Ennis Edel, Bond Raymond, Mulvenna Maurice, Sweeney Colm
School of Psychology, Ulster University, Coleraine, United Kingdom.
School of Computing, Ulster University, Belfast, United Kingdom.
JMIR Form Res. 2025 Jan 29;9:e65658. doi: 10.2196/65658.
Psychologists have developed frameworks to understand many constructs, which have subsequently informed the design of digital mental health interventions (DMHIs) aimed at improving mental health outcomes. The science of happiness is one such domain that holds significant applied importance due to its links to well-being and evidence that happiness can be cultivated through interventions. However, as with many constructs, the unique ways in which individuals experience happiness present major challenges for designing personalized DMHIs.
This paper aims to (1) present an analysis of how sex may interact with age, marital status, and parental status to predict individual differences in sources of happiness, and (2) to present a preliminary discussion of how open datasets may contribute to the process of designing health-related technology innovations.
The HappyDB is an open database of 100,535 statements of what people consider to have made them happy, with some people asking to consider the past 24 hours (49,831 statements) and some considering the last 3 months (50,704 statements). Demographic information is also provided. Binary logistic regression analyses are used to determine whether various groups differed in their likelihood of selecting or not selecting a category as a source of their happiness.
Sex and age interacted to influence what was selected as sources of happiness, with patterns being less consistent among female individuals in comparison with male individuals. For marital status, differences in sources of happiness were predominantly between married individuals and those who are divorced or separated, but these were the same for both sexes. Married, single, and widowed individuals were all largely similar in their likelihood of selecting each of the categories as a source of their happiness. However, there were some anomalies, and sex appeared to be important in these anomalies. Sex and parental status also interacted to influence what was selected as sources of happiness.
Sex interacts with age, marital status, and parental status in the likelihood of reporting affection, bonding, leisure, achievement, or enjoying the moment as sources of happiness. The contribution of an open dataset to understanding individual differences in sources of happiness is discussed in terms of its potential role in addressing the challenges of designing DMHIs that are ethical, responsible, evidence based, acceptable, engaging, inclusive, and effective for users. The discussion considers how the content design of DMHIs in general may benefit from exploring new methods informed by diverse data sources. It is proposed that examining the extent to which insights from nondigital settings can inform requirements gathering for DMHIs is warranted.
心理学家已开发出多种框架来理解许多概念，这些框架随后为旨在改善心理健康结果的数字心理健康干预措施（DMHI）的设计提供了参考。幸福科学就是这样一个领域，由于其与幸福感的关联以及有证据表明幸福可以通过干预来培养，因而具有重要的应用价值。然而，与许多概念一样，个体体验幸福的独特方式给设计个性化的数字心理健康干预措施带来了重大挑战。
本文旨在（1）分析性别如何与年龄、婚姻状况和父母身份相互作用，以预测幸福来源的个体差异；（2）初步探讨开放数据集如何有助于设计与健康相关的技术创新。
HappyDB是一个开放数据库，包含100535条关于人们认为使自己幸福的事情的陈述，其中一些人被要求考虑过去24小时（49831条陈述），另一些人则考虑过去三个月（50704条陈述）。同时还提供了人口统计学信息。采用二元逻辑回归分析来确定不同群体在选择或不选择某一类别作为幸福来源的可能性上是否存在差异。
性别和年龄相互作用，影响了被选为幸福来源的因素，与男性相比，女性的模式不太一致。对于婚姻状况，幸福来源的差异主要存在于已婚个体与离异或分居个体之间，但两性情况相同。已婚、单身和丧偶个体在选择每个类别作为幸福来源的可能性上大致相似。然而，也存在一些异常情况，性别在这些异常情况中似乎很重要。性别和父母身份也相互作用，影响了被选为幸福来源的因素。
在将情感、亲密关系、休闲、成就或享受当下视为幸福来源的可能性方面，性别与年龄、婚姻状况和父母身份存在相互作用。从应对设计符合伦理、负责、基于证据、可接受、引人入胜、包容且对用户有效的数字心理健康干预措施所面临的挑战的潜在作用角度，讨论了开放数据集对理解幸福来源个体差异的贡献。该讨论考虑了一般情况下数字心理健康干预措施的内容设计如何从探索受多种数据源启发的新方法中受益。建议有必要研究非数字环境中的见解在多大程度上可为数字心理健康干预措施的需求收集提供参考。
