Performance of the interpersonal needs questionnaire in adolescent clinical samples: Confirmatory factor analyses and evaluation of measurement invariance.

OBJECTIVE: This study evaluated the factor structure, internal consistency reliability, construct and criterion validity, and measurement invariance of the Interpersonal Needs Questionnaire (INQ) among adolescents. METHOD: Participants (N = 539) included three distinct samples of youth drawn from two outpatient psychology clinics and an inpatient psychiatric unit. The combined sample was 63.3% female and had a mean age of 14.95 years (SD = 1.31 years). All participants completed the INQ as well as measures of depressive symptoms and suicide ideation. RESULTS: Confirmatory factor analyses indicated that the removal of three items from the thwarted belongingness subscale of the INQ was needed to achieve acceptable model fit. The resulting combined 12-item scale demonstrated good factor structure, internal consistency reliability, construct validity, and criterion validity. The modified 12-item INQ also demonstrated scalar invariance across subgroups defined by sex, race, and age. CONCLUSIONS: Findings support the use of this reduced 12-item version of the INQ among adolescents. Youth may have difficulty accurately responding to changes in item valence; thus, future research with youth should consider using a 12-item version of the INQ that avoids valence changes within subscales.

Suicide Safety Planning: Clinician Training, Comfort, and Safety Plan Utilization.

Extant literature has demonstrated that suicide safety planning is an efficacious intervention for reducing patient risk for suicide-related behaviors. However, little is known about factors that may impact the effectiveness of the intervention, such as provider training and comfort, use of specific safety plan elements, circumstances under which providers choose to use safety planning, and personal factors which influence a provider's decision to use safety planning. Participants were (N = 119) safety plan providers who responded to an anonymous web-based survey. Results indicated that most providers had received training in safety planning and were comfortable with the intervention. Providers reported that skills such as identifying warning signs and means safety strategies were routinely used. Providers who reported exposure to suicide were more likely to complete safety plans with patients regardless of risk factors. In addition, almost 70% of providers indicated a need for further training. These data provide important considerations for safety plan implementation and training.

Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.

This study applies classification tree analysis to prospectively identify suicide attempters among a large adolescent community sample, to demonstrate the strengths and limitations of this approach for risk identification. Data were drawn from the National Longitudinal Study of Adolescent to Adult Health. Youth (n = 4,834, Mage = 16.15, SD = 1.63, 52.3% female, 63.7% White) completed at-home interviews at Wave 1 and a measure of suicide attempts 12 months later, at Wave 2. Results indicated two classification tree solutions that maximized risk prediction, with 69.8%/85.7% sensitivity/specificity and 90.6%/70.9% sensitivity/specificity, respectively. Classification trees provide a technique for identification of individuals at-risk for suicide attempts. Classification trees produce easy-to-implement decision rules and tailored screening approaches that can be adapted to the goals of a particular organization.