress Scale (DASS-10) is a brief 10-item version of the full version of the Depression Anxiety Stress Scale (DASS-42). The DASS-10 can determine the overall level of distress as well as provides subscale scores for two symptom clusters: Depression and Anxiety/Stress

The scale was designed to be used for routine outcome monitoring in psychology practices and other mental health settings. It provides an overall level of distress that is sensitive to clinical change and can be used to track the effectiveness of treatment. It can be used with people 16 years and older. 

Psychometric Properties

Halford and Frost (2021) developed the DASS-10 as a shorter version of the original DASS-42 and DASS-21 (Lovibond & Lovibond, 1995). EFA and CFA yielded two highly correlated factors: Anxiety-Stress and Depression subscales. Both subscales and the higher-order Distress factor had high internal consistency (Cronbach’s alpha = 0.83, 0.85, & 0.89 respectively; Halford & Frost, 2021).

Based on the above psychometric properties, reliable change was determined to be a five or more point change between first and last DASS-10 administration. 

As expected, the validation study found the DASS-10 was able to discriminate between populations, with a clinical sample scoring significantly higher (mean =  7.67, SD = 4.36) than a community sample (mean = 3.01, SD 3.15). The community sample of newly wedded couples (n = 376) can be used to compute normative percentiles. 

Scoring and Interpretation 

The total score represents overall distress (0 to 30), with higher scores indicating more severe distress or a greater number of symptoms.  Two subscales are presented:

  • Anxiety-Stress: Items 1, 4, 6, 7, 8, 9 (raw score range = 0 to 18)
  • Depression: Items  2, 3, 5, 10 (raw score range = 0 to 12)

Overall scores can be classified into three severity groups: 

  • Mild/subclinical (raw score = 6 or less, average score 0.6 or less; which is equivalent to a percentile of 83 or less)
  • Moderate (raw score between 7 and 12, average between 0.7 and 1.2; which is equivalent to a percentile of between 84 and 99.8)
  • Severe (raw score 13 or more, average between 1.3 and 3; which is equivalent to a percentile of between of 99.9 or greater)

A normative percentile is computed based on a community sample (Halford & Frost, 2021), indicating how the respondent scored in relation to a typical pattern of responding for adults. For example, a percentile of 83 or less indicates the individual has less distress than 83 percent of the normal population, and puts them in the mild/subclinical category. In mental health settings it is typical to see people with percentiles in the 90s.

In addition to the raw score being computed, average scores are calculated by dividing the raw score by the number of items, giving a sense of the general pattern of responding at the subscale level. Average scores are helpful for interpretation as they allow comparisons between total score and subscales.  When administered more than once, average scores are graphed, showing the change in symptoms over time.

Based on reliable change calculations, interpretive text is provided describing the respondent’s change in symptoms from first to last administrations, as either having experinced:

  • deterioration (increase in scores by 5 or more)
  • no reliable change (scores changed by 4 or less)
  • reliable improvement (scores reduced by 5 or more)
  • recovery (scores reduced by 5 or more and most recent score is 6 or less, putting the in the Mild/Subclinical range)

Developer

Halford, W. K., & Frost, A. D. J. (2021). Depression Anxiety Stress Scale-10: A Brief Measure for Routine Psychotherapy Outcome and Progress Assessment. Behaviour Change: Journal of the Australian Behaviour Modification Association, 1–14. https://doi.org/10.1017/bec.2021.12

References

Lovibond S.H. & Lovibond P.F.(1995). Manual for the Depression, Anxiety, Stress Scale. Sydney: Psychology Foundation, University of New South Wales.

Supervisory Styles Inventory (SSI)

Dr David Hegarty

The Supervisory Styles Inventory (SSI) is a 25 item scale which measures the interpersonal or relational aspects of supervisors as perceived by supervisees. The SSI is completed by a supervisee to rate their perceptions of their supervisor’s style based on three subscales: Attractive, Interpersonally Sensitive, and Task-Oriented. This scale can be useful to start a discussion around the preferences a supervisee has for their supervision. 

In addition to being used to rate the supervisor’s style, the scale can be useful during the initial stages of a supervisory relationship to ask the supervisee about their preferences of how they would like supervision to be (as opposed to how supervision actually is). The process of asking for the supervisee’s preferred style before supervision starts can be helpful so the supervisor can tailor their style in accordance to the supervisee’s preferences. In addition, if the scale is administered again during the course of supervision the supervisor can assess the consistency of the supervisee’s preferences versus their experience of supervision. 

In addition, the supervisor may choose to use this scale to self-assess by self rating their supervisory style and compare the results to the perception of the supervisee. 

The SSI has been used in assessing the supervisory relationship with regards to supervisee satisfaction (Fernando & Hulse-Killacky, 2005; Nelson & Friedlander, 2001), the impact of gender and supervisory style on supervisee satisfaction (Rarick & Ladany, 2013), and supervisory style related to perceptions of satisfaction with individual, triadic, and group supervision (Newgent & Davis, 2003).

The style of the supervisor is related to a supervisee’s perception of satisfaction with their supervision as all subscales of the SSI are highly correlated with supervisory satisfaction (Bussey, 2015).  The strongest correlation was that of attractiveness and satisfaction (r=.79) suggesting that a friendly, warm, and supportive supervisor is highly desirable for supervisees in their early stages of development (Bussey, 2015).

Psychometric Properties

Derived from research identifying relationship and relational aspects as an important part of successful supervision, Friedlander and Ward (1984) identified dimensions of supervisory style that were consistent among supervisors and supervisees. Through content analyses of transcribed interviews, a number of items were developed and then assigned a category based on applicability to supervisor or supervisee. The most stable items were kept for use in the instrument, and they found the three underlying constructs (attractive, interpersonally sensitive, task-oriented). 

Herbert and Ward (1995) found the SSI to have internal consistency reliabilities of .93 (Attractiveness), .91 (Interpersonally Sensitive), and .92 (Task-oriented). Test-retest reliabilities are .92 (Friedlander & Ward, 1984) suggesting that the instrument is consistent over time and with various populations.

Research by Bussey (2015) obtained norms from 90 supervisees who were recently graduated or enrolled in a mental health / school counselling program, and their mean subscale scores (and standard deviations) were:

  • Attractive: 6.24 (1.02)
  • Interpersonally Sensitive: 6.05 (1.08)
  • Task-Oriented: 5.57 (1.16)

Note the original version of the SSI had eight items that did not correspond to the above factors, so they have been excluded from the scale on NovoPsych. In addition, the instructions have been modified to ask that at least five questions be rated as average or below, which helps reduce ceiling effects. 

Scoring and Interpretation 

The SSI has three subscales:

  • Attractive (items 11, 12, 18, 19, 23, 24, 25): refers to a supervisor who is warm, friendly, supportive, and trust-worthy.
  • Interpersonally Sensitive (items 2, 5, 7, 8, 17, 20, 21, 22): refers to attributes such as committed to the relationship, resourceful, and perceptive.
  • Task-Oriented (items 1, 3, 4, 6, 9, 10, 13, 14, 15, 16): refers to the attributes such as practical, concrete, evaluative, and focused. 

Higher scores in each subscale indicate supervisee’s / supervisor’s perception of that particular supervisory style. The SSI is scored on a seven point Likert scale. The attractiveness scale has seven questions which are summed and then divided by seven. Interpersonally sensitive scale has eight questions which are summed and divided by eight, and the task oriented scale has 10 questions which are summed and divided by 10. 

The instructions of the scale asked that at least five questions were marked as average or below, which helps the scale discriminate which of the three supervision styles are most and least endorsed. Noting the pattern of the highest and lowest subscale scores can help a supervisor understand the supervisee perceptions, and adjust supervision if appropriate. 

If the scores on all subscales are consistently high (above 6) it may indicate one of the following:

  1. The supervisee is extremely happy with the supervision
  2. The supervisee did not critically examine the nature of the supervisory relationship
  3. The supervisee does not feel comfortable providing critical feedback to the supervisor

Developer

Friedlander, M., & Ward, L. (1984). Development and validation of the Supervisory Styles Inventory. Journal of Counseling Psychology, 31, 541–557. https://doi.org/10.1037/0022-0167.31.4.541

References

Bussey, L. E. (2015). The Supervisory Relationship: How Style and Working Alliance Relate to Satisfaction among Cyber and Face-to-Face Supervisees.  PhD thesis, University of Tennessee, 2015. https://trace.tennessee.edu/utk_graddiss/3564 

Fernando, D. M., & Hulse‐Killacky, D. (2005). The relationship of supervisory styles to satisfaction with supervision and the perceived self‐efficacy of master’s‐level counseling students. Counselor Education and Supervision, 44, 293-304. http://dx.doi.org/10.1002/j.1556-6978.2005.tb01757.x

 

Herbert, J. T., & Ward, T. J. (1995). Confirmatory factor analysis of the supervisory style inventory and the revised supervision questionnaire. Rehabilitation Counseling Bulletin, 38, 334-339.

 

Nelson, M., & Friedlander, M. L. (2001). A close look at conflictual supervisory relationships: The trainees’s perspective.Journal of Counseling Psychology,48, 384-395. http://dx.doi.org/10.1037/0022-0167.48.4.384 

 

Newgent, R. A., Davis, H., & Farley, R. C. (2004). Perceptions of individual, triadic, and group models of supervision. The Clinical Supervisor, 23, 65-79. doi: 10.1300/J001v23n02_05

 

Rarick, S. L., & Ladany, N. (2012). The relationship of supervisor and trainee gender match and gender attitude match to supervisory style and the supervisory working alliance. Counselling and Psychotherapy Research, 13,138-144. doi: 10.1080/14733145.2012.732592