Introduction Smartphones, in addition to communicating, provide many technological opportunities such as internet access, entertainment environments, navigation services, and the ability to take photos and videos. Smartphones, as a result of these features, have become indispensable tools for their users, not only in their personal lives but also in their professional and educational lives. The extensive data usage and storage capabilities of smartphones have revealed both the benefits that will improve people’s lives and the negative consequences, as they have been made smaller and more suitable portable personal tools as a result of technological advancements (Adnan, Gezgin, 2016; Aktaş, Yilmaz, 2017). Smartphone addiction, particularly in parents with children, can disrupt their own lives and their obligations and relationships with their children. According to Zhou et al. (2014), it has been concluded that people who are addicted to mobile phones neglect their children and do not spend enough time with them, and these parents demonstrate a bad example for their children. The fact that parents are constantly distracted by their phones when near their children increases their children’s interest and willingness to use the phone through “social learning” (Yusufolu, 2017). When viewed in this light, the significance of a comprehensive assessment of the concept of smartphone addiction in the family becomes clear. Examining the literature in our nation, it has been discovered that studies on smartphone addiction are conducted individually with students or studying at various levels. However, no scale in the literature has been found to determine the family’s smartphone usage habits holistically. However, given that smartphone technologies are now used by people of all ages, the importance of holistic smartphone addiction in the family has drawn attention. From this perspective, the research problem was identified as the development of a comprehensive scale to assess the smartphone usage habits of parents and their children collectively. Thus, the goal is to contribute to the literature with more comprehensive and detailed research findings that examine the smartphone addiction of parents and their children in the family together. This study aims to develop a scale that can assess the family’s level of smartphone addiction. Method The goal of this study was to develop a scale to detect smartphone addiction in parents and their children in the family. In this regard, during the scale development process, an item pool was first created by reviewing the relevant literature in Turkey and abroad. An expert evaluation form was created following the expert review. The content validity ratios were calculated based on expert opinions to determine the extent to which the items in this evaluation form serve the purpose. The content validity rates were calculated using the Lawshe (1975) technique. Following the inclusion of content validity in the scale, studies on construct validity, another factor influencing the measurement tool, were conducted. The factor analysis method, one of the most commonly used approach, was used in this study to determine the construct validity. Factor analysis is performed in two ways based on explanation and verification. First, exploratory factor analysis was employed in the study to reveal the scale’s factor structure. In this direction, one of the factor analysis methods, principal component analysis (Can, 2013), was used to eliminate unnecessary items measuring the same feature and to determine the least number of variables. Findings The Family Smartphone Addiction Scale, which was developed to measure parents’ views on the level of smartphone addiction in the family, is a Likert-type scale with five options (Strongly disagree-Strongly agree); it consists of 2 subscales and 20 items as the “Parent Dimension,” which determines parents’ views about themselves, and the “Child Dimension,” which specifies parents’ views about their child. During the scale development phase, the relevant literature was thoroughly reviewed, and a 54-item question pool was created for the scale. The items were then pre-examined by an expert working in the field of education programs and teaching for clarity and suitability for the scale. A 42-item expert evaluation form was created based on their opinions. To ensure the content validity of this 42-item form, the Lawshe technique was used. As a result, the KGI value of 0.82 was higher than the value of 0.78 determined by Veneziano and Hooper (1997) based on the number of experts (cited in Yurdugül, 2005), which statistically proved that the scale provided content validity. To determine the suitability of the scale for factor analysis, the data set of 288 people were tested first, with the KMO value = 0.928 and the Barlett Sphericity Test p-value = 0.000 indicating that the data set was suitable for factor analysis. The two factor structure with 20 items emerged from the exploratory factor analysis. The first factor’s eigenvalue was 8.702 and explained 33.52% of the variance, while the second factor’s eigenvalue was 3.290 and explained 26.43% of the variance. All 20 items distributed across two factors explain 59,960% of the total variance. From this perspective, it has been demonstrated that the contribution of the obtained results to the total variance is sufficient. The resulting factors were subjected to confirmatory factor analysis. The resulting values were compared with the fit indices proposed by Schermelleh-Engel et al. (2003), confirming the scale’s two-factor structure and demonstrating that the calculated goodness-of-fit values were within acceptable or good fit ranges. According to the reliability analysis performed with 20 items in the scale, the Cronbach Alpha reliability coefficient was 0.928, the “Child Dimension” factor was 0.936, and the ratio of the “Parent Dimension” factor was 0.911, proving that the scale has a highly rel