Factors Affecting Happiness Among Rural Residents: A Cross Sectional Survey

Jo, Hae Kyung; Kim, Mi Kyeong; Jeong, Ji Na

doi:10.1007/s10597-020-00555-1

Cited by 10 publications

(9 citation statements)

References 25 publications

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“…A study on the keys to happiness found that social life was associated with greater chance of happiness while factors like money power and health were adversely associated with happiness [10]. In another study, happiness was correlated with age, income, violence, social support, and subjective health [7]. On the other hand, a research on factors affecting happiness index found that physical well-being was the most influential factor in determining happiness index [13].…”

Section: Acknowledged Workmentioning

confidence: 99%

“…Recent studies have shown happiness is extremely dependent on social life, daily activities, exercises, and time management and there are conflicting results in some of the factors studied [2,6,7,11,13]. Current study relied and explored the same factors by examining how people can allocate time and attention to better their lives financially, physically, and socially by employing a neural network that involved a pool of fourteen variables to keenly follow up on factors affecting happiness and predict whether a person is happy or not happy.…”

Section: Statement Of the Problemmentioning

confidence: 99%

“…Many studies in this area have been contradicting showing how researchers have struggles to explore happiness. Various factors have been linked to happiness and the key factors are Love, Exercising, Relaxing, Career, Friends, Family, Sleep, Traveling, Health, and income [1,7,11,13]. Numerous studies found physical activeness as the main factor to determine happiness.…”

Section: Acknowledged Workmentioning

confidence: 99%

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Prediction of Levels of Happiness Using Multinomial Logit as a Neural Network: Evidence in Kenyan Youths

Ngari¹,

Wanjoya²,

Kihoro³

2022

IJDSA

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Happiness has become a major concern across many disciplines starting form public policy, economics and psychology because of the effects that come with not being happy. Psychologist would want to know the effects of low levels of happiness, economist would want to know the effects of levels of happiness in to the market place, researchers from health would be concerned with effects of high and low levels of happiness to health status. While predominantly, people had just a philosophical notion about happiness, currently there are numerous scientific studies on happiness. Approaches like cluster analysis have been employed before. This research used neural networks to classify multinomial levels of happiness of Kenyan youths by considering life style aspects of current life such as Internet usage, Physical activeness, Health, Social life, Education, Income, Country's top leadership, Dining and Sleeping Habits. The research was able to fit a 14-1-4 neural network model to classify levels of happiness in Kenyan youths, an accuracy of 73% was achieved. The data was randomly split in to 70% training set and 30% test set. The training set was balanced using SMOTE approach. This research trained the model by applying gradient descent using error back propagation algorithm with initial weights drawn from uniform distribution and applied softmax activation function. Accuracy metrics were confusion matrix, precision and recall for each level of happiness, and F-Scores. The top leading factor related to happiness positively was physical activeness with youths who were more active being happier. The second factor was relationship type, the married youths were happier than the singles, separated or engaged. Youths who were more satisfied with their relationship, they were happier. Health was also positively related to happiness. On the other hand, the number of hours a youth spent on social media negatively affected their levels of happiness. The more the number of hours the low levels of happiness.

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Section: Acknowledged Workmentioning

confidence: 99%

Section: Statement Of the Problemmentioning

confidence: 99%

Section: Acknowledged Workmentioning

confidence: 99%

See 1 more Smart Citation

Prediction of Levels of Happiness Using Multinomial Logit as a Neural Network: Evidence in Kenyan Youths

Ngari¹,

Wanjoya²,

Kihoro³

2022

IJDSA

View full text Add to dashboard Cite

show abstract

“…Furthermore, rural residents not only may be more accustomed to self-isolation and cohesive family interdependence, but they may actively cultivate these lifestyle qualities. 48,49 Thus, sheltering in place may not feel as constricting as it would to an urban or suburban resident. We may be able to discern much from the rural community about how to effectively adjust and live so as to successfully weather this pandemic and minimize related adverse mental health sequelae.…”

mentioning

confidence: 99%

“…The reason that individuals in rural communities are at diminished risk is merely a matter of density: the same reason why state governors and local municipalities initially banned gatherings of over 50 people, subsequently reduced them to 10, and in some cases as few as 2. Furthermore, rural residents not only may be more accustomed to self‐isolation and cohesive family interdependence, but they may actively cultivate these lifestyle qualities 48,49 . Thus, sheltering in place may not feel as constricting as it would to an urban or suburban resident.…”

mentioning

confidence: 99%