Nomophobia is defined as the fear of being out of mobile phone contact and is considered to be a phobia of the modern age. The current study set out to establish the relationship between temperament and personality and the development of nomophobia. The sample was composed of 968 participants selected from the Andalusian population, of which there were 182 males and 785 females aged from 23.19 years. The instruments used were the Questionnaire to Assess Nomophobia (QANIP; Olivencia-Carrión et al., 2018) and the Temperament and Character Inventory Revised (TCI-R; Cloninger et al., 1993). We found that cooperation is a characteristic that significantly reduces nomophobic levels, particularly for the two factors of Mobile Phone Addiction and Negative Consequences. Furthermore, Reward Dependence appears to be positively related to two of the factors involved in nomophobia, namely Mobile Phone Addiction and Loss of Control, suggesting a relationship between Nomophobia and personality. These findings are discussed in terms of their usefulness for identifying the personality predictors of nomophobia in order to develop preventive and intervention strategies.

Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due to the sampling mechanism commonly used, whereby participants self-select from a subgroup whose characteristics differ from those of the target population. Several techniques have been proposed to tackle this issue. One such is Propensity Score Adjustment (PSA), which is widely used and has been analysed in various studies. The usual method of estimating the propensity score is logistic regression, which requires a reference probability sample in addition to the online nonprobability sample. The predicted propensities can be used for reweighting using various estimators. However, in the online survey context, there are alternatives that might outperform logistic regression regarding propensity estimation. The aim of the present study is to determine the efficiency of some of these alternatives, involving Machine Learning (ML) classification algorithms. PSA is applied in two simulation scenarios, representing situations commonly found in online surveys, using logistic regression and ML models for propensity estimation. The results obtained show that ML algorithms remove selection bias more effectively than logistic regression when used for PSA, but that their efficacy depends largely on the selection mechanism employed and the dimensionality of the data.

Female genital cutting (FGC) has major implications for women’s physical, sexual and psychological health, and eliminating the practice is a key target for public health policy-makers. To date one of the main barriers to achieving this has been an inability to infer privately-held views on FGC within communities where it is prevalent. As a sensitive (and often illegal) topic, people are anticipated to hide their true support for the practice when questioned directly. Here we use an indirect questioning method (unmatched count technique) to identify hidden support for FGC in a rural South Central Ethiopian community where the practice is common, but thought to be in decline. Employing a socio-demographic household survey of 1620 Arsi Oromo adults, which incorporated both direct and indirect direct response (unmatched count) techniques we compare directly-stated versus privately-held views in support of FGC, and individual variation in responses by age, gender and education and target female (daughters versus daughters-in-law). Both genders express low support for FGC when questioned directly, while indirect methods reveal substantially higher acceptance (of cutting both daughters and daughters-in-law). Educated adults (those who have attended school) are privately more supportive of the practice than they are prepared to admit openly to an interviewer, indicating that education may heighten secrecy rather than decrease support for FGC. Older individuals hold the strongest views in favour of FGC (particularly educated older males), but they are also more inclined to conceal their support for FGC when questioned directly. As these elders represent the most influential members of society, their hidden support for FGC may constitute a pivotal barrier to eliminating the practice in this community. Our results demonstrate the great potential for indirect questioning methods to advance knowledge and inform policy on culturally-sensitive topics like FGC; providing more reliable data and improving understanding of the “true” drivers of FGC.