Secondary Logo

Journal Logo


Development and Validation of the Postpartum Sleep Quality Scale

Yang, Chiu-Ling; Yu, Chen-Hsiang; Chen, Chung-Hey

Author Information
Journal of Nursing Research: June 2013 - Volume 21 - Issue 2 - p 148-154
doi: 10.1097/jnr.0b013e3182921f80
  • Free



Sleep is a basic human physiological need and complex physiological process essential in restoring physical agility and energy (Chen et al., 2010; Dijk & von Schantz, 2005; Ko, Chang, & Chen, 2010). Sleep quality is a critical factor affecting quality of life. Sleep disorders can cause tiredness, fatigue, daytime functional problems, and depression (Harmat, Takács, & Bódizs, 2008; Ko et al., 2010; Kung, Yang, Chiu, & Kuo, 2011; MunguiA-Izquierdo & Legaz-Arrese, 2012).

Researchers have reported that postpartum women experience less total sleep time, less sleep efficiency (time asleep vs. time in bed), and lower rapid eye movement than their non-postpartum peers (Dørheim, Bondevik, Eberhard-Gran, & Bjorvatn, 2009; Li, Chen, Li, Gau, & Huang, 2011; Posmontier, 2008). New mothers normally experience 20% more wake time during their first 6 postpartum weeks (Goyal, Gay, & Lee, 2007; Posmontier, 2008). The postpartum period is a transitional stage essential in restoring and promoting the health of new mothers (Ko & Chen, 2010; Zhang et al., 2007). However, it is a period often punctuated by physical and psychological symptoms resulting from sleep disturbance. Disturbances include physical discomfort, infant crying, disturbance by bed partners, and perceived stress, among others. Postpartum women thus face increased risk of depression (Bei, Milgrom, Ericksen, & Trinder, 2010; Dørheim et al., 2009; Eberhard-Gran, Tambs, Opjordsmoen, Skrondal, & Eskild, 2004; Munk-Olsen, Larsen, Pefersen, Mors, & Mortensen, 2006).

According to traditional Chinese medicine, pregnancy and childbirth cause a transient functional imbalance among major organs that disrupts a woman’s normal physical well-being (Tien, 2004). Chinese culture thus embraces a set of beliefs and practices referred to collectively as doing-the-month (zuo yuezi, that is, remaining largely inactive and confined during the first postnatal month). Adherence to the doing-the-month regimen is believed to help restore organs to a healthy balance (Cheung, 1997; Wang, Wang, & Wang, 2008). The regimen requires that postpartum women remain indoors, rest for 1 entire month, and follow many restrictive practices (Chien, Tai, Ko, Huang, & Sheu, 2006). Although many postpartum Taiwanese mothers follow some or most of the doing-the-month regimen, studies show that doing so does not ensure nocturnal sleep quality. Anecdotal studies have shown two to four major sleep disruptions (awakenings) to be common and nightly sleep duration the first postpartum month to range from less than 5 to 6.9 hours (Carty, Bradley, & Winslow, 1996; Huang, 2002; Lee, 2005; Quillin, 1997). This situation may inhibit physical and psychological recovery to health. Huang et al. (2004) and Hung (2006) reported that postpartum mothers identified insufficient sleep as the primary stressor during the early postpartum period. Huang (2002) classified most (95.4%) postpartum women in her study as “poor sleepers.” Mothers reported a perceived nightly sleep debt of approximately 3 hours during the early postpartum period.

Infants’ sleep patterns in the early stage may influence mothers’ sleep quality. Studies on newborn infant sleep have reported significantly different average sleep times. Quillin’s (1997) study of 44 four-week-old infants found an average sleep time of 13.9 hours per 24-hour period, with the number of nighttime awakenings averaging between 1 and 2 (1.57 ± 0.47). Yamazaki, Lee, Kennedy, and Weiss (2005) found an average daily sleep time for infants of 12.2 hours; Teng, See, Cheng, and Lee (2007) found an average of 2.61 ± 1.56 nighttime awakening at 1 month old, 1.93 ± 1.18 at 3 months old, and 1.85 ± 1.33 at 6 months old.

Although sleep quality is a readily accepted clinical construct, it is difficult to define and measure objectively (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). Most researchers have utilized subjective measures to assess sleep quality and sleep disturbances (Tsai et al., 2005). Self-rating questionnaires represent a cost-effective, easy-to-implement alternative to polysomnography and actigraphy, which objectively measure sleep.

In a concept analysis of sleep quality (Chiu & Chao, 2000), scales recognized as widely available and able to subjectively measure adult sleep included the Leeds Sleep Evaluation Questionnaire (Parrott & Hindmarch, 1980), Verran and Snyder-Halpern Sleep Scale (Snyder-Halpern & Verran, 1987), Medical Outcomes Study Sleep Questionnaire (Stewart & Ware, 1992), and Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989). The above scales assess between four and eight dimensions of sleep. Of these questionnaires, PSQI has been shown to be a highly reliable tool for evaluating sleep quality and sleep disturbance and has been extensively used in a variety of clinical populations (Tsai et al., 2005). The PSQI assesses sleep quality using seven dimensional scores that measure, respectively, subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, sleeping medication use, and daytime dysfunction.

Postpartum women need to experience physical and psychological adjustment to restore the status of body and mind and must also take care of their newborn babies. Therefore, postpartum sleep quality is a critical health index. According to the literature (Huang, 2002; Hunter, Rychnovsky, & Yount, 2009; Lee, 2005; Li et al., 2011, Teng et al., 2007), inadequate rest because of lack of sleep is a major source of stress for postpartum women. None of the aforementioned sleep scales address sleep issues unique to the physical–psychosocial adjustment and infant care conditions faced by postpartum women. Therefore, we aimed to develop and validate PSQS that uniquely measures sleep quality in postpartum women.


We used a cross-sectional design to develop and test the PSQS. The PSQS was developed and validated in two phases.

Phase 1: Developing the PSQS

The PSQS is in Chinese and was constructed using a review of the literature that focused particularly on postnatal women’s sleep problems and clinical practices. PSQS elements included quantitative aspects (e.g., sleep duration, sleep latency, number of arousals), subjective aspects (e.g., restfulness, daytime function; Buysse et al., 1989), and factors influencing postnatal women’s sleep quality. Five experts critiqued the PSQS for item clarity, relevance, and comprehensiveness (Grant & Davis, 1997), with four specializing in maternity nursing and one as a senior obstetrician. Three postnatal women assessed the face validity of the scale. On the basis of expert recommendations, four items were reworded and three new items were added including “disturbed by leg cramping,” “blue mood,” and “take medicine to help sleep.” We used the content validity index (CVI) described by Lynn (1986) to ensure consistency between study conceptualization and the measurement content domain. CVI evaluation results (CVI score = .97) indicated a high rate of agreement on PSQS items among experts.

The PSQS was revised based on expert recommendations and included 16 self-rated questions designed to assess postnatal women’s sleep quality during the past 2 weeks, with items scored on a 5-point Likert scale (0 = never, 1 = few, 2 = sometimes, 3 = often, 4 = almost always). A 5-day test–retest was used to assess scale stability, Cronbach’s alpha evaluated internal consistency, and two junior high school Chinese teachers assessed reading level appropriateness. Exploratory factor analysis (EFA) was used to examine construct validity and assessed PSQS convergent validity using the PSQI.

The PSQI, developed by Buysse et al. (1989), uses scores ranging from 0 (no difficulty) to 3 (severe difficulty) to measure subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for the seven components yields the global PSQI score (range = 0–21). Higher scores indicate poorer sleep quality.

Using a sample of “good” sleepers (healthy subjects, n = 52) and “poor” sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62), Buysse et al. (1989) found a Cronbach’s α of .83 for internal consistency and a 2-week test–retest correlation coefficient of 0.85. A global PSQI score higher than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% in distinguishing good and poor sleepers. Therefore, 5 was adopted as the cutoff, with a global PSQI score greater than 5 indicating poor sleep quality and less than or equal to 5 indicating good sleep quality. A Taiwan study conducted by Ko et al. (2010) on 300 pregnant and 300 non pregnant women supported the internal consistency of the Chinese-version PSQI, with a Cronbach’s α of .73.

Phase 2: Validating the PSQS

Participants and settings

After the study protocol was approved by the institutional review board, we recruited participants from the postnatal clinic of one medical center and one obstetric clinic in southern Taiwan. Data were collected from November 2010 to March 2011. Enrolled participants met the following criteria: (a) at least 18 years old and married, (b) delivery of a normal newborn, and (c) consent to participate. Postpartum women experiencing stillbirth were excluded. In factor analysis, a ratio of at least 10 subjects for each item is desirable to generalize from the sample to a wider population, and 100–200 subjects are enough for most purposes (Munro, 2005). For our validation, 202 postnatal women met the criteria and completed the PSQS.

Demographic data

A demographic form collected descriptive data from participants. This included age, number of children, employment status, socioeconomic status (SES), type of delivery, gender of the infant, prenatal complications, postnatal complications, premature delivery, household work burden (hours per day), and daytime nap habit (hours per day). The index of status was used to stratify family SES according to social status (Lin, 1978). Education and occupation data were combined into one nuclear family unit status score. The index classifies social status into levels I through V. In this study, levels I and II were categorized as high SES, level III as middle SES, and levels IV and V as low SES.

Data Analysis

We performed data analyses using SPSS for Windows 17.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics summarized sample characteristics and variables of interest. Data were expressed as mean ± SD for continuous variables and n (%) for categorical variables. Item analyses included calculations of item means, standard deviation, and item-to-total correlations. We considered internal consistency reliabilities of .70 or above as acceptable for this newly developed scale (DeVellis, 2003; Wu, Chin, Chen, Lai, & Tseng, 2011). We assessed PSQS test–retest reliability using intraclass correlation coefficient criteria over a 5-day time frame and PSQS construct validity using EFA. Criteria used were (a) a factor loading between .3 and .9, (b) an eigenvalue greater than 1 for each component, and (c) at least three items in each factor (Netemeyer, Bearden, & Sharma, 2003). A Pearson correlation coefficient was used to examine convergent validity with PSQI. All results were considered significant at p < .05.


Two hundred two participants completed the required scales. Table 1 shows participants’ demographic data. Participant mean age was 31.50 ± 4.28 years (range, 20–43 years), with most below the age of 35 years (77.7%). Most were employed (n = 126, 62.40%) and of high SES (n = 101, 50.00%), a majority experienced vaginal delivery (n = 136, 67.30%), slightly more than half the neonates were men (n = 110, 54.50%), and most experienced no prenatal complications (n = 187, 92.60%) or postnatal complications (n = 195, 96.50%). The household work burden of participants averaged 2.12 ± 1.17 hours per day during the previous 2-week period and daytime napping time averaged 1.85 ± 1.21 hours per day.

Participant Demographic and Clinical Characteristics (N = 202)

Item Analysis

Two Chinese language teachers reviewed the PSQS and determined that the scale was easily understood by respondents with a ninth grade or better reading level. Item-to-total correlations for the 16-item PSQS ranged from .21 to .67. Two items, “disturbed by leg cramping” and “take medicine to help sleep” were removed because item-total correlation coefficients for these two fell below the .3 threshold (Chiou, 2010).


The remaining 14 PSQS items all had an acceptable item-total correlation range of .32–.67. The alpha for each subscale was satisfactory and ranged from .71 to .81. The internal consistency of the total PSQS scale yielded a Cronbach’s alpha of .81, indicating good internal consistency. Intraclass correlation coefficient analysis gave 5-day test–retest reliability a score of .81 (n = 10), indicating acceptable PSQS stability.

Construct Validity

Two factors extracted from the 14-item PSQS are presented in Table 2 along with item-total correlations and factor loadings. After calculating a middling Kaiser-Meyer-Olkin value of 0.75 (χ2 = 917.41, p < .001) for the 14-item PSQS, we generated and defined these two factors using eigenvalues above 1.0 and screen plots. The factors were defined, respectively, as “Factor 1: Infant night care-related daytime dysfunction” and “Factor 2: Physical symptoms-related sleep inefficiency.” These two factors collectively explained 44.49% of total variance, with factor loadings ranging from .43 to .76.

Descriptive Statistics and Factor Loading for the PSQS

Convergent Validity

The PSQS correlated positively with the PSQI (r = .67, p < .001), supporting convergent validity.


On the basis of our study, it is evident that the 14-item PSQS is a reliable and valid instrument for assessing sleep quality in postpartum women. Internal consistency and test–retest reliability were both used to test scale reliability. The Cronbach alpha coefficient for homogeneity of the scale was .81, indicating a high degree of internal consistency. Burns and Grove (2005) suggested that instruments with slightly lower coefficients (.8–.9) could more richly reflect the fine discriminations in construct levels. The acceptable alpha coefficients (.71 and .81) for two subscales indicated that two strong factors were formed in PSQS, thus providing evidence of internal consistency reliability and supporting initial evidence of construct validity for a developing scale (Munro, 2005). Test–retest reliability used to examine consistency in repeated measures found a correlation coefficient of .81, which confirmed good instrument stability.

In addition, we verified the 14-item PSQS validity using the PSQI as our criterion. The correlation coefficient (r = .64) confirmed PSQS validity in measuring the sleep quality of postpartum women. In the absence of absolute validity evaluation criteria, we confirmed PSQS validity as an adequate instrument to measure sleep quality based on Chiou’s (2010) 0.6∼0.8 correlation coefficient range.

Factor analysis is an important statistical tool for confirming validity for the structure of instruments (Munro, 2005). Using EFA, two factors extracted from the PSQS explained 44.49% of total variance, with factor loadings ranging from .43 to .76. The first factor “infant night care-related daytime dysfunction” showed how taking care of infants at night affected the postpartum woman’s sleep quality and competency to manage daytime activities. This result echoes the findings of several other studies of poor sleep quality in postpartum women (Dørheim et al., 2009; Hunter et al., 2009; Teng et al., 2007). Taking care of infants during the night disrupts and fragments the sleep cycle of postpartum women and degrades overall sleep quality. The second factor “physical symptoms-related sleep inefficiency” addresses the woman’s physiological interference factors affecting sleep and sleep inefficiency symptoms. Previous studies that used the PSQI to investigate postpartum sleep quality found that most postpartum women exhibit poor sleep quality (Hedman, Pohjasvaara, Tolonen, Suhonen-Malm, & Myllylä, 2002; Huang, Carter, & Guo, 2004). Because previous research could not determine the unique effect of taking care of infants on postpartum sleep quality, we recommend using the newly developed 14-item PSQS to evaluate postpartum sleep quality because of its specific and comprehensive focus on postpartum women.

This study verified the 14-item PSQS as reliable and valid. The PSQS is primarily intended to measure postnatal women’s sleep quality and is not intended to provide accurate clinical diagnoses. The developed scale provides to health personnel a tool to quickly and completely evaluate sleep quality in postpartum women. Also, individual needs highlighted in the scale can assist healthcare professionals to provide proper health education to their postpartum clients, direct future research on postpartum sleep quality, and inspire the development of innovative intervention protocols to improve postpartum sleep quality. This study also found low (<4%) use of sleep-enhancing medications among participants, which may reflect participant concern that doing so would affect breastfeeding and fetal health.

Although considerable efforts were made to ensure design soundness, this study had several limitations. First, it is possible that some participants who met the sample selection criteria and exhibited heterogeneity with the sample were not recruited because of their location outside targeted institutions. Second, the use of convenience sampling may have recruited subjects who were atypical of the general population with regard to measured variables. Most participants were of moderate to high SES and thus likely represented a significantly higher SES-range sample than the average of all postpartum women in Taiwan. The PSQS is primarily intended to measure women’s sleep quality during postpartum and is not intended to provide accurate clinical diagnoses. Future research could consider defining an appropriate cutoff PSQS value to delineate good and poor sleepers.

In conclusion, we recommend the use of the developed 14-item PSQS in future studies. The scale can contribute to nursing and academic knowledge on the sleep quality of postpartum women by enriching the body of empirical data available. Adequate psychometric qualities in terms of internal consistency, 5-day test–retest reliability, content validity, construct validity, and convergent validity show PSQS as an effective instrument for measuring sleep quality in Taiwanese postpartum women. PSQS may be a valuable tool to assess the efficacy of intervention protocols designed to improve sleep quality. However, continued evaluation is required to verify instrument applicability in different ethnic and cultural settings.


We would like to thank the National Science Council of Taiwan for funding this study and the women who participated in the study.


Bei B., Milgrom J., Ericksen J., Trinder J. (2010). Subjective perception of sleep, but not its objective quality, is associated with immediate postpartum mood disturbances in healthy women. Sleep, 33 (4), 531–538.
Burns N., Grove S. K. (2005). The practice of nursing research. Conduct, critique & utilization (5th ed.). Philadelphia, PA: W. B. Saunders.
Buysse D. J., Reynolds C. F., Monk T. H., Berman S. R., Kupfer D. J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28 (2), 193–213. doi:10.1016/0165-1781(89)90047-4
Carty E. M., Bradley C., Winslow W. (1996). Women’s perceptions of fatigue during pregnancy and postpartum: The impact of length of hospital stay. Clinical Nursing Research, 5 (1), 67–80. doi:10.1177/105477389600500106
Chen K. M., Chen M. H., Lin M. H., Fan J. T., Lin H. S., Li C. H. (2010). Effects of yoga on sleep quality and depression in elders in assisted living facilities. The Journal of Nursing Research, 18 (1), 53–61. doi:10.1097/JNR.0b013e3181ce5189
Cheung N. F. (1997). Chinese zuo yuezi (sitting in for the first month of the postnatal period) in Scotland. Midwifery, 13 (2), 55–65. doi:10.1016/S0266-6138(97)90057-7
Chien L. Y., Tai C. J., Ko Y. L., Huang C. H., Sheu S. J. (2006). Adherence to “doing-the-month” practices is associated with fewer physical and depressive symptoms among postpartum women in Taiwan. Research in Nursing & Health, 29 (5), 374–383. doi:10.1002/nur.20154
Chiou H. J. (2010). Quantitative research and statistical analysis. Taipei City, Taiwan, ROC: Wu-Nan Books.
Chiu H. Y., Chao Y. F. C. (2010). Concept analysis: Sleep quality. The Journal of Nursing, 57 (4), 106–111. (Original work published in Chinese)
DeVellis R. F. (2003). Scale development: Theory and applications. London, England: Sage.
Dijk D. J., von Schantz M. (2005). Timing and consolidation of human sleep, wakefulness, and performance by a symphony of oscillators. Journal of Biological Rhythms, 20 (4), 279–290. doi:10.1177/0748730405278292
Dørheim S. K., Bondevik G. T., Eberhard-Gran M., Bjorvatn B. (2009). Sleep and depression in postpartum women: A population-based study. Sleep, 32 (7), 847–855.
Eberhard-Gran M., Tambs K., Opjordsmoen S., Skrondal A., Eskild A. (2004). Depression during pregnancy and after delivery: A repeated measurement study. Journal of Psychosomatic Obstetrics & Gynecology, 25 (1), 15–21. doi:10.1080/01674820410001737405
Goyal D., Gay C. L., Lee K. A. (2007). Patterns of sleep disruption and depressive symptoms in new mothers. The Journal of Perinatal & Neonatal Nursing, 21 (2), 123–129. doi:10.1097/01.JPN.0000270629.58746.96
Grant J. S., Davis L. L. (1997). Selection and use of content experts for instrument development. Research in Nursing & Health, 20 (3), 269–274. doi:10.1002/(SICI)1098-240X(199706)20:3<269::AID-NUR9>3.0.CO;2-G
Harmat L., Takács J., Bódizs R. (2008). Music improves sleep quality in students. Journal of Advanced Nursing, 62 (3), 327–335. doi:10.1111/j.1365-2648.2008.04602.x
Hedman C., Pohjasvaara T., Tolonen U., Suhonen-Malm A. S., Myllylä V. V. (2002). Effects of pregnancy on mothers’ sleep. Sleep Medicine, 3 (1), 37–42. doi:10.1016/S1389-9457(01)00130-7
Huang C. H. (2002). Sleep and sleepiness in first-mothers during early postpartum in Taiwan (Unpublished doctoral dissertation). University of Texas at Austin, TX.
Huang C. H., Carter P. A., Guo J. L. (2004). A comparison of sleep and daytime sleepiness in depressed and non-depressed mothers during the early postpartum period. The Journal of Nursing Research, 12 (4), 287–296. doi:10.1097/
Hung C. H. (2006). Correlates of first-time mothers’ postpartum stress. The Kaohsiung Journal of Medical Sciences, 22 (10), 500–507. doi:10.1016/S1607-551X(09)70344-4
Hunter L. P., Rychnovsky J. D., Yount S. M. (2009). A selective review of maternal sleep characteristics in the postpartum period. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 38 (1), 60–68. doi:10.1111/j.1552-6909.2008.00309.x
Ko S. H., Chang S. C., Chen C. H. (2010). A comparative study of sleep quality between pregnant and nonpregnant Taiwanese women. Journal of Nursing Scholarship, 42 (1), 23–30. doi:10.1111/j.1547-5069.2009.01326.x
Ko S. H., Chen C. H. (2010). Comparison of health-promoting lifestyles between postnatal Han Taiwanese and indigenous women. The Journal of Nursing Research, 18 (3), 191–198. doi:10.1097/JNR.0b013e3181edef18
Kung Y. Y., Yang C. C. H., Chiu J. H., Kuo T. B. J. (2011). The relationship of subjective sleep quality and cardiac autonomic nervous system in postmenopausal women with insomnia under auricular acupressure. Menopause, 18 (6), 638–645. doi:10.1097/gme.0b013e31820159c1
Lee H. L. (2005). Womens sleep quality, fatigue and depression during the 2nd and 4th postpartum weeks (Unpublished master’s thesis). National Taipei College of Nursing, Taiwan, ROC. (Original work published in Chinese)
Li C. Y., Chen S. C., Li C. Y., Gau M. L., Huang C. M. (2011). Randomised controlled trial of the effectiveness of using foot reflexology to improve quality of sleep amongst Taiwanese postpartum women. Midwifery, 27 (2), 181–186. doi:10.1016/j.midw.2009.04.005
Lin T. (1978). Psychiatry and society. Taipei City, Taiwan, ROC: Chi-Tsung. (Original work published in Chinese)
Lynn M. R. (1986). Determination and quantification of content validity. Nursing Research, 35 (6), 382–386. doi:10.1097/00006199-198611000-00017
MunguiA-Izquierdo D., Legaz-Arrese A. (2012). Determinants of sleep quality in middle-aged women with fibromyalgia syndrome. Journal of Sleep Research, 21 (1), 73–79. doi:10.1111/j.1365-2869.2011.00929.x
Munk-Olsen T., Laursen T. M., Pedersen C. B., Mors O., Mortensen P. B. (2006). New parents and mental disorders: A population-based register study. The Journal of the American Medical Association, 296 (21), 2582–2589. doi:10.1001/jama.296.21.2582
Munro B. H. (2005). Statistical methods for health care research (5th ed.). Philadelphia, PA: Lippincott Williams & Wilkins.
Netemeyer R. G., Bearden W. O., Sharma S. (2003) Scaling procedures: Issues and applications. London, England: Sage.
Parrott A. C., Hindmarch I. (1980). The Leeds Sleep Evaluation Questionnaire in psychopharmacological investigations—A review. Psychopharmacology, 71 (2), 173–179. doi:10.1007/BF00434408
Posmontier B. (2008). Sleep quality in women with and without postpartum depression. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 37 (6), 722–737. doi:10.1111/j.1552-6909.2008.00298.x
Quillin S. I. M. (1997). Infant and mother sleep patterns during 4th postpartum week. Issues in Comprehensive Pediatric Nursing, 20 (2), 115–123. doi:10.3109/01460869709026882
Snyder-Halpern R., Verran J. A. (1987). Instrumentation to describe subjective sleep characteristics in healthy subjects. Research in Nursing & Health, 10 (3), 155–163. doi:10.1002/nur.4770100307
Stewart A. L., Ware J. E. (1992). Measuring functioning and well-being: The medical outcomes study approach. Durham, NC: Duke University Press.
Teng F. L., See L. C., Cheng P. J., Lee J. T. (2007). The quality of sleep and its associated factors in the puerperium women. Chang Gung Nursing, 18 (4), 499–510. (Original work published in Chinese)
Tien S. F. (2004). Nurses’ knowledge of traditional Chinese postpartum customs. Western Journal of Nursing Research, 26 (7), 722–732. doi:10.1177/0193945904266541
Tsai P. S., Wang S. Y., Wang M. Y., Su C. T., Yang T. T., Huang C. J., Fang S. C. (2005). Psychometric evaluation of the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) in primary insomnia and control subjects. Quality of Life Research, 14 (8), 1943–1952. doi:10.1007/s11136-005-4346-x
Wang X., Wang Y., Wang J. (2008). A population-based survey of women’s traditional postpartum behaviors in Northern China. Midwifery, 24 (2), 238–245.
Wu L. M., Chin C. C., Chen C. H., Lai F. C., Tseng Y. Y. (2011). Development and validation of the paediatric cancer coping scale. Journal of Advanced Nursing, 67 (5), 1142–1151. doi:10.1111/j.1365-2648.2010.05567.x
Yamazaki A., Lee K. A., Kennedy H. P., Weiss S. J. (2005). Sleep-wake cycles, social rhythms, and sleeping arrangement during Japanese childbearing family transition. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 34 (3), 342–348. doi:10.1177/0884217505276156
Zhang J., Li F., Lin Y., Sheng Q., Yu X., Zhang X. (2007). Subjective sleep quality in perimenopausal women and its related factors. Journal of Nanjing Medical University, 21 (2), 116–119. doi:10.1016/S1007-4376(07)60028-8

women’s health; postnatal care; sleep quality

Copyright © 2013 by the Taiwan Nurses Association.