JMIR mhealth and uhealth · 2016 · 26 citations · 25 references
Social SciencesHealth BehaviorPsychologyHealth PsychologyPsychometricsScale DevelopmentAddiction AssessmentFactor AnalysisItem AnalysisPsychological TestingScale RefinementTest ReliabilityBehavior Change InterventionsDepressive Symptom AssessmentHealth Behavior ChangeInternal Consistency ReliabilityMobile Communication Usage PatternsMulti-group Measurement ModelsProductivityResilience Scales
BACKGROUND: Existing instruments that assess individuals' relationships with mobile phones tend to focus on negative constructs such as addiction or dependence, and appear to assume that high mobile phone use reflects pathology. Mobile phones can be beneficial for health behavior change, disease management, work productivity, and social connections, so there is a need for an instrument that provides a more balanced assessment of the various aspects of individuals' relationships with mobile phones. OBJECTIVE: The purpose of this research was to develop, revise, and validate the Mobile Phone Affinity Scale, a multi-scale instrument designed to assess key factors associated with mobile phone use. METHODS: Participants (N=1058, mean age 33) were recruited from Amazon Mechanical Turk between March and April of 2016 to complete a survey that assessed participants' mobile phone attitudes and use, anxious and depressive symptoms, and resilience. RESULTS: Confirmatory factor analysis supported a 6-factor model. The final measure consisted of 24 items, with 4 items on each of 6 factors: Connectedness, Productivity, Empowerment, Anxious Attachment, Addiction, and Continuous Use. The subscales demonstrated strong internal consistency (Cronbach alpha range=0.76-0.88, mean 0.83), and high item factor loadings (range=0.57-0.87, mean 0.75). Tests for validity further demonstrated support for the individual subscales. CONCLUSIONS: Mobile phone affinity may have an important impact in the development and effectiveness of mobile health interventions, and continued research is needed to assess its predictive ability in health behavior change interventions delivered via mobile phones.
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