Pre- and post-morbid mental health conditions can prolong recovery from concussion and are generally detrimental to athletic performance and quality of life. If psychiatric conditions can be identified in athletes at the time of baseline testing, psychological/psychiatric intervention can be implemented to prevent these complications. Given the time constraints on neuropsychological baseline testing, it is important to have time-efficient screening measures. As such, the purpose of this study was to develop and calibrate a psychiatric screening measure within the Post-Concussion Symptom Scale (PCSS) from the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), which is commonly administered to athletes at baseline, thereby “killing two birds with one stone”: (1) screening for psychiatric conditions and (2) obtaining a baseline measurement of concussion-like symptoms.

Participants were 278 undergraduate students from a Canadian university with a mean age of 21.87 years (SD=4.87, range=18 to 52) and a sex composition of 64% females (n=179, Age: M=21.29 years-old, SD=4.34, range: 18 to 52) and 36% males (n=179, Age: M=22.93 years-old, SD=5.57, range: 18 to 50). Participants were a convenience sample collected via online survey platform in exchange for bonus points toward courses through a participant pool system between January and July 2021. The psychiatric screener consisted of the affective subscale from the PCSS (irritability, sadness, feeling more emotional, nervousness) and the criterion measure was the Depression, Anxiety, and Stress Scales (DASS-42). Statistical analyses were conducted in R v.4.3 and included confirmatory factor analysis and receiver operating characteristic (ROC) curve analyses. Although a balance was sought between sensitivity and specificity, the former was prioritized given that this is intended as a screening measure. Males and females were analyzed separately as females tend to report more symptoms than males. Mild, moderate, and severe elevations were predicted for depression, anxiety, and stress, based on standard DASS cutoffs.

The CFA analyses revealed good fit for both the PCSS (CFI=.992; TLI=.991; RMSEA=.053; SRMR=.066) and DASS (CFI=.995; TLI=.995; RMSEA=.053; SRMR=.065) models. Cutoffs of >3, >4, and >8 (SENS= .77-.80, SPEC= .52-.83) optimally classified males as having mild, moderate, and severe depression, respectively; and cutoffs of >8, >8, and >9 (SENS= .79-.83, SPEC= .63-.67) optimally classified females as having mild, moderate, and severe depression, respectively. A cutoff of >2 (SENS= .78-.81, SPEC= .35-.39) optimally classified males as having both mild and moderate anxiety (insufficient n in severe group); and >7, >8, and >9 (SENS= .80-.85, SPEC= .63-.68) optimally classified females as having mild, moderate, and severe anxiety. Cutoffs of >5and >8(SENS= .80-.86, SPEC= .70-.85) were optimal for detecting mild and moderate stress in males (insufficient n in severe group); and >8, >8, and >9 (SENS= .80.89, SPEC= .60-.75) were optimal in females.

The affective subscale within the PCSS operates well as a psychiatric screening measure. In general, females had higher cutoffs and the cutoffs for mild and moderate levels of the conditions tended to be similar. Males were less onsistent, with cutoffs varying widely depending on the construct and severity.