大五人格問卷(BFI-44)信度元分析
——基于信度概化方法

黎紅艷 徐建平 陳基越 范業鑫,2

(1北京師范大學心理學院, 應用實驗心理北京市重點實驗室, 北京 100875)(2首都醫科大學宣武醫院, 北京 100503)

1 引言

大五人格問卷(Big Five Inventory, BFI-44)自1991年開發以來, 得到了研究者們的持續關注。在其基礎上, 相繼產生了多種不同語言的版本和修訂版, 并被廣泛應用于教育、臨床、家庭咨詢、組織行為等研究領域(Blüml, Kapusta, Doering,Br?hler, Wagner, & Kersting, 2013; Gerend, Aiken,& West, 2004; Gonzaga, Campos, & Bradbury,2007; Koh et al., 2014; McAbee & Oswald, 2013;Zaidi, Wajid, Zaidi, Zaidi, & Zaidi,2013)。

1.1 BF I的理論基礎及發展

BFI是以 Goldberg (1981)提出的“大五” (Big Five)人格結構為理論基礎發展出來的人格測驗。有研究者發現, 很多人格特質只能通過形容詞進行描述, 大約有1715個形容詞能清晰的表示出人格的原型(Prototype) (Angleitner, Ostendorf, &John, 1990)。John等人通過因素分析, 從這1715個表示人格原型的形容詞中選出了“大五”各維度中因素載荷最高的形容詞(John & Srivastava,1999), 并采用詞匯學取向的“大五”人格理論構建BFI。但是, 為了詳盡描述人格特質, 提高作答一致性, 編制者在每道題目中選用了 1～2個最能表現大五人格結構的人格描述形容詞, 并增加了對形容詞描述或說明性的信息, 因而每道題目被編制成一個短語而非詞匯。例如, 開放性維度中的特質詞匯“獨創的” (original), 在 BFI中被編制為“具有獨創性, 會產生新點子” (is original, comes up with new ideas); 盡責性維度中的特質詞匯“堅持不懈的” (persevering), 在BFI中被編制為“堅持到任務完成” (perseveres until the task is finished)(John, Naumann, & Soto, 2008)。最初, BFI有BFI-44和BFI-54兩個版本, 但是BFI-54中有10道題目計分不便, 現在已基本不再使用; 研究者公開發表的測驗為 BFI-44 (John, Donahue, &Kentle,1991; John et al., 2008)。

隨著BFI-44研究需求的增加, 也為了在國際上廣泛應用且便于跨文化研究比較, 各國研究者在BFI-44原版的基礎上, 先后修訂并產生了德、法、荷、韓、意、匈、挪等 7種語言的版本, 并有相關的研究文獻發表 (Denissen, Geenen, van Aken, Gosling, & Potter, 2008; Engvik & F?llesdal,2005; Farkas & Orosz, 2013; Fossati, Borroni,Marchione, & Maffei, 2011; Kim et al., 2010; Lang,Lüdtke, & Asendorpf, 2001; Plaisant, Srivastava,Mendelsohn, Debray, & John, 2005)。在伯克利人格實驗室官方網站(http://www.ocf.berkeley.edu/～johnlab/bfi.htm), 除了以上這些語言的版本, 還有中、立、瑞三種語言版本。其中, BFI-44中文版測驗題目可見 http://www.ocf.berkeley.edu/～johnlab/pdfs/BFI-Chinese.pdf。在BFI-44研究與使用過程中, 研究者還相繼修訂開發出了BFI-25、BFI-S、BFI-K、BFI-10、BFI-20五個簡版BFI測驗(Engvik& Clausen, 2011; Gerlitz & Schupp, 2005; John et al., 1991; Rammstedt &John, 2005; Rammstedt &John, 2007)。目前, BFI多個測驗版本中使用最為廣泛的是BFI-44。

1.2 問題提出

不同語言版本的 BFI-44在各個國家的廣泛應用中, 研究者發現測驗的信度水平會隨著施測樣本的變化而變化, 但只有少數研究者探究了其跨樣本時的信度穩定性。例如, 有研究者將 28種語言的BFI-44在56個國家的18,378名被試中進行了施測,發現各維度的α系數處于 0.76～0.79之間(Schmitt,Allik, McCrae, & Benet-Martínez, 2007)。此外, 還有研究者探究了BFI-44在55個國家不同性別的差異,其平均α系數為 0.72(Schmitt, Realo, Voracek, &Allik, 2008)。但大多數研究只提供了研究中單一樣本的α系數, 沒有考慮到測驗的信度水平在不同樣本中具有變異性。因此, 很有必要對已有文獻中使用的BFI-44測驗信度進行元分析, 為BFI-44使用者提供一個有代表性的α系數參考值和范圍。

信度是心理測量學的基本概念, 指測驗的可靠程度, 它表現為測驗結果的一貫性、一致性和穩定性。信度是反映測驗結果受到隨機誤差影響程度的指標, 是評價測驗質量的最基本的指標之一(Guttman, 1945; 張力為, 2002)。信度是效度的必要不充分條件, 一個測驗要有效度必須要有信度, 沒有信度就沒有效度。如果一個測驗測量的數據不準確, 就不能有效地解釋和說明所研究的現象。由于對一個測驗進行多次施測時, 信度不是測驗工具固有不變的屬性, 它會隨著施測條件而變化, 在具體應用中, 它指的是測驗結果的可靠程度。針對信度的可變性, Vacha-Haas (1998)提出了“信度概化” (reliability generalization)的概念,并用這種概化理論思想來指導信度的元分析技術。信度概化的目的是確定某一測驗工具在不同研究中α系數的變化范圍, 該測驗工具信度的變異性, 以及影響測驗信度水平的變量(Vacha-Haas,1998)。有研究者指出, 信度概化已經成為對測驗α系數進行元分析的主要方法之一(Rodriguez &Maeda, 2006)。它將已有研究中的α系數作為研究樣本, 通過描述統計、回歸分析等方法, 探究影響α系數變異的預測源, 分析它們為什么會對α系數有影響以及如何影響, 為研究者在今后的研究中使用BFI-44時提供參考, 注意平衡自己的研究需求與α系數變異預測源之間的關系, 并為后來測驗的使用者提供一些建議。本研究將采用一種最新的信度概化技術(Rodriguez & Maeda, 2006)對BFI-44的信度進行元分析。

2 研究方法

2.1 文獻來源及篩選步驟

檢索了包含Proquest系列在內的共計17個數據庫中自1991年1月1日至2014年4月4日共24年來有關BFI的學術期刊文獻和書籍。(1)標題查找。在數據檢索的“標題”欄中輸入關鍵詞“Big Five Inventory”或簡寫 “BFI”, 查詢到文獻 20 篇。(2)摘要查找。在數據庫檢索“摘要”欄中輸入關鍵詞“Big Five Inventory”或“BFI”, 并在“引用作者”一欄中輸入“John, Donahue & Kentle”, 去掉重復文獻后, 查到文獻165篇, 其中1991～2009年間共67篇, 2010年至今共98篇。(3)全文查找。在數據庫檢索“全文”欄中輸入關鍵詞“Big Five Inventory”,刪除與前兩種查找方法重復的文獻后, 共收集到571篇文獻, 其中1991～2009年間共230篇, 2010年至今共341篇。三種查詢方法查詢到1991年至今有關BFI的學術期刊文獻、書籍共計756篇。

在 CNKI數據庫中, 使用關鍵詞“Big Five Inventory”在“標題”或“英文摘要”或“全文”或“參考文獻”欄中搜索, 共查找到26篇中文文獻。

總共查找中、英文文獻782篇。其中, 有129篇報告了研究中 BFI-44各維度的α系數, 有 85篇除報告了各維度的α系數, 還報告了被試樣本量、被試國籍、測驗語言版本、被試平均年齡、男女比例(通過計算獲得)等人口學變量信息。在這85篇文獻中, 部分論文包括了多個子研究, 共計包括110個樣本。本研究最終用于對BFI-44 的α系數進行元分析以及研究α系數變異的預測源的85篇文獻都是英文文獻, 大多數發表在“Journal of personality and social psychology(IF: 5.51),Journal of personality(IF: 2.94)Personality and Individual Differences(IF: 1.88)”, 其文章引用率和期刊在專業領域的影響力都比較高。

以往的研究一般都會對影響α系數變異最重要的樣本特定因素進行編碼。Vacha-Haase (1998)對《貝姆性別量表》(BSRI)的α系數元分析中, 考察了樣本量、測驗類型、測驗語言版本、國籍等變量對測驗α系數的影響。有研究者利用信度概化方法對《工作倦怠量表》的α系數進行元分析時, 探究了樣本量、測驗語言版本、被試的職業、國籍等變量對α系數的影響(Wheeler, Vassar,Worley, & Barnes, 2011)。還有研究者選取樣本量、中國南北區域差異、男女比例、平均年齡、健康類型等作為MMPI問卷各分量表α系數元分析的預測變量(焦璨, 張潔婷, 吳利, 張敏強, 2010)。在本研究涉及到的 110個研究樣本中, 可選擇的預測變量有種族、樣本量、被試國籍、測驗語言版本、被試平均年齡、交往時間、工齡、男女數量等變量。其中, 樣本量、被試國籍、測驗語言版本、平均年齡、男女比例(通過計算獲得)在 110個研究樣本中信息完整。因此, 本研究中把這 5個變量作為考察BFI-44信度水平的預測變量。

在 5個變量中, 被試樣本量、平均年齡、男女比例為連續變量; 被試國籍和測驗語言版本為分類變量, 對其進行虛無編碼。由于BFI-44最先由美國的研究者以英語修訂發表, 因此本研究將被試國籍編碼為美國(1)、非美國(0)兩類, 測驗語言版本相應編碼分為英語(1)、非英語(0)。

3 研究結果

3.1 BF I各維度的代表性信度水平

Rodriguez和 Maeda (2006)認為,α系數會隨著樣本的變化而變化, 但先前的信度元分析沒有涉及到α系數的抽樣分布(Vacha-Haase, 1998;Vacha-Haase, Kogan, Tani, & Woodall, 2001)。于是,他們對Vacha-Haase的信度概化方法進行了改進,運用樣本量加權方法和T轉換加權方法, 使信度估計更準確。其中,T轉換是一個假設檢驗的過程,提出虛無假設H0是“所有樣本中BFI-44各維度的α系數沒有顯著差異”。通常, 先采用Q檢驗來對該假設進行驗證。然后, 將各個研究樣本的α系數采用公式轉換成本研究選用了 85篇文獻中的110個樣本α系數的算術平均數、樣本量加權平均數和T轉換加權平均數進行計算。轉換公式及Q檢驗公式為：

表1 BF I-44各維度α系數的各類平均數

三種算法中, BFI-44問卷E維度的α系數處于0.824～0.855間, A維度處于0.745～0.794間, C維度處于0.792～0.823間, N維度處于0.813～0.833間, O維度處于0.788～0.796間。各維度的α系數都接近或超過0.8, 其中樣本量加權平均數和T轉換加權平均數兩種算法的結果比較相似。除開放性維度外, 其他維度T轉換加權計算的平均數都比采用另兩種算法得到的數值高。

五個分維度Q檢驗結果為：QE(109) = 3579.601,QA(109) = 2242.416,QC(109) = 2150.65,QN(109) =1918.299,QO(109) = 1860.496, 各維度的Q檢驗都達到顯著水平(p<0.0001)。說明樣本中各維度的α系數差異顯著。

3.2 BF I各維度α系數變異的預測源

以T轉換量為因變量,wi為權重, 進行加權最小二乘回歸分析, 探究BFI-44信度系數變異的預測源(Rodriguez & Maeda, 2006)。結果如表2所示。

表2結果顯示, 樣本量對BFI量表中的A、C、N和O維度的α系數有影響,ΔR2分別為19.2%、4%、8.5%、15%。其中, 樣本量對 A、C起正向預測作用, 對N、O起負向預測作用。國籍對E、A、C維度α系數起正向預測作用,ΔR2分別為10.5%、20.5%、15.6%。男女比例對E、C、O維度α系數有影響,ΔR2分別為10.3%、20%、6.4%,其中, 男女比例對E、O維度的α系數起正向預測作用, 對 C維度起負向預測作用。測驗的語言版本和被試的平均年齡對各維度的α系數影響沒有達到顯著水平。

表2 BF I-44各維度α系數回歸分析表

4 討論

從元分析結果可知, 在各個國家的 110個樣本研究中, BFI-44各分量表的α系數介于0.745～0.855間。通常, 人格量表的信度比智力測驗要低,α系數不低于0.6即可接受(戴海琦, 張峰, 陳雪楓,2011)。研究表明 BFI-44在國籍、語言版本、樣本量、被試平均年齡、男女比例等不同情境中的應用是穩定的。在國內發表的26篇文獻中, 只有4篇完整地報告了各維度的信度, 很多研究則犯了“信度引入” (reliability induction)的錯誤, 在自己的研究中報告的是前人研究中測驗的信度, 缺少自己研究樣本施測數據的信度值, 把前人的研究結果作為判斷測驗質量的依據。國內其余的研究, 甚至沒有對其信度做任何描述, 這在一定程度上阻礙了對國內研究中所使用的測驗進行信度概化研究, 影響了測驗可靠性和有效性的進一步提升(焦璨等, 2010)。在今后研究中, 研究者應意識到“信度引入”的錯誤所在, 并能夠有意識地完整報告自己研究中使用的測驗施測數據的信度系數。

在選取的 5個預測源中, 樣本量、國籍、男女比例對不同維度的α系數均有影響, 而測驗語言和平均年齡對各維度的α系數均沒有影響。在A、C維度中, 樣本量越大,α系數越高; 而在N、O維度中,α系數則隨著樣本量增大而減小。這可能是由于樣本選取方法不科學導致分數出現偏態分布。例如, 用于本研究元分析的樣本中, 很多研究都采取方便取樣, 樣本缺乏代表性, 或者在抽樣過程中沒有考慮到樣本的國籍、男女比例等人口學變量, 而這些變量都會對BFI-44不同維度的信度水平產生顯著影響。有研究選用1013名學生被試施測BFI-44, 其中男生占63%, 女生占37%,平均年齡21.88歲, 年齡標準差為0.74, 測驗的信度范圍處于 0.54～0.74間(Furnham, Nuygards, &Chamorro-Premuzic, 2013), 而Soh和Jacobs (2013)利用BFI-44對165名學生和在職人員施測時, 男女比例分別為42%和53%, 年齡跨度為18～59歲,測驗的信度范圍達到 0.76～0.87。以上說明, 有時簡單盲目地增加樣本量不僅不能提高測驗的信度水平, 反而會造成相反的結果, 因此, 應注意分層或分類抽樣。

結果顯示, 國籍對 BFI-44測驗的 E、A、C三維度α系數起正向預測作用。在美國實施的研究中,α系數高于其他國家研究的值, 因為BFI最先由美國的研究者開發而成, 在其他國家的樣本中應用施測時, 由于文化差異、不同地區的人所具有的某種穩定的人格特征不同, 問卷言語表達等因素會造成被試理解的偏差, 進而影響其信度水平。有研究者對 462名美國被試進行施測,BFI-44各維度的α系數為E (0.88)、A (0.79)、C(0.82)、N (0.84)、O (0.83), 均值為 0.83 (John &Srivastava, 1999)。John等人(2008)對829名美國和加拿大被試進行施測, BFI-44各維度的α系數為：E (0.86)、A (0.79)、C (0.82)、N (0.87)、O (0.83),均值為0.83。在美國和加拿大樣本中, BFI-44各維度的α系數介于0.75～0.90之間。而韓語版BFI-44在韓國人群中施測, 各維度的α系數為E (0.52)、A (0.61)、C (0.75)、N (0.71)、O (0.75), 均值為 0.67(Kim et al., 2010)。此外, 德語版各維度的α系數介于0.67～0.82之間(Lang et al., 2001), 明顯低于美國樣本。

男女比例變量會對BFI-44不同維度的α系數起不同的作用。在E、O維度中, 男性越多,α系數越高; 而在 C維度中, 女性越多,α系數越高,表明男女在人格結構中的差異也會影響測驗的α系數。有研究者利用 BFI-44測驗探究全世界 55個國家不同性別的被試在人格得分上的差異, 結果顯示很多國家的女性在神經質、外傾性、宜人性和盡責性等維度上的分數都高于男性(Schmitt et al., 2008)。此外, 有研究者發現, 女性在神經質和宜人性兩個維度中得分高于男性, 但其他三個維度得分與男性沒有明顯差異(Costa, Terracciano,& McCrae, 2001)。除神經質維度外, 男女比例對其他四個維度的影響并沒有形成一致的結果。

被試年齡對其BFI-44各維度的α系數沒有影響, 其結果與之前研究一致。Denissen 等人(2008)在荷蘭通過網絡邀請本國 6948名被試完成了BFI-44測驗, 年齡跨度從 10歲至 70歲, 經過多樣本分析發現, 被試在各個年齡段的得分差異不大, 且BFI-44結構很穩定。而本研究中語言版本對BFI-44各維度的α系數都沒有影響, 這一結果與前人研究不符, Caruso (2000)利用信度概化方法對NEO人格測驗α系數分析中發現, 英語和非英語版本的測驗對E、N、O三個維度的α系數有影響。這可能是因為本研究綜合了很多研究結果,整合了單一研究的差異。如有研究者利用英、德、中三種語言版本BFI測驗對三個國家被試施測時,德國樣本中有些維度的α系數高于美國被試(Gunkel, Schlaegel, Langella, & Peluchette, 2010)。該結果還有待于今后的研究者通過收集原始數據,進行進一步驗證。

比較 BFI-44與其簡版測驗, 結果表明,BFI-10與 BFI-44各維度的相關雖達到 0.7以上,但英語版和德語版的BFI-10對BFI-44的解釋率分別為 55%和 62%, 因此使用簡版問卷會存在一些隱患(Rammstedt & John, 2007)。同時, 有研究對不同長度版本的五因素人格測驗進行比較后發現, 測驗的信度水平隨測驗題目數量的增多而提高。使用題目數量過少的問卷, 會增加測驗結果犯一類錯誤和二類錯誤的概率, 進而對整個問卷的結果產生影響, 因此, 建議在施測時采用中等長度的問卷(Credé, Harms, Niehorster, & Gaye-Valentine, 2012)。

5 結論及應用建議

運用信度概化方法對85篇BFI-44英文文獻進行元分析后得出以下結論：

(1)用于信度概化分析的樣本間 BFI-44各維度的α系數差異顯著。

(2) BFI-44各維度的α系數均接近或高于0.8,其中E、N維度的α系數高于其他3個維度。

(3)被試樣本量、國籍、男女比例均對BFI-44測驗不同維度的α系數有影響。樣本量對 A、C維度的α系數起正向預測作用, 對N、O維度的α系數起負向預測作用; 國籍對E、A、C維度的α系數起正向預測作用; 男女比例對E、O維度的α系數起著正向預測作用, 對 C維度則起負向預測作用。測驗的語言版本和被試的平均年齡對各維度的α系數沒有顯著影響。

BFI-44語言版本多樣, 在世界范圍內應用廣泛, 各維度α系數均接近 0.8, 且該測驗僅由 44道形容詞短語題目構成, 簡短省時, 建議在國內推廣使用。使用時建議報告研究中測驗工具施測數據的信度水平, 并進一步考察其信效度。在使用中還應注意抽取被試的方法, 注意平衡地區差異、男女比例對其信度水平的影響。

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