Feeling Loved: A Novel Brief Self-Report Health Measure.

CONTEXT: There is need for a short validated self-report instrument for assessing the feeling of being loved. The Feeling Loved instrument asks: "Do you feel loved?" and "How loved do you feel?" as well as "Do you love yourself?" and "How much do you love yourself?" with 100 mm visual analogue scales assessing the continuous response options. OBJECTIVE: To assess convergent and discriminant validity and to explore psychometric structure for this novel self-report measure. DESIGN: Convergent validity comparators include: general mental health, perceived social support, perceived stress, depressive symptoms, and positive/negative emotion. Discriminant validity comparators include: gender, age, ethnicity, socioeconomic status, and body mass index. Latent class analysis techniques explore psychometric structure. SETTING: Baseline evaluation for a randomized controlled trial. PARTICIPANTS: Community-recruited adults in Madison, Wisconsin. INTERVENTION: This validation study is based on pre-intervention data. MAIN OUTCOME MEASURES: Strength of correlation with comparators is used to assess convergence and discrimination. Goodness-of-fit indicators assess latent class models. RESULTS: Of n = 412 respondents, 92% answered positively to both Yes/No questions, and 59% self-rated ≥75/100 on both 0-to-100 VAS scales. Supporting convergent validity, highly significant (p < 0.001) Spearman's rho=ρ correlations of a summed Feeling Loved score were: mental health (ρ = 0.49); social support (ρ = 0.46); perceived stress (ρ = -0.46), depressive symptoms (ρ = -0.31), and both positive (ρ = 0.50) and negative (ρ = -0.43) emotion. Significant associations were also found for personality indicators. Supporting discriminant validity, Feeling Loved scores did not correlate significantly with physical health (ρ = -0.08), body mass index (ρ = 0.01), age (ρ = 0.06), or income (ρ = 0.07) (p values all ≥ 0.12). Latent class analysis models suggested a 3-class structure, with strong goodness-of-fit indicators.

Self-Reported Mental Health Predicts Acute Respiratory Infection.

BACKGROUND: Poor mental health conditions, including stress and depression, have been recognized as a risk factor for the development of acute respiratory infection. Very few studies have considered the role of general mental health in acute respiratory infection occurrence. The aim of this analysis is to determine if overall mental health, as assessed by the mental component of the Short Form 12 Health Survey, predicts incidence, duration, or severity of acute respiratory infection. METHODS: Data utilized for this analysis came from the National Institute of Health-funded Meditation or Exercise for Preventing Acute Respiratory Infection (MEPARI) and MEPARI-2 randomized controlled trials examining the effects of meditation or exercise on acute respiratory infection among adults aged > 30 years in Madison, Wisconsin. A Kendall tau rank correlation compared the Short Form 12 mental component, completed by participants at baseline, with acute respiratory infection incidence, duration, and area-under-the-curve (global) severity, as assessed by the Wisconsin Upper Respiratory Symptom Survey. RESULTS: Participants were recruited from Madison, Wis, using advertisements in local media. Short Form 12 mental health scores significantly predicted incidence (P = 0.037) of acute respiratory infection, but not duration (P = 0.077) or severity (P = 0.073). The Positive and Negative Affect Schedule (PANAS) negative emotion measure significantly predicted global severity (P = 0.036), but not incidence (P = 0.081) or duration (P = 0.125). Mindful Attention Awareness Scale scores significantly predicted incidence of acute respiratory infection (P = 0.040), but not duration (P = 0.053) or severity (P = 0.70). The PHQ-9, PSS-10, and PANAS positive measures did not show significant predictive associations with any of the acute respiratory infection outcomes. CONCLUSION: Self-reported overall mental health, as measured by the mental component of Short Form 12, predicts acute respiratory infection incidence.