Changes of teachers’ subjective well-being in mainland China (2002~2019): The perspective of cross-temporal meta-analysis

doi:10.3724/SP.J.1041.2021.00875

Abstract

Abstract:

As a key index to measure the mental health of teachers, teachers’ subjective well-being is very important to the investigation and analysis of their current situation, and it cannot be neglected to monitor the trend of its dynamic change with the social change and its relationship with the social change. This study conducted a cross-temporal meta-analysis of 51 reports measuring teachers’ subjective well-being (SWB) from 2002 to 2019, including 13,600 teachers. The findings are as follows: (1) the average scores of subjective well-being of teachers is negatively correlated with the year, which indicates that the subjective well-being of teachers in China is decreasing year by year. (2) the changes of eight macro-social indicators from three aspects of social economic conditions (consumption level, housing price, old-age dependency ratio and education funds), social connection (family size, divorce rate and urbanization level) and social threat (crime rate) can significantly predict the decline of teachers’ subjective well-being. (3) the subjective well-being of primary and middle school teachers has a tendency to decrease with the year, and the scores of subjective well-being are lower than those of college teachers. This study not only explores the changing trend of teachers’ subjective well-being in China in the past 20 years, but also puts forward a three-dimensional theoretical framework that influences teachers’ subjective well-being in China. This paper extends the research ideas of group social psychology vertically (with the changes of the times) and horizontally (macroscopical social index), expanding the theoretical basis, and in practice, providing the decision-making basis for intervening and regulating the subjective well-being level of teachers in our country.

Key words: teachers, subjective well-being, the General Wellbeing Schedule, social change, cross-temporal meta-analysis, meta- analysis

XIN Sufei, LIANG Xin, SHENG Liang, ZHAO Zhirui. (2021). Changes of teachers’ subjective well-being in mainland China (2002~2019): The perspective of cross-temporal meta-analysis. Acta Psychologica Sinica, 53(8), 875-889.

Figures/Tables 5

References 78

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Year of publication	Totality		Study phase
Year of publication	Number of papers	Sample Size	Primary and secondary schools	High School
2004	1	410	1	0
2005	1	131	1	0
2007	2	340	1	1
2008	1	724	0	1
2010	2	1013	2	0
2011	2	455	2	0
2012	3	525	2	1
2013	8	2242	4	3
2014	3	842	1	3
2015	3	604	2	1
2016	9	2000	5	4
2017	9	2829	8	1
2018	1	232	1	0
2019	4	980	3	1
2020	2	273	1	0
Total	51	13600	34	16

Year of publication	Totality		Study phase
Year of publication	Number of papers	Sample Size	Primary and secondary schools	High School
2004	1	410	1	0
2005	1	131	1	0
2007	2	340	1	1
2008	1	724	0	1
2010	2	1013	2	0
2011	2	455	2	0
2012	3	525	2	1
2013	8	2242	4	3
2014	3	842	1	3
2015	3	604	2	1
2016	9	2000	5	4
2017	9	2829	8	1
2018	1	232	1	0
2019	4	980	3	1
2020	2	273	1	0
Total	51	13600	34	16

First author	Publish year	Collect year	Sample size	M	SD	Male proportion	Journal type	Region	Study phase
Pan	2004	2002	410	77.55	11.43	0.41	3	1	1
Su	2005	2003	131	85.52	11.10	0.31	2	0	1
Wang	2007	2005	61	76.62	13.66	NA	1	1	1
Mao	2007	2005	279	80.79	15.00	0.58	1	2	2
Zhou	2008	2006	724	80.58	12.29	0.42	2	2	2
Sun	2010	2008	365	76.95	13.11	0.52	2	3	1
Liang	2010	2008	648	76.71	9.46	0.45	1	3	1
Xian	2011	2009	363	76.26	9.90	0.39	1	4	1
Wang	2011	2009	92	77.82	9.81	NA	1	3	1
Yang	2012	2010	366	75.64	NA	NA	1	2	2
Li	2012	2010	67	67.45	10.59	0.75	1	2	1
Yao	2012	2010	92	70.63	10.80	0.24	2	2	1
Mao	2013	2011	345	72.17	8.85	0.14	3	2	0
Li	2013	2011	246	76.30	NA	0.54	2	2	2
Liu	2013	2011	171	78.15	10.97	NA	2	2	2
Zhou	2013	2011	90	83.05	11.44	0.48	2	1	2
Dai	2013	2011	511	69.93	15.16	0.32	3	2	1
Zhang	2013	2011	328	80.12	17.66	0.41	1	2	1
Mai	2013	2011	252	78.92	12.84	0.52	2	1	1
Liu	2013	2011	299	79.40	8.15	0.66	3	1	1
Li	2014	2012	504	79.90	12.28	0.51	1	2	2
Zhang	2014	2012	121	79.26	8.84	NA	2	2	2
Zhang	2014	2012	31	77.68	9.33	NA	2	2	2
Li	2014	2012	186	81.20	14.08	0.55	2	2	1
Tan	2015	2013	137	78.57	13.02	0.32	3	2	1
Tian	2015	2013	285	79.74	12.24	0.56	1	2	2
Chen	2015	2013	182	72.26	13.21	0.30	3	2	1
Wang	2016	2014	34	79.94	10.07	NA	3	1	1
Chen	2016	2014	186	70.94	8.91	0.54	2	1	2
Han	2016	2014	232	71.36	9.67	0.50	3	1	1
Cao	2016	2014	96	85.46	14.22	0.42	2	1	2
Han	2016	2014	467	71.94	10.33	0.57	1	3	1
Gong	2016	2014	60	78.63	NA	NA	1	3	2
Wang	2016	2014	312	75.19	15.45	0.52	2	1	2
Guo	2016	2014	316	71.82	13.50	0.32	1	2	1
Song	2016	2014	297	65.57	11.40	0.34	3	1	1
Yao	2017	2015	58	82.29	12.24	NA	2	1	1
Tan	2017	2015	205	70.35	14.63	0.37	3	3	1
First author	Publish year	Collect year	Sample size	M	SD	Male proportion	Journal type	Region	Study phase
Li	2017	2015	308	72.88	8.91	0.38	3	3	1
Liang	2017	2015	303	74.84	13.02	0.34	2	0	2
Zhang	2017	2015	651	74.42	11.69	0.31	2	1	1
Ren	2017	2015	275	73.03	13.24	0.20	3	4	1
Ning	2017	2015	312	75.72	12.59	0.25	3	4	1
Guo	2017	2015	434	75.65	15.69	0.25	2	2	1
Tang	2017	2015	283	73.40	13.66	0.36	3	2	1
Li	2018	2016	232	65.03	14.02	0.55	3	3	1
Zhang	2019	2017	176	74.80	13.89	0.13	3	2	1
Qian	2019	2017	300	79.85	NA	0.25	1	1	2
Su	2019	2017	276	81.70	13.57	0.52	2	0	1
Wang	2019	2017	228	74.36	14.27	0.34	3	1	1
Luo	2020	2018	100	71.07	5.87	0.44	2	3	1
Qin	2020	2019	173	72.00	14.62	0.09	2	3	0

First author	Publish year	Collect year	Sample size	M	SD	Male proportion	Journal type	Region	Study phase
Pan	2004	2002	410	77.55	11.43	0.41	3	1	1
Su	2005	2003	131	85.52	11.10	0.31	2	0	1
Wang	2007	2005	61	76.62	13.66	NA	1	1	1
Mao	2007	2005	279	80.79	15.00	0.58	1	2	2
Zhou	2008	2006	724	80.58	12.29	0.42	2	2	2
Sun	2010	2008	365	76.95	13.11	0.52	2	3	1
Liang	2010	2008	648	76.71	9.46	0.45	1	3	1
Xian	2011	2009	363	76.26	9.90	0.39	1	4	1
Wang	2011	2009	92	77.82	9.81	NA	1	3	1
Yang	2012	2010	366	75.64	NA	NA	1	2	2
Li	2012	2010	67	67.45	10.59	0.75	1	2	1
Yao	2012	2010	92	70.63	10.80	0.24	2	2	1
Mao	2013	2011	345	72.17	8.85	0.14	3	2	0
Li	2013	2011	246	76.30	NA	0.54	2	2	2
Liu	2013	2011	171	78.15	10.97	NA	2	2	2
Zhou	2013	2011	90	83.05	11.44	0.48	2	1	2
Dai	2013	2011	511	69.93	15.16	0.32	3	2	1
Zhang	2013	2011	328	80.12	17.66	0.41	1	2	1
Mai	2013	2011	252	78.92	12.84	0.52	2	1	1
Liu	2013	2011	299	79.40	8.15	0.66	3	1	1
Li	2014	2012	504	79.90	12.28	0.51	1	2	2
Zhang	2014	2012	121	79.26	8.84	NA	2	2	2
Zhang	2014	2012	31	77.68	9.33	NA	2	2	2
Li	2014	2012	186	81.20	14.08	0.55	2	2	1
Tan	2015	2013	137	78.57	13.02	0.32	3	2	1
Tian	2015	2013	285	79.74	12.24	0.56	1	2	2
Chen	2015	2013	182	72.26	13.21	0.30	3	2	1
Wang	2016	2014	34	79.94	10.07	NA	3	1	1
Chen	2016	2014	186	70.94	8.91	0.54	2	1	2
Han	2016	2014	232	71.36	9.67	0.50	3	1	1
Cao	2016	2014	96	85.46	14.22	0.42	2	1	2
Han	2016	2014	467	71.94	10.33	0.57	1	3	1
Gong	2016	2014	60	78.63	NA	NA	1	3	2
Wang	2016	2014	312	75.19	15.45	0.52	2	1	2
Guo	2016	2014	316	71.82	13.50	0.32	1	2	1
Song	2016	2014	297	65.57	11.40	0.34	3	1	1
Yao	2017	2015	58	82.29	12.24	NA	2	1	1
Tan	2017	2015	205	70.35	14.63	0.37	3	3	1
First author	Publish year	Collect year	Sample size	M	SD	Male proportion	Journal type	Region	Study phase
Li	2017	2015	308	72.88	8.91	0.38	3	3	1
Liang	2017	2015	303	74.84	13.02	0.34	2	0	2
Zhang	2017	2015	651	74.42	11.69	0.31	2	1	1
Ren	2017	2015	275	73.03	13.24	0.20	3	4	1
Ning	2017	2015	312	75.72	12.59	0.25	3	4	1
Guo	2017	2015	434	75.65	15.69	0.25	2	2	1
Tang	2017	2015	283	73.40	13.66	0.36	3	2	1
Li	2018	2016	232	65.03	14.02	0.55	3	3	1
Zhang	2019	2017	176	74.80	13.89	0.13	3	2	1
Qian	2019	2017	300	79.85	NA	0.25	1	1	2
Su	2019	2017	276	81.70	13.57	0.52	2	0	1
Wang	2019	2017	228	74.36	14.27	0.34	3	1	1
Luo	2020	2018	100	71.07	5.87	0.44	2	3	1
Qin	2020	2019	173	72.00	14.62	0.09	2	3	0

Social indicators	actual year		one year prior		Three years prior		Five years prior
Social indicators	β	R²	β	R²	β	R²	β	R²
Socio-economic conditions
House price	-0.37^**	0.14	-0.39^**	0.15	-0.40^**	0.16	-0.39^**	0.15
Old-age dependency ratio	-0.34^*	0.12	-0.35^*	0.12	-0.35^*	0.12	-0.35^**	0.13
Consumption level	-0.37^**	0.14	-0.37^**	0.14	-0.39^**	0.15	-0.33^*	0.11
Education funds	-0.38^**	0.14	-0.37^**	0.14	-0.41^**	0.17	-0.37^*	0.14
Social connectedness
Divorce rate	-0.38^**	0.15	-0.40^**	0.16	-0.39^**	0.16	-0.38^**	0.14
Family size	0.25	0.06	0.36^**	0.13	0.42^**	0.18	0.41^**	0.17
Urbanization level	-0.38^**	0.15	-0.38^**	0.15	-0.41^**	0.17	-0.37^**	0.14
Social threat
Crime rate	-0.38^**	0.15	-0.42^**	0.18	-0.34^*	0.12	-0.34^*	0.12