Child Anxiety Life Interference Scale (CALIS)

Commonly, clinical measures of children’s anxiety focus on the assessment of disorder symptoms to support formal diagnoses. This has led to assessments of anxiety symptom impact or “anxiety life interference” becoming less common, despite reductions in these impairments contributing to clients’ treatment satisfaction (Lyneham, et. al., 2013). Consequently, the Child Anxiety Life Interference Scale (CALIS; Lyneham, et. al., 2013) was developed to provide a psychometrically supported method of evaluating the impact that children’s anxiety has on their life, as well as on the life of their parents.

Developed at the Centre for Emotional Health at Macquarie University in Sydney, Australia, the CALIS consists of one 10-item scale administered to children, and two 9-item scales administered to parents. The scale administered to children evaluates self-reported anxiety life interference; the scales administered to parents evaluate child anxiety life interference relative to the child’s life, and child anxiety life interference relative to the parents’ life. All items, which relate to common activities (e.g. “being with friends outside of school” or “your career choice”), are rated on a five-point Likert scale (0 = not at all, 4 = a great deal), with higher scores indicating higher anxiety life interference.

Psychometric Properties

Currently, psychometric data for the CALIS is based exclusively on one evaluative study (Lyneham, et. al., 2013); this study administered the scale to 622 Australian or American children with anxiety disorders, aged between 6 and 17 years.

According to this study, the CALIS demonstrates moderate internal consistency, with Cronbach’s Alphas ranging from .84 for children to .90 for mothers. The CALIS also demonstrates moderate inter-rater reliability between parents and children, which is consistent with previous studies that have identified differences in children and parents’ perceptions of anxiety (Niditch & Varela, 2011). Lastly, the CALIS demonstrates strong test-retest reliability; pre- and post-waitlist administrations of the CALIS produced significant correlations.

Clinical Utility

The use of the CALIS in clinical settings is supported by psychometric data that indicates that it is a significant, valid and reliable measure of anxiety life interference. The CALIS contributes to the development of a comprehensive understanding of a child’s experience of anxiety by using multiple raters to evaluate its impact across multiple activities. Additionally, the CALIS can be used to inform treatment decisions by indicating the domains in which a child is most significantly impaired, as well as provide an indication of overall treatment efficacy. However, due to limited evaluations of the scale’s psychometric properties, the CALIS should be used and interpreted with caution; limited data relating to the impact that cultural differences may have on psychometric properties. Furthermore, Lyneham et. al. (2013) advise that the CALIS be used in conjunction with symptom-specific scales, as it cannot independently support a diagnosis of anxiety.

CALIS freely available from: http://www.mq.edu.au/

References

Lyneham, H., Sburlati, E., Abbott, M., Rapee, R., Hudson, J., Tolin, D., & Carlson, S. (2013). Psychometric properties of the Child Anxiety Life Interference Scale (CALIS). Journal of Anxiety Disorders, 27(7), 711-9.  doi: 10.1016/j.janxdis.2013.09.008

Niditch, L., & Varela, R. (2011). Mother-child disagreement in reports of child anxiety: Effects of child age and maternal anxiety. Journal of Anxiety Disorders, 25(3), 450-5. doi: 10.1016/j.janxdis.2010.11.009

Yale – Brown Obsessive Compulsive Scale (Y-BOCS)

The Yale-Brown Obsessive Compulsive scale was developed by Wayne Goodman and his colleagues to rate the severity and types of symptoms that a client my have. It is important to note that the Y-BOCS is not intended to diagnose OCD but is used to rate the severity of symptoms and can be administered throughout therapy to track improvements made by the client. The Y-BOCS is administered as a semi-structured interview where the client responds to questions that are asked by the interviewer. The severity of the obsessive symptoms and compulsive symptoms are rated separately to give the practitioner an idea of what symptoms are most prominent. The semi-structured interview also allows the practitioner to ask the client any additional questions that they may feel will be helpful in treating the client.  The Y-BOCS is considered to be a valid and reliable measure with strong internal consistency for the symptom checklist and severity scale. Scoring the test is straight forward and categorises the clients score to having a mild case of OCD to an extreme case of OCD.

References

https://psychcentral.com/disorders/ocd/what-causes-obsessive-compulsive-disorder-ocd/ )

https://iocdf.org/about-ocd/treatment/

https://www.ncbi.nlm.nih.gov/pubmed/20528050

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3958520/

http://www.brainphysics.com/ybocs.php

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994744/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994744/table/t1-jcnsd-8-2016-013/

http://www.novopsych.com/y-bocs.html

https://www.ncbi.nlm.nih.gov/pubmed/20528050

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3958520/

Iowa Personality Disorder Screen (IPDS)

Structured interview-based methods for diagnosing Personality Disorders (PD) are considered among the best practices for diagnosing PD (Zanarini et al., 2000), but they are time consuming and involve specific training of the clinician. Therefore, several authors have advised that clinicians should first screen patients for PD to identify patients who need a more thorough evaluation (Rizeanu, 2016).

The Iowa Personality Disorder Screen (IPDS) was developed by Langbehn et al (1999) to serve as a brief interview-based measure, taking around 5 min to complete. It is an 11-item screening instrument used to evaluate whether a PD is present or absent in the psychiatric outpatient clinic setting (Langbehn et al., 1999). Most of the 11 items have follow up questions making up a total 19 possible questions. It can easily be integrated into standard diagnostic clinical interviews and initial validation research suggests that it is adequate in identifying patients requiring further evaluation to determine if they meet criteria for a personality disorder. Furthermore, a study by Trull and Armdur (2001) examined the effectiveness of the IPDS in a non-clinical sample of 103 undergraduate students and determined that it may be useful as a screening measure for PD in both clinical and nonclinical populations.

Retrospective analyses using 1,203 Structured Interview for Disorders of Personality-Revised (SIDP-R; Pfohl, Blum, Zimmerman,1995) interviews suggested that the IPDS items should provide good sensitivity and specificity (Langbehn et al., 1999). Furthermore, results from a prospective validation study, using a mixed group of 52 nonpsychotic inpatients and outpatients who were diagnosed showed that blind administration of the IPDS yielded excellent sensitivity (92%) and good specificity (79%). The IPDS shows promise as a quick PD screen for use in research settings or standard clinical interviews. Moreover, socio-demographic and psychopathological factors have been suggested to have little effect on the IPDS as screening instrument (Olssøn, Sørebø, & Dahl, 2011).

In a study by Morse and Pilkonis (2007) psychiatric and non-psychiatric samples were employed to compare the validity of three screening measures: the PD scales from the Inventory of Interpersonal Problems, a self-report version of the Iowa Personality Disorder Screen, and the self-directedness scale of the Temperament and Character Inventory. The screeners were highly correlated in a range from .71 to .77, despite their different theoretical origins. These findings suggest that the use of multiple screeners was not a significant improvement over any individual screener, and no single screener stood out as clearly superior to the others.

When using self-rating scales, clinicians should be mindful as individuals with PD see themselves in distorted ways and may not be able to give accurate accounts of their presenting difficulties (Klonsky, Oltmanns, & Turkheimer, 2002). Reports of symptoms have been shown to differ from those of their friends and families (Klonsky, Oltmanns, & Turkheimer, 2002), therefore interviews with people who know the patient well can improve the accuracy of a diagnosis.

This tool is not meant to be used as a diagnostic tool. Only a trained professional can properly diagnose a personality disorder. The formal diagnosis for a PD is ultimately a clinical decision that should be made by incorporating multiple sources and the screening measures are intended to aid clinicians in making decisions regarding identification of patients who are in need of a more thorough evaluation, but a formal diagnosis should not be given based exclusively on these data alone.
References

Langbehn DR et al. (1999). The Iowa Personality Disorder Screen: development and preliminary validation of a brief screening interview. J Pers Disord. Spring;13(1)75-89.

Morse, J. Q., & Pilkonis, P. A. (2007). Screening for Personality Disorders. Journal of Personality Disorders21(2), 179–198. http://doi.org/10.1521/pedi.2007.21.2.179

Olssen, I., Sørebø, Ø., & Dahl, A. A. (2011). A cross-sectional testing of The Iowa Personality Disorder Screen in a psychiatric outpatient setting. BMC Psychiatry11, 105. http://doi.org/10.1186/1471-244X-11-105

Pfohl, B., Blum, N., Zimmerman, M. (1995). Structured interview for DSM-IV personality SIDP-IV. Iowa City, IA. The University of Iowa.

Rizeanu, S. (2016). Screening measures for personality disorders. Romanian Journal of Experimental Applied Psychology, 7(2).

Siefert, C. J. (2010). Screening for Personality Disorders in Psychiatric Settings: Four Recently Developed Screening Measures, in Baer, L., Blais, M.A. (2010). Handbook of Clinical Rating Scales and Assessment in Psychiatry and Mental Health. N.Y: Human Press.

Trull, T.J. & Amdur, M. (2001). Diagnostic Efficiency of the Iowa Personality Disorder Screen Items in a Nonclinical Sample. Journal of Personality Disorders: Vol. 15, No. 4, pp. 351-357. https://doi.org/10.1521/pedi.15.4.351.19184

Trauma History Screen (THS)

The Trauma History Screen (THS) was developed by Carlson et al. (2011) to address the need for a brief, simple and easy-to-read tool to assess exposure to distressful events. THS contains 14 dichotomous items (‘Yes’ or ‘No’).  Comprising of two constructs, the THS is designed to assess high magnitude stressor events (HMS) and events relating to significant and persisting posttraumatic distress (PDD). HMS items refers to global, sudden events known to illicit distress response to majority of individuals (for example, hurricane, earthquake), whilst PPD events refers to events associated with significant subjective distress persisting for longer than 1 month (e.g. abandonment by spouse). THS also assesses the individuals’ duration of distress and the distress level.

            THS is intended as a preliminary assessment of exposure to HMSs and PPDs, and the subjective experiences of individuals. As such, THS does not include a formal cut-off scoring procedure. Instead, THS is a quick and useful tool assess trauma exposure and levels and duration of distress which could inform clinicians of therapeutic conceptualisation. Clinicians can therefore utilise further measures to confirm diagnoses if needed.

            Tested across four samples (home veterans, clinical sample, community sample and university students), the THS test-retest correlations over 2 periods (between 1 week and 2 months) were found to be moderate and very high (ranging from .61 to .95). THS was found to be highly correlated to the more lengthy published measure of traumatic life events questionnaire (TLEQ) across a variety of samples such as veterans (r = .77) and young adults (r = .73). The THS is an easy-to-read tool, requiring a fifth grade reading level. It requires a short amount of time to administer and is available at no cost. While it has not been validated cross-culturally, the structure of THS can be replicated to reflect culturally appropriate items. (Jaber, 2012). One notable limitation of the THS is the reliance on self-report, which may not be entirely accurate and may be estimation influenced by current symptoms.

In sum, THS is a reliable and valid tool to assess exposure to traumatic events that is brief, cost effective, therefore easy to administer. It can be a valuable measure when conceptualising cases as well as a screening tool towards diagnosis.

References

Carlson, E.B., Smith, S. R., Palmieri, P. A., Dalenberg, C., Ruzek, J. I., Kimerling, R., Burling, T. A., Spain, D. A. (2011). Development and validation of a brief self-report measure of trauma exposure: the Trauma History Screen. Psychological Assessment, 23, 463–477.

Jaber, S. (2012). Developing a self-help guide for traumatised university students in Iraq. UK: University of Nottingham, PhD thesis.

The Trauma History Screen (2005). Available from http://www.ptsd.va.gov

 

 

Levenson Self-report Psychopathy Scale (LSRP)

The Levenson Self-report Psychopathy Scale (LSRP) was created in 1995 by Michael R Levenson. It is a measure of psychopathic/sociopathic (interchangeable) traits. Psychopathy/sociopathy are colloquial terms for Anti-social Personality Disorder.

Originally two Subscales, 26 items

-Primary psychopathy (psychopathic emotional affect) – 16 items
-Secondary psychopathy (psychopathic lifestyle) – 10 items

More current research proposes a three-way model (three sub-scales) which can be broken up into egocentricity, callousness and anti-social.

Example items

  • Success is based on survival of the fittest; I am not concerned with the losers
  • I find that I am able to pursue one goal for a long time
  • Looking out for myself is my top priority
  • I often admire a really clever scam

Validity checks

  • Internal validity – Cronbach’s alpha: .84 (Sellbom, 2009)
  • Has been validated with prison and non-prison samples (Sellbom, 2011)
  • Good test-retest reliability
  • Good convergent reliability with other psychopathy measures (Sellbom, 2011)

Cross-cultural evidence

The LSRP was originally developed for Western individuals, specifically a North American audience. The LSRP has since been translated into Chinese, and used for Chinese populations. Internal convergent and discriminate validity remained high (Shou, Sellbom & Han, 2016)

Advantages

  • Free to the public
  • Quick to administer
  • Valid across culture

Disadvantages

  • Not well validated in a clinical setting

References:

Levenson, M., Kiehl, K., Fitzpatrick, C. (1995). Assessing psychopathic attributes in a noninstitutionalized population.  Journal of Personality and Social Psychology, 68, 151-158.

Shou, Y., Sellbom, M., & Han, J. (2016). Evaluating the Construct Validity of the Levenson Self-Report Psychopathy Scale in China. Assessment. doi: 10.1177/1073191116637421

Sellbom, M. (2011). Elaborating on the construct validity of the Levenson Self-report Psychopathy Scale in incarcerated and non-incarcerated Samples. Law and Human Behaviour, 6, 440 – 451.

Patient Health Questionnaire Somatic Symptom Severity Scale (PHQ-15)

In the mid-1990s the Patient Health Questionnaire (PHQ), was developed and validated as a shorter self-administered version of the Primary Care Evaluation of Mental Disorders (PRIME-MD). The PHQ was developed by Robert Spitzer, Janet Williams and Kurt Kroenke and colleagues at Columbia University. A large study found the PHQ had diagnostic validity comparable to the original clinician-administered PRIME-MD and was more efficient in clinical practice (Spitzer et al., 1999). The Patient Health Questionnaire Somatic Symptom Severity Scale (PHQ-15) is a brief, self-administered questionnaire that was derived from the full PHQ and is increasingly used to assess somatic symptom severity and screen for the potential presence of somatisation and somatoform disorders (based on DSM-IV criteria) in adults (Kroenke et al., 2002). The scale consists of 15 items that ask whether somatic symptoms, such as stomach pain or dizziness are present within the last 4 weeks and the severity (response categories of “not bothered at all”, “bothered a little” and “bothered a lot”). The PHQ-15 scores of 5, 10, and 15 represent cut off points for low, medium, and high somatic symptom severity, respectively (Spritzer et al., 1994).

Psychometric Properties

The PHQ-15 has been validated in different clinical and occupational populations. (De Vroege et al., 2012; Kroenke et al., 2010). With a cut off score of 6 or more the sensitivity of the PHQ-15 was 78% (true positive) and specificity was 71% (false negative). The negative predictive value of 97% indicates that only 3% of individuals who have a score of less than 6 will have a somatoform disorder (Van Ravesteijn et al., 2009). Convergent validity with the Beck Depression Inventory (BDI) and the General Health Questionnaire-12 (GHQ-12) were positive. Increasing scores on the PHQ-15 are strongly associated with increased functional impairment, disability, health care use and symptom-related difficulty (Changsu et al., 2009; Kroenke et al., 2002).  The PHQ-15 demonstrates acceptable internal consistency (Cronbach coefficient alpha of .80) (Kroenke et al., 2002; Van Ravesteijn et al., 2009; Kroenke et al., 1998). The PHQ-15 has moderate test-retest reliability (intraclass correlation coefficient of 0.83) with a 2 week interval (Van Ravesteijn et al., 2009).

The reliability and validity of the PHQ-15 is unaffected by pertinent individual difference factors such as age, gender and education (Kroenke et al., 2010; Kocalevent et al., 2013; Changsu et al., 2009; Shih-Cheng et al., 2016). The PHQ-15 has been translated into over 20 languages (Spritzer et al., 1994). The scale has been validated in Korean and Chinese populations, however does not perform well in Hispanic populations which could be due to multiple factors within the cultural context that may affect how individuals identify and classify bodily sensations, perceive illness and seek medical attention (APA, 2013; Interian et al., 2006; Changsu et al., 2009; Shih-Cheng et al., 2016). East Asian populations often complain of somatic symptoms rather than reveal any depressive feelings, which is important for clinical practice as somatoform disorders have considerable comorbidity with anxiety and depressive disorders which the PHQ-15 does not screen for (Changsu et al., 2009).

Clinical utility

Overall, the PHQ-15 is a valid and reliable screening tool for presence of somatic symptoms and severity. The DSM-IV main criteria for somatoform disorder was medically unexplained symptoms, whereas, the DSM-5 emphasises distress (APA, 2013). Therefore, the PHQ-15 can be aligned with the DSM-5 criteria as the scale is a screening tool of severity and distress (Shih-Chen et al., 2016). More research is needed to support the PHQ-15 as a measure of responsiveness to changes throughout treatment of individuals with somatoform disorders (Kroenke et al., 2010). It is important to note the PHQ-15 is a self-report scale therefore susceptible to reporting biases. Elevated neuroticism or negative affectivity may lead to inflated symptom reporting (Watson et al., 1989). The main strengths of the scale are it is easy to use (for clinician and client), free and has been validated in different clinical and occupational populations. It has shown good sensitivity and specificity for screening for somatoform disorders, however it is not a diagnostic tool rather an indication of an individual at risk (Kroenke et al., 2010). Further, the scale addresses current rather than previous symptoms to gain more valid and reliable data (Kroenke et al., 2010).

Link to free version of PHQ-15

http://www.phqscreeners.com/sites/g/files/g10016261/f/201412/English_0.pdf
 

References

American Psychiatric Association (APA). (2013). Diagnostic and statistical manual of mental disorders: DSM-5. Washington, D.C: American Psychiatric Association.

Spitzer, R., Williams, J., & Kroenke, K. (1994). Instructions for Patient Health Questionnaire (PHQ) and GAD-7 Measures (pp. 1-9). Retrieved from https://phqscreeners.pfizer.edrupalgardens.com/sites/g/files/g10016261/f/201412/instructions.pdf

Spitzer, R., Kroenke, K., & Williams, J. (1999). Validation and Utility of a Self-report Version of PRIME-MD. The Patient Health Questionnaire Primary Care Study Group. JAMA, 282(18), 1737–1744. doi:10.1001/jama.282.18.1737

Kroenke, K., Spitzer, R., & Williams, J. (2002). The PHQ-15: Validity of a New Measure for Evaluating the Severity of Somatic Symptoms. Psychosomatic Medicine64(2), 258-266. http://dx.doi.org/10.1097/00006842-200203000-00008

Kroenke, K., Spitzer, R., Williams, J., & Löwe, B. (2010). The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review. General Hospital Psychiatry, 32(4), 345-359. http://dx.doi.org/10.1016/j.genhosppsych.2010.03.006

Han, C., Pae, C., Patkar, A., Masand, P., Woong Kim, K., Joe, S., & Jung, I. (2009). Psychometric Properties of the Patient Health Questionnaire–15 (PHQ–15) for Measuring the Somatic Symptoms of Psychiatric Outpatients. Psychosomatics, 50(6), 580-585. http://dx.doi.org/10.1016/s0033-3182(09)70859-x

Liao, S., Huang, W., Ma, H., Lee, M., Chen, T., Chen, I., & Gau, S. (2016). The relation between the patient health questionnaire-15 and DSM somatic diagnoses. BMC Psychiatry, 16(1). http://dx.doi.org/10.1186/s12888-016-1068-2

Van Ravesteijn, H., Wittkampf, K., Lucassen, P., van de Lisdonk, E., van den Hoogen, H., & van Weert, H. et al. (2009). Detecting Somatoform Disorders in Primary Care With the PHQ-15. The Annals Of Family Medicine, 7(3), 232-238. http://dx.doi.org/10.1370/afm.985

Interian, A., Allen, L., Gara, M., Escobar, J., & Díaz-Martínez, A. (2006). Somatic Complaints in Primary Care: Further Examining the Validity of the Patient Health Questionnaire (PHQ-15). Psychosomatics, 47(5), 392-398. http://dx.doi.org/10.1176/appi.psy.47.5.392

Kocalevent, R., Hinz, A., & Brähler, E. (2013). Standardization of a screening instrument (PHQ-15) for somatization syndromes in the general population. BMC Psychiatry, 13(1). http://dx.doi.org/10.1186/1471-244x-13-91

De Vroege, L., Hoedeman, R., Nuyen, J., Sijtsma, K., & van der Feltz-Cornelis, C. (2012). Erratum to: Validation of the PHQ-15 for Somatoform Disorder in the Occupational Health Care Setting. Journal Of Occupational Rehabilitation, 22(4), 590-590. http://dx.doi.org/10.1007/s10926-012-9383-z

Watson, D., & Pennebaker, J. W. (1989). Health complaints, stress, and distress: Exploring the central role of negative affectivity. Psychological Review, 96, 234–254

 

Florida Obsessive-Compulsive Inventory (FOCI)

The Florida Obsessive-Compulsive Inventory (FOCI) is a free to use measure of the number of symptoms of obsessive-compulsive disorder (OCD) present, as well as the severity of the symptoms1. It was initially developed in 2007 by researchers at the University of Florida1, 2. It was based on the Yale-Brown Obsessive-Compulsive Scale-Self Report (Y-BOCS-SR), which was considered the gold standard at the time and the only other self-report measure for OCD. However, the FOCI is a much quicker measure to use and to score, taking less than 5 minutes2.

One of the primary reasons the FOCI was developed is that there were some concerns surrounding the Y-BOCS-SR’s validity due to its use of separate obsession and compulsion scales when factor analysis is conducted1. Secondly, many of the other OCD measures that had been used by clinicians in the past were not able to measure the number and severity of symptoms in a brief manner. Thus, the FOCI was developed with the Y-BOCS in mind, was reviewed by OCD experts for reliability and relevance, and was revised in consultation with a few OCD in-patients1, 2.

Psychometric Properties

Once the final FOCI was developed, its psychometric properties were measured using 113 previously diagnosed (using DSM-III-R or DSM-IV) OCD patients, who were diagnosed at least one year prior. It has been since found to have good internal consistency (α = 0.89), adequate reliability (K-R 20 = 0.83) for the SC, and is highly correlated with the Y-BOCS-SR total score (previously considered the gold standard)1, 2.

In addition, internal consistency has been shown with the moderate correlations between the two parts of the measure (SC and SS, rs < 0.45). It has also shown to correlate with other measures such as the DASS and Hamilton Depression Rating Scale (depression/anxiety) and Clinical Global Impression Scale (psychopathology severity)1, 2.

Scoring

The FOCI contains two parts: 1) the symptom checklist (SC) and 2) the severity scale (SS). The SC measures the number of symptoms present from a 20-item list of common symptoms that the individual will circle either “yes” for present or “no” for not present (range 0 – 20; 10 each of obsessions and compulsions). If there is more than one “yes”, the client completes the SS on the second page. They will rate the severity of their symptoms identified on the SC. The clinician adds the total and a score of 8+ indicates possible OCD traits. The clinician can also average the scores over the SS to find an overall severity The SS measures the severity of the symptoms that have been identified, as a whole, and not individual symptoms1, 2.

Cultural issues

There does not appear to be any issues between gender, culture or age at this stage of research, and the measure has been adapted into a child version (C-FOCI), which has been translated into Spanish. The adult version has been translated into Thai and Chinese, and all versions developed to date have similar psychometric properties to the adult English version3 – 6.

Critical analysis

While it cannot measure the severity of individual symptoms, it does measure the severity of the impact of the symptoms on the client. It cannot, for example, determine the severity of contamination concerns versus the severity of avoiding certain numbers; but it can determine the severity of time consumed on the behaviours.

One other issue with the FOCI is that there is no option to add extra symptoms to the list, and the list is not exhaustive. However, the list does include the most common obsessions and compulsions that occur in OCD clients. Because the FOCI is a self-report, it is possible that the client may indicate this in another way (such as writing their own) or, because it should be followed by a clinical interview, this can be brought to the clinicians attention on deeper analysis.

The FOCI has established, good sensitivity to change, and is therefore a great tool to use when determining the success or failure of treatment interventions over time, and there are no known issues with using the measure multiple times with the same client. Because it is quick to complete and easy to score, it is preferable to use the FOCI instead of longer assessments, such as the Y-BOCS. However, it should be noted that the English version has not been tested across clinical and non-clinical populations or clinical-OCD versus other clinical populations.

Finally, it is worth noting that there is a high correlation with the FOCI and measures of depression and anxiety.  However, this is thought to be due to the high co-morbidity of these disorders.

References

  1. Storch, E. A., Kaufman, D. A. S., Bagner, D., Merlo, L. J., Shapira, N. A., Geffken, G. R., Murphy, T. K., & Goodman, W. K. (2007). Florida Obsessive-Compulsive Inventory: Development, reliability and validity. Journal of Clinical Psychology, 63(9), 851 – 859. DOI: 10.1002/jclp.20382
  2. Aleda, M. A., Geffken, G. R., Jacob, M. L., Goodman, W. K., & Storch, E. A. (2009). Further psychometric analysis of the Florida Obsessive-Compulsive Inventory. Journal of Anxiety Disorders, 23, 124 – 129. DOI:10.1016/j.janxdis.2008.05.001
  3. Saipanish, R., Hiranyatheb, T., Jullagate, S., & Lotrakul, M. (2015). A study of diagnostic accuracy of the Florida Obsessive-Compulsive Inventory – Thai version (FOCI-T). BMC Psychiatry, 15, 251 – 257. DOI: 10.1186/s12888-015-0643-2
  4. Storch, E. A., Khanna, M., Merlo, L. J., Loew, A., Franklin, M., Reid, J. M., Goodman, W. K., & Murphy, T. K. (2009). Children’s Florida Obsessive Compulsive Inventory: Psychometric properties and feasibility of a self-report measure of obsessive-compulsive symptoms in youth. Child Psychiatry & Human Development, 40, 467 – 483. DOI: 10.1007/s10578-009-0138-9
  5. Piqueras, J. A., Rodriquez-Jimenez, T., Ortiz, A. G., Moreno, E., Lazaro, L., & Storch, E. A. (2017). Factor structure, reliability and validity of the Spanish version of the Children’s Florida Obsessive-Compulsive Inventory (C-FOCI). Child Psychiatry & Human Development, 48, 166 – 179. DOI: 10.1007/s10578-016-0661-4
  6. Zhang, C. C., McGuire, J. F., Qiu, X., Jin, H., Li, Z., Cepeda, S., Goodman, W. K., & Storch, E. A. (2017). Florida Obsessive-Compulsive Inventory: Psychometric properties in a Chinese psychotherapy-seeking sample.  Journal of Obsessive-Compulsive and Related Disorders, 12, 41 – 45. DOI: 10.1016/j.jocrd.2016.11.006

Substances and Choices Scale (SACS)

The Substances and Choices Scale (SACS) is an adolescent alcohol and other drug (AOD) use measurement instrument with high acceptability, validity and reliability. It has utility in screening and measuring outcome and can be used to enhance the identification and treatment of AOD difficulties in adolescents across a range of health settings.

The SACS a one-page pencil and paper self-report questionnaire for adolescents aged 13 -18 years. It takes about 5 minutes to complete and is free of charge. It can be completed alone or in association with the young person’s health or social agency worker. It is structured in a similar format to the Strengths and Difficulties Questionnaire (SDQ) and the two instruments can be used together if a broader perspective on a young person’s functioning is required. The SACS can assist in identifying young people at risk of AOD problems, guide future treatment or referral options and can measure outcomes as young people progress through the treatment process. Electronic online versions are also available.

The SACS is divided into 3 sections:

  • Section A (12 items) records the number of occasions the young person has used a variety of substances in the last month. The aim of this first section is to monitor occasions and range of substance use.
  • Section B (10 items) measures addictive behaviours, harms and consequences of substance use. Scoring this section yields the ‘SACS difficulties score’ from 0 to 20 which can be used to screen or measure change through a treatment episode.
  • Section C covers tobacco use.

There are clinical and community versions of the SACS which differ only in terms of the content of Section A, with the community version listing a limited number of substances. The SACS difficulties score (Section B) is the same in both versions thus the psychometric properties of each version are the same. The use of the clinical version is encouraged where possible to get a clearer perspective of a young person’s substance use.

References

Christie, G., Marsh, R., Sheridan, J., Wheeler, A., Suaalii-Sauni, T., Black, S., & Butler, R. (2007). The Substances and Choices Scale (SACS) – the development and testing of a new alcohol and other drug screening and outcome measurement instrument for young people. Addiction, 102(9), 1390-1398.

Eating Disorder Diagnostic Scale (EDDS)

The Eating Disorder Diagnostic Scale (EDDS; Stice, Telch, & Rizvi, 2000) is a 22-item self-report questionnaire designed to measure Anorexia nervosa, Bulimia nervosa, and Binge-eating disorder symptomatology aligned with the DSM-IV diagnostic criteria.

The scale is comprised of a combination of Likert ratings, dichotomous scores, behavioural frequency scores, and open-ended questions asking for weight and height. The first four questions assess attitudinal symptoms of Anorexia and Bulimia within the past 3 months. The next four items measure the frequency of uncontrollable food consumption, with a focus on the number of days per week over the past 6 months (a criterion for Binge-eating disorder), and number times per week over the last 3 months (a criterion for Bulimia). The following four items measure frequency of compensatory behaviours. Lastly, individuals are asked to record their height, weight, presence of menstrual cycles and birth control pill use.

There are two further scales used in the EDDS that differentiate between eating disorders and deviance from healthy eating pathology. The diagnostic scale may be used to inform diagnosis of Anorexia, Bulimia and Binge-eating disorders. Stice et al. (2000) have developed a scoring algorithm to accompany this scale to determine score cut-offs. The symptom composite scale may be used to create a continuous composite score of disordered eating pathology.

Psychometric Development & Validation

The EDDS went through a rigorous development and validation process with careful adherence to a number of steps. The developers first generated a pool of items to assess DSM-IV eating disorder diagnostic criteria. These items were evaluated by a panel of 14 eating disorder experts, followed by revision to eventually produce the final EDDS to test for reliability and validity against an American female sample aged 13 to 65 years inclusive of those with and without eating disorders.

Results revealed excellent 1-week test-retest reliability for Anorexia (kappa = .95), and adequate test-retest coefficients for Bulimia (kappa = .71) and Binge-eating disorder (kappa = .75). The overall symptom composite test-retest reliability was also strong (kappa = .87). Likewise, internal consistency of the overall symptom composite score was robust (Cronbach’s α = .91). These reliability magnitudes reflect Shrout’s (1998) psychometric rule-of-thumb whereby kappa values above .8 represent high reliability, values between .4 and .8 indicate moderate agreement, and values less than .4 suggest poor reliability.

Content validity results generated by the 14 eating disorder experts revealed that items within the scale adequately reflected the DSM-IV diagnostic criteria for Anorexia, Bulimia, and Binge-eating disorder. Consistently, data also suggested that the EDDS possessed convergent validity by comparing participants with eating disorders with their non-diagnosis control counterparts; with higher scores reported for those with eating disorders than those without.

Strengths & Weaknesses

The EDDS has an abundance of strengths. It is short and quick to complete. With only 22 items, it takes only a few minutes to complete the entire instrument. It is sensitive to change over time; that is, the EDDS has the versatility of being used as a screening tool at the beginning stages of assessment, a diagnostic tool in supporting eating disorder diagnostic criteria, and lastly it may also be used for treatment monitoring and evaluation.

However, the EDDS is not without its limitations. In at least one study, the EDDS has been found to generate a large number of ‘false positives’ (Lee et al., 2007), indicating a weakness in specificity. Conversely, this may not necessarily be a negative drawback considering that when used as a screening tool it is preferable to be able to identify more people as false positives than run a risk of missing out on detecting potential cases of eating disorders. This is because eating disorders, though low in prevalence compared to other clinical disorders, has one the highest mortality rates amongst psychiatric conditions (Arcelus, Mitchell, Wales, & Nielsen, 2011). Additional weaknesses include gender and cultural insensitivity. Different attitudes towards food consumption for gender was found to be reinforced by differing cultural ideals–which were not adequately captured in the EDDS (Lee et al., 2007). Similarly, eating disorder pathology and risk factors were not invariant across Caucasian American women and African American women (Kelly et al., 2012).

Conclusion

Overall, the EDDS is a short and quick to complete self-assessment tool that is versatile to use as a screening measure, diagnostic instrument, and treatment evaluation and monitoring tool for the assessment of Anorexia, Bulimia, and Binge-eating disorder. Its tendency to detect more false positives need not necessarily be a weakness given the vulnerability of the eating disorder population as having some of the most severe mortality and prognosis rates amongst mental conditions. The lack of gender and cultural sensitivity warrants further modifications and refinements by researchers so that this tool can adequately capture the individual nuances that exist both within and between minority groups.

Access

The EDDS is freely available following this link: http://www.ori.org/files/Static%20Page%20Files/EDDS.pdf. Information regarding scoring and interpretation may be found here: http://www.ori.org/files/Static%20Page%20Files/SticeTelch00.pdf.

References

Arcelus, J., Mitchell, A. J., Wales, J., & Nielsen, S. (2011). Mortality rates in patients with anorexia nervosa and other eating disorders: A meta-analysis of 36 studies. Archives of General Psychiatry, 68(7), 724-731. doi:10.1001/archgenpsychiatry.2011.74

Kelly, N. R., Mitchell, K. S., Gow, R. W., Trace, S. E., Lydecker, J. A., Bair, C. E., & Mazzeo, S. (2012). An evaluation of the reliability and construct validity of eating disorder measures in white and black women. Psychological Assessment, 24(3), 608-617. doi:10.1037/a0026457

Lee, S. W., Stewart, S. M., Striegel-Moore, R. H., Lee, S., Ho, S-Y., Lee, P. W. H., …Lam, T-H. (2007). Validation of the eating disorder diagnostic scale for use with Hong Kong adolescents. International Journal of Eating Disorders, 40(6), 569-574. doi:10.1002/eat

Shrout, P. (1998). Measurement reliability and agreement in psychiatry. Statistical Methods in Medical Research, 7(3), 301-317. doi:10.1191/096228098672090967

Stice, E., Telch, C. F., & Rizvi, S. L. (2000). Development and validation of the eating disorder diagnostic scale: A brief self-report measure of anorexia, bulimia, and binge-eating disorder. Psychological Assessment, 12(2), 123-131. doi:10.1037//1040-3590.12.2.123

Autism Treatment Evaluation Checklist (ATEC)

The Autism Treatment Evaluation Checklist (ATEC) is a 77-item diagnostic assessment tool that was developed by (Rimland & Edelson, 1999) at the Autism Research Institute. The ATEC was designed as a comparative subscale for ASD diagnosed individuals – that is to measure change in ASD individuals due to various interventions by difference between the initial (baseline) ATEC scores and later ATEC scores. The ATEC is to be completed by parents, teachers, or others who see the individual’s behaviour on a regular basis, this takes about 10–15 minutes to complete and is designed for use with children aged 5-12.

Scoring

The ATEC consists of four subtest scales: Scale I. Speech/Language/Communication (14 items – score range 0 – 28), Scale II. Sociability (20 items – score range 0 – 40), Scale III. Sensory/Cognitive Awareness (18 items – score range 0 – 36), and Scale IV. Health/Physical Behavior (25 items- score range 0 – 75). The four subscale scores are used to calculate a total score (77 items – score range 0 to 180). Overall scores in each subscale and in total can be used to determine the severity of the participant with higher scores indicating more impairment and lower scores with less impairment.

Psychometric Properties

On evaluation of 1,358 participants the ATEC presented high Pearson split-half (internal consistency) coefficients with uncorrected r values: Scale I. Speech/Language/Communication (r = .92), Scale II. Sociability (r = .84), Scale III. Sensory/Cognitive Awareness (r = .88) and Scale IV. Health/Physical Behaviour (r = .82).  Overall the internal consistency reliability of the measure is high (r = .94) for the total score. The ATEC has high correlations with the Childhood Autism Rating Scale (CARS) indicating further support of validity (ρ = .71, p < .0001) (Geier, Kern & Geier, 2013). Furthermore this was also indicative in results with sensitivity, specificity, and accuracy between CARS and total ATEC domains with sensitivity equal to 0.96, specificity at 0.67 and accuracy at 0.82. (Gier et al., 2013).

Clinical Utility

Overall the ATEC is indicative to be a useful screening tool to measure treatment effects and progress over time in ASD (Jarusiewicz, 2002; Lonsdale, Shamberger, & Audhya, 2002; Magiati, Moss, Yates, Charman, & Howlin, 2011). Strengths of the ATEC include high correlation with physical symptoms and biomarkers in ASD, (Adams, Johansen, Powell, Quig, & Rubin, 2011; Kern, Geier, Adams, & Geier, 2010) including quantitative assessment of these features as well as providing domain specific scores with an overall score and percentage of ASD severity. Furthermore the ATEC is simple to administer, easily understood and quick to complete. Limitations include limited research of reliability and validity as well as being based on previous versions of the Diagnostic Statistical Manual of Mental Disorders (DSM) therefore the tool may not be representative of the recent changes to autism in the DSM-5.

Links

Autism Research Institute Website: (http://www.autism.com/ind_atec_survey.asp).

ATEC with online scoring and results: http://www.surveygizmo.com/s3/1329619/Autism-Treatment-Evaluation-Checklist-revised

References:

Adams J. B., Johansen L. J., Powell L. D., Quig D., Rubin R. A. Gastrointestinal flora and gastrointestinal status in children with autism: Comparisons to typical children and correlation with autism severity. (2011). BMC Gastroenterology. 11, 22

Geier, D.A., Kern, J.K., & Geier, M.R. (2013).  A comparison of the Autism Treatment Evaluation Checklist (ATEC) and the Childhood Autism Rating Scale (CARS) for the quantitative evaluation of autism.  Journal of Mental Health Research in Intellectual Disabilities, Vol. 6, No. 4, pp 255-267.

Jarusiewicz B. Efficacy of neurofeedback for children in the autism spectrum: A pilot study. (2012). Journal of Neurotherapy. 6 pp 39–49.

Kern J. K., Geier D. A., Adams J. B., Geier M. R. A biomarker of mercury body-burden correlated with diagnostic domain-specific clinical symptoms of autism spectrum disorder. (2010). Biometals. 23, pp 1043–1051.

Lonsdale D., Shamberger R. J., Audhya T. Treatment of autism spectrum children with thiamine tetrahydrofurfuryl disulfide: A pilot study. (2002) Neuroendocrinology Letters. 23, pp 303–308.

Magiati I., Moss J., Yates R., Charman T., Howlin P. Is the Autism Treatment Evaluation Checklist a useful tool for monitoring progress in children with autism spectrum disorders? (2011). Journal of Intellectual & Disabilities Research. 55, pp 302–312.

Rimland B., Edelson M. Autism Treatment Evaluation Checklist. Autism Research Institute; 1999. 4812 Adams Avenue, San Diego, CA 92116. Retrieved from https://www.autismeval.com/ari-atec/report1.html.