Subject code: E02aa02

Study | Feather & O'Brien (1986): study AU 1980 |

Title | A Longitudinal Study of the Effects of Employment and Unemployment on School-Leavers. |

Source | Journal of Occupational Psychology, 1986, Vol. 59, 121 -144 |

Public | School-leavers, Australia, followed 2 years,1980-1982 |

Sample | |

Non-Response | T2: 25%, T3: 34% |

Respondents N = | 5446 |

Correlate | |

Author's label | Unemployment. |

Page in Source | 131-134 |

Our classification | Change in employment, code E02aa02 |

Operationalization | 0 Employed at T2/T3. 1 Unemployed at T2/T3 |

Remarks | Level of happiness at T1(1980), T2(1981) and T3(1982). T1 and T2 happiness by T2 employment(sample A): T2-empl. T2 unempl. difference |

Observed Relation with Happiness | ||

Happiness Measure | Statistics | Elaboration/Remarks |

A-CP-g-mq-n-24-a | AoV=+ ns | happiness at T1 Mt'= 6.53 Mt'= 6.46 -.07 happiness at T2 Mt'= 6.61 Mt'= 6.16 -.45 Interaction employment x time (nonsignificant): happ. T1 to T2 +.08 -.30 -.38 T1 and T3 happiness by T3 employment(sample A): T3-empl. T3 unempl. difference |

A-CP-g-mq-n-24-a | AoV=- p < .01 | happiness at T1 Mt'= 6.60 Mt'= 6.36 -.24 happiness at T3 Mt'= 6.50 Mt'= 5.80 -.70 Interaction employment x time ( p<01 ): happ. T1 to T3 -.10 -.56 -.46 T2 and T3 happiness by T3 employment(sample A+B): T3-empl. T3 unempl. difference |

A-CP-g-mq-n-24-a | AoV=- p < .01 | happiness at T2 Mt'= 6.27 Mt'= 5.93 -.34 happiness at T3 Mt'= 6.43 Mt'= 5.60 -.83 Interaction employment x time ( p< 01): happ. T2 to T3 +.16 -.33 -.49 Significance assessed by variance-analysis, also involving employment. The original depression score is ranging from 4 to 28. Mt' is standardized into a happpiness score (0-10 and reversed) Possible testing effects checked by comparing three sub-samples: - sample A: selected at T1, tested at T1, T2, T3 - sample B: selected at T1, tested at T2 and T3 - sample C: selected at T1, tested at T3 only At T3 happiness appeared lower in sample A than in sample B, but there is little evidence for systematic testing effects. |

Appendix 1: Happiness measures used

Code | Full Text |

A-CP-g-mq-n-24-a | Selfreport on 4 questions: How do you see yourself in general....? A 'happy' to 'sad', B 'elated' to 'depressed', C 'tensed' to 'relaxed' D 'satisfied' to 'dissatisfied'. Scoring: each item scored on bi-polar 7 step numerical scale. Summation: scores added; possible range 4-28 |

Appendix 2: Statistics used

Symbol | Explanation |

AoV | ANALYSIS of VARIANCE (ANOVA) Type: statistical procedure Measurement level: Correlate(s): nominal, Happiness: metric. In an ANOVA, the total happiness variability, expressed as the sum of squares, is split into two or more parts, each of which is assigned to a source of variability. At least one of those sources is the variability of the correlate, in case there is only one, and always one other is the residual variability, which includes all unspecified influences on the happiness variable. Each sum of squares has its own number of degrees of freedom (df), which sum up to Ne -1 for the total variability. If a sum of squares (SS) is divided by its own number of df, a mean square (MS) is obtained. The ratio of two correctly selected mean squares has an F-distribution under the hypothesis that the corresponding association has a zero-value. NOTE: A significantly high F-value only indicates that, in case of a single correlate, the largest of the c mean values is systematically larger than the smallest one. Conclusions about the other pairs of means require the application of a Multiple Comparisons Procedure (see e.g. BONFERRONI's MULTIPLE COMPARISON TEST, DUNCAN's MULTIPLE RANGE TEST or STUDENT-NEWMAN-KEULS) |

Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.

https://worlddatabaseofhappiness.eur.nl