Validating a stage of change tool to predict employment outcomes.
Governments spend a significant proportion of their budget on reemployment and rehabilitation services to help unemployed citizens return to work. In Australia, the budget for 2016-17 was AU$6,861bn (Australian Government Departments of Social Services & Employment Budget, 2016), whilst the Obama administration spent over S270.5bn of the Federal budget in 2015 on Income Security, Welfare & Social Services (U.S. Bureau of Economic Analysis, 2016). Employment and rehabilitation services generally refer to unemployed citizens as "jobseekers" in the UK and Australia. Question: do all of these jobseekers actually want a job? Are they really jobseeking?
Whether a jobseeker is truly ready and willing to seek employment could be of critical importance to the cost-effectiveness of considerable sums of "public purse" expenditure. Yet there is a dearth of academic literature addressing this fundamental question. The UK House of Commons Work and Pensions Committee Report stated that, "Neil Couling, the Department of Work and Pensions' Director of Work Services, believed that a jobseeker classification tool which could accurately assess claimants' likelihood of long-term unemployment was the "holy grail" of employment support" (Begg, 2014, p. 9 Section 19).
The transtheoretical model (TTM), or stage of change model, is an empirically-based method of assessing individual's readiness to change behaviors (J. O. Prochaska & DiClemente, 1991). The researchers suggest that interventions to change behaviors are more effective when timed to that individual's "stage of change": their commitment to change. Such a premise could have compelling implications for informing more effective government-funded re-employment programs. To date the stage of change model has been adapted for very specific cohorts of unemployed participants (Gervey, 2010; Lam, Wiley, Siu, & Emmett, 2010; Mannock, Levesque, & Prochaska, 2002). This study adapts the model for general unemployed cohorts (both with and without a disability), in receipt of Australian government welfare payments (rather than work injury cover insurance), and for use on a considerably larger scale.
Prochaska and DiClemente developed the stage of change model to consider the underlying structure of behavior change, and the processes that individuals go through whilst changing (J. O. Prochaska & DiClemente, 1982) in order to address and somewhat formalize "the unprecedented pace at which new therapies are being placed on the market" (J. Prochaska & Coyle, 1979).
Probably the most obvious and direct implication of our research is the need to assess the stage of a client's readiness for change and to tailor interventions accordingly. We have determined that efficient self-change depends on doing the right things (processes) at the right time (stages). (J. O. Prochaska, DiClemente, & Norcross, 1992, p. 1110)
Several discreet stages of change or "clusters of intent" were identified, exhibited and self-reported by clients and therapy outpatients (DiClemente & Hughes, 1990; Lam, McMahon, Priddy, & Gehred-Schultz, 1988; McConnaughy, DiClemente, Prochaska, & Velicer, 1989; McConnaughy, Prochaska, & Velicer, 1983; J. O. Prochaska & DiClemente, 1982, 1991; J. O. Prochaska et al., 1992; J. O. Prochaska, DiClemente, & Norcross, 1993; J. O. Prochaska, DiClemente, Velicer, & Rossi, 1993). The description of stages has remained consistent since the initial publication of Prochaska, DiClemente and Norcross' 1993 paper, and may be directly applied to attitudes towards jobseeking.
G. K. Chesterton describes those in the precontemplation stage: "It isn't that they can't see the solution. It is that they can't see the problem" (Chesterton, 1935). There is no intention to change behavior, and if they present for interventions, it is often because of pressure from others. This "coercion" is a key concept relating to jobseekers that we shall address later in this paper. Precontemplation jobseekers may have no desire to attain a job, or no belief that they can find and sustain employment.
Contemplation jobseekers are aware that a problem exists, are seriously thinking about overcoming it, but have not yet committed to taking action. Employment service advisors have described contemptation jobseekers as follows: "They're "gonnas"--going to do something about it... maybe in six months' time. Manana." Contemplation jobseekers know that they should find employment, but they are not fully committed to taking action just yet.
Preparation jobseekers are intending to take action soon --perhaps in the next month--and may have unsuccessfully tried to make changes in the last year. They may have made some small reductions in their problem behavior and wish to take action. Preparation jobseekers might benefit from support and take an interest in activities such as good resume writing, interview skills, job search, perhaps even a vocational course.
Action individuals are committed to behavioral change and have successfully altered their behavior for between one day and six months. Prochaska and DiClemente argue that "People, including professionals, often equate action with change. As a consequence, they overlook the requisite work that prepares changes for action and the important efforts required to maintain the changes following action" (J. O. Prochaska, DiClemente, & Norcross, 1993, p. 1104). Relapse and recycling through the stages may occur, and that it often takes three to five attempts at action before clients become longterm "maintainers" (Norcross & Vangarelli, 1989; Schachter, 1982). Jobseekers taking action are undertaking job search, applying for positions in employment or full time education, and attending interviews etc.
When vocational counseling and rehabilitating clients with or without a disability back into employment, counsellors generally rely upon their experience, a client's personal history and clinical judgement to assess their clients' physical, practical and mental readiness to change (Bolton, Bellini, & Brookings, 2000; Strohmer & Leierer, 2000). However, it has been suggested that such judgement is prone to biases and errors, and has more of a focus upon negative issues (i.e. client barriers) over positive client factors (Spengler, Strohmer, & Prout, 1990; Strohmer & Leierer, 2000). As such "a valid assessment of clients' readiness to return to work would help counsellors to more effectively help their clients' transition to employment and independence." (Mannock, Levesque, & Prochaska, 2002)
Since the 1990s, studies of the TTM across various behaviors where change is desirable (such as for personal, health, social or economic reasons) have taken place. Results have been encouraging and many were summarized in the meta-analysis by Hall and Rossi across 48 health behaviors with almost 50,000 participants (Hall & Rossi, 2008; Marcus et al., 1998; J. O. Prochaska, Redding, Harlow, Rossi, & Velicer, 1994; J. O. Prochaska, Rossi, & Wilcox, 1991; J. O. Prochaska, Velicer, et al., 1994; Rakowski et al., 1998). The effectiveness of the TTM may be argued to involve an element of the "Hawthorne Effect" which suggests that counsellors might feel more enabled and positive towards their client due to their greater confidence in believing that they "understand" their client better (Houlihan, 1999). The primary aim of this study to validate a measure of jobseekers' genuine commitment to jobseeking. Can the 'University of Rhode Island Change Assessment--Vocational Counseling' (URICA-VC) be adapted to accurately ascertain the stage of change of general unemployed jobseekers on a much larger scale than previous studies? It aims to confirm whether a measure of jobseekers' stage of change does predict their likelihood of being in employment or remaining unemployed in 6-9 months' time, the "Holy Grail" of government welfare departments. (Begg, 2014)
Three papers have applied the TTM to unemployed adults: Lam et al., 2010 (n=149), Mannock et al., 2002 (n=155) and Gervey, 2010 (n=296). In all three studies, participants were clustered into categories of commitment to jobseeking (stages) in both studies utilizing either a 14 or 12-item questionnaire where participants rated their answers on a 5-option Likert scale. To generate survey items, Mannock et al. reviewed 96 client quotes from unemployed adults' case notes. Three senior rehabilitation counseling experts grouped the quotes into categories based upon the conceptual definitions of the stages of change and devised questions based upon those quotes. The counseling experts removed similar questions to eventually refine the URICA-VC survey to 12 questions. Gervey (2010) utilized the Mannock et al. question set with unemployed persons with mental illness. Similarly, the Lam Assessment on Stages of Employment Readiness (LASER) took 24 questions representing the key stages of change (taken from Prochaska & DiClemente's studies) and asked rehabilitation case managers to refine them, resulting in 14 items.
Mannock et al's URICA-VC measure showed that those assessed as being in the participative cluster (i.e. action stage of change) were three to four times (39%) more likely than other clusters (13%, reluctant/precontemplation and 10% reflective/contemplation) to have returned to work during the 13-month study period. The LASER survey indicated that 6 months after program exit, 25% of those assessed as mostly indifferent/precontemplation, 38% of those mostly ambivalent/contemplation and 56% of those in the readiness/action category had found competitive employment. Gervey applied the URICA-VC in a rehabilitation setting to 296 persons with mental illness, and confirmed a fourth cluster, preparation, from participants' relative scores across the three factors (precontemplation, contemplation and action). "Compared to the general population norm, this cluster group showed average T-scores on Pre-contemplation (M= 47.84) and Contemplation (M= 48.20), and moderately high scores on Action (M= 56.88)." (Gervey, 2010, p. 137)
The three studies are encouraging in suggesting the accuracy of a stage of change measure in predicting an individual's jobseeking commitment and likelihood of success. However, the three studies were very specific in their participant profile and all survey items could not be directly applied to general unemployed cohorts on a large scale, which was the focus of this study. Specifically, the URICA-VC focused upon those injured at work and who are attempting to return to work with the support of a rehabilitation counselor, whilst the LASER was almost entirely female (98.3%) and dominated by a single ethnicity (83% African-American). Thus, this study needed to amend a number of items to investigate the use of a contextualized form of the measure with general unemployed adult populations.
We utilized the URICA-VC 12 questions (Mannock et al., 2002) as a starting point for the items to be included in our survey, labelled the Psychological Assessment of Work Readiness (PAWR) for unemployed adults. As the URICA-VC questions are directed at adults unemployed due to injury at work and covered by insurance, a number of the questions were inappropriate for use with participants in countries who are receiving government social security/welfare payments. For example, one question refers to chances a financial "legal settlement" being affected by finding alternative employment. Consultation with 32 professional employment advisors from an employment services provider resulted in directly relevant alternatives which were then refined and agreement reached for an effective item. In the case of the above financially-pertinent, precontemplation question, "I believe that 1 might be worse off financially if I start employment" was used instead.
Examples of other items include: "I am really working hard to find a job" (an "action" question) and "I have started to consider my career and employment options" (a "contemplation" question). Dr. Prochaska and Dr. Levesque at the Pro-Change Behavior Systems Inc. were directly consulted to ensure that the amended items, selected by experienced employment consultants in the same manner as their original item generation process, would be appropriate and consistent with the scoring methodology.
As this was to be such a large scale study (over 1,000 participants) that might have an impact upon real jobseekers via commercial employment service companies, it was considered appropriate to undertake two small pilot studies to ensure ethical standards and the scalability of the survey. Initially 105 participants responded to the paper-based questionnaire when attending sessions with employment services providers in Queensland and Victoria, Australia. 47 participants were male, 46 female, and 12 did not indicate their gender. All were aged between 18 and 63 years old, and unemployed between 1 month and 30 years (mean = 41.74 months, standard deviation = 64.66 months).
In accordance with the URICA-VC developed by Mannock, Levesque and Janice Prochaska, employment services advisors manually reviewed completed questionnaires to ascertain the jobseeker's total "score" for each of the precontemplation, contemplation and action questions. These three scores were plotted on a graph and a line drawn to join the three dots. The four common 'patterns' formed by the graph determined which of the stages of change a client is in. For example, high precontemplation, low contemplation and low action scores indicate & precontemplation jobseeker.
Sample graphs for precontemplation, contemplation, preparation and action enabled advisors to compare their client's chart with the four "patterns" to enable an allocation of stage of jobseeking commitment to each jobseeker. Advisors recorded the completed survey scores and client's stage of change and posted surveys back to the researcher for double checking and compiling results. However, upon reviewing all scores and the employment advisors' interpretation, an issue became apparent. Advisors reported an average of 26 minutes for completion and scoring. This is an impractically long time for an employment services provider to incorporate into their operations as they usually only have 20-30 minutes for each jobseeker meeting and need to undertake many other activities.
A second pilot of the Psychological Assessment of Work Readiness survey involved 84 unemployed adults attending sessions with an advisor at a government-run employment organization in the United Kingdom. This second pilot aimed to determine whether a "public sector" environment impacted upon results. This pilot suggested three further issues: 1. Advisors misinterpreted 27 of the 84 surveys (32%). Following feedback, this seemed to be because of uncertainty when the result graphs did not form patterns as distinctive as suggested by the four model graphs. More highly-trained psychologists might have been able to interpret each answer and come to an overall conclusion on the correct "diagnosis" of readiness to change/work readiness. Additionally, they might have less susceptibility to bias. 2. 62% of clients were in the action stage of change, plus a further 15% in preparation. This is inconsistent with previous studies (Curtis, Gibbon, & Katsikitis, 2016; Lam et al., 2010; Mannock et al., 2002). It could indicate that jobseekers respond in a much more action-biased manner when sitting in a government environment, with advisors that have the power to remove their benefits if the jobseeker is not actively searching for employment. 3. 15% of jobseekers presented as scoring very highly in precontemplation as well as very highly in action. This is a contradictory score and there is no such pattern in the URICA-VC published scoring model.
The question of the contradictory action--precontemplation scores needed to be addressed. In reviewing responses, it appeared that some clients were genuinely conflicted in their answers. They might be applying for interviews and taking action-oriented steps, whilst other responses suggested that they lacked the belief, desire or confidence to obtain employment. We conjectured that this unusual profile might result from peer pressure into "going for jobs", or the threat of sanctions if they do not attempt to find employment. Dr. Levesque at Pro-Change Behavior Systems, Inc., and co-author of the Mannock et al paper, concurred with us, elaborating in email correspondence (April 2012) as follows:
"There's a relatively rare URICA profile, "Unreflective Action " that I've found among workers with a disability and in other populations I've studied using the URICA (e.g., domestic violence offenders, psychotherapy patients). Participants with an Unreflective Action profile score relatively high on Precontemplation and Action, and relatively low on Contemplation. They've either been coerced into taking action, or have leapt into action without doing enough preparatory work - e.g., without building knowledge and motivation that would be required to sustain change. For intervention purposes, I would praise them for the steps they are taking, but also deliver early-stage [precontemplation] interventions (raising awareness, increasing the pros, working on self-image, etc.)."
From discussion with employment consultants to the jobseekers that provided "unreflective action" responses, it became apparent that the jobseekers may be actually very reflective and thoughtful, but conflicted in taking action to obtain and sustain a job. Exactly as Dr. Levesque suggested, this seemed to be due to a lack of motivation, confidence and self-efficacy. As a result, and with such a significant proportion of the jobseekers appearing to be in this stage of change, we termed it "unauthentic action ".
It was apparent that electronic automation of the survey was necessary to facilitate its roll-out to a much larger participant sample and employment provider locations, as well as to remove the possibility of advisor bias/misinterpreting the stage of change chart. A highly-experienced database programmer created an online survey that reduced the scoring time from an average of 26 minutes to under 1 second and removed inconsistency in scoring by assessors with an accuracy of 100%. The resulting scoring algorithm allocated a stage to each of the 244,140,625 possible response strings (i.e. precontemplation, contemplation, preparation, action), including where contradictory high action and precontemplation scores existed (unauthentic action). The online survey also incorporated a section to record ethically-approved participant demographics (age, location, gender, months unemployed, jobseeker ID number. Despite this researcher's request, the participating Australian employment service providers did not consider ethnicity key data to record). The survey included an ethics-informed statement emphasizing that "answers will not impact your benefits payments", to help ensure that responses were more likely to be true and less likely to be impacted by the fear of "sanctions" from the government. (Sanctions include the removal of monetary and other welfare benefits.)
An Australian government-funded employment services provider was engaged to take part in the study. They had direct access to general unemployed adults including a variety of age, disability-status, length of unemployment and geographical locations. The provider had an interest in seeing if the PAWR survey might prove valid for jobseekers. If it did prove valid, the central hypothesis of the TTM (tailoring and timing interventions to a client's stage of change will result in more effective behavior change), would be extremely beneficial to employment service providers' aim of improving sustainable employment and education outcomes for their jobseekers.
Jobseekers visited the employment service offices every 2-4 weeks with the aim of receiving support in their efforts to re-enter the workforce. As such, questions and surveys are a familiar part of the employment advisor's intervention with their client. On their next visit, regardless of how long the individual had been unemployed, jobseekers were shown an ethics-approved Research Project Information Sheet, stressing that their responses will have no impact upon benefits payments. Jobseekers acknowledged consent to participate and completed the 12-item survey on a PC screen. Employment advisors were on hand to help jobseekers to complete the survey, in case of literacy issues. To help minimize bias in responses, advisors were warned not to complete the survey for the jobseeker, nor stand over their shoulder and watch jobseekers input answers. Advisors were group-trained during a one-hour workshop on the theory and ethical implementation of the survey.
The 1,213 adult participants were all from Queensland, Australia. The age range was 16-70 with a mean age of 33.4 years. 47.7% were female (578) and 52.3%male (635), indicating a very slightly higher percentage of males in the sample than the 2013 Queensland average for unemployed adults of 55.8% male, 44.2% female (ABS, 2014). The average length of unemployment was 19.75 months (1 year, 7 months, 23 days), with the range from 1 month to 26 years. 27.3% (331) of the sample were unemployed adults with a disability. Participant ethnicity data were not collected. No participants refused to take the survey, ostensibly because they are familiar with undertaking surveys as part of their session with their employment advisor.
Three Factor Solution - Exploratory Factor Analysis
To explore the presence of a 3-factor solution, a factor analysis using Maximum Likelihood extraction and Direct Oblimin rotation was explored on the dataset (n=l,213), with three factors fixed for extraction. We tested the assumptions of sphericity and sampling adequacy using Bartlett's test of sphericity and Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO). Bartlett's Test was significant ([[chi].sup.2]=5144.20, df=66, p<.001) and the KMO value of 0.88 indicates that a factor analysis is appropriate for the 12items. To support the extraction of 3-factors, eigenvalues, scree-plot and parallel analysis (see Table 1) were used as criteria for factor extraction. All criteria provided initial support for the 3-factor solution. A clear "elbow" is present at factor four, indicating that a three-factor solution is appropriate. As shown in Table 1, all sample eigenvalues were greater than randomly generated eigenvalues, using permutations of the raw dataset to create random eigenvalues.
From the factor loadings in Table 2, a three-factor solution was a good representation of the underlining factors of the PAWR. Using a cut-off factor loading of 0.3, all 12 items loaded on a single factor, forming a simple solution. The three extracted factors explained 47.61% of the total variation in the data, with all showing communalities >0.20. To further demonstrate the good fit of a 3-factor solution, a CFA was performed on the test dataset (n=l,213). Results of the CFA further indicated the 3-factor solution of the PAWR Assessment to be a good fit of the data: [[chi].sup.2](51)=246.01, p<.001, CFI=0.96, GFI=0.97,TLI= 0.95, RMSEA=0.06, pclose=.058.
Having generated the items and refined the process and administration, initial results indicate a high correlation between an individual's stage of change, as assessed by the PAWR survey, and their likelihood of re-entering employment or full time education. It is worth reiterating that the relative position of the three factors to each other determine five discreet stages of change, where preparation scores between action and contemplation, and unauthentic action shows a contradictory high score on both action and precontemplation.
Between March and May 2013, 1,213 jobseekers were assessed. The employment service provider was able to cross-reference the Jobseeker ID with a government database to establish which of the participants had returned to full time employment or education (the Australian Department of Employment's definition of an "outcome") by 30th November 2013, which was 6 to 9 months post-PAWR survey. The data demonstrate a correlation between work placement and education outcomes and a jobseeker's stage of change. Only 23% of precontemplation jobseekers were in employment/education 6-9 months after completing the PAWR survey. Employment/education outcomes increased to 31% amongst those in contemplation, 36% for unauthentic action jobseekers, 43% of preparation and 47% of action. Proportions of the sample in each stage of change were as follows: 29% of jobseekers in action; 20% in preparation, 23% in unauthentic action, 12% in contemplation and 15% in precontemplation. Overall, 49.7% indicated an earnest willingness to enter employment or education (action, preparation), whilst 50.4% of the survey responses indicated a low intention or belief in returning to employment or education (precontemplation, contemplation, unauthentic action) (Curtis et al., 2016; Mannock et al., 2002).
Our study indicates progress in validating a stage of change tool for use in jobseeker rehabilitation and support into employment. Data from the online, 12-item Psychological Assessment of Work Readiness (PAWR) tool suggest that the survey is a highly accurate predictor of a person's likelihood of entering employment or education. The data predict that precontemplation jobseekers are highly likely (77%) to remain long term unemployed. The URICA-VC's 12-items (4 questions for each of the three factors) identified distinct but correlated constructs (precontemplation, contemplation, action). The PAWR survey builds upon this and reinforces five distinct clusters--the most significant new finding being the cluster termed unauthentic action. It is essential to identify this distinct group in order to provide appropriate interventions to prevent the jobseeker cycling in and out of employment, and to enable the rehabilitation and employment industry to achieve more sustained employment outcomes. One might conjecture that unauthentic action jobseekers are not completely committed to re-entering employment or education, and are likely to drop out of interviews or employment early.
Notwithstanding the fact that unauthentic action jobseekers have conflicting beliefs in terms of re-entering employment, there might be a pygmalion effect for some members of this group. Once in an interview or employment, they actually fully commit to believing that they actually can hold the job down, and it isn't so daunting (Rosenthal, 1973).
Limitations of the Study
The issue remains that jobseekers may answer the survey in terms of what they think their advisors (or the benefits-paying government/insurer) want them to say. Nonetheless, the scoring algorithm appears effective in allowing for this as job placement data suggest that their stage of change is indeed an accurate predictor of returning to employment or education. Opposition by Littell & Girvin (2004) to the use of the stage of change model by child welfare workers could be extended to jobseekers. The fundamental consideration being that many causal issues in child welfare are not behavioral where the locus of control vests in the child or caregiver, but rather there are considerable external and uncontrollable adverse circumstances impacting upon that child's situation. This study was also unable to ascertain ethnicity, which needs to be addressed in further study.
The usefulness of a modified TTM for rehabilitation and employment services and government funders is significant. It was important to establish the application of the model to behaviors that aren't addictive (such as the initial TTM studies that addressed smoking, drug abuse etc.). Additionally, our straw poll of 42 unemployment advisors suggests that 72% of interventions with jobseekers are "action-oriented", such as resume writing, interview skills, vocational qualifications and job-search skills. Our data suggest that only 29% of jobseekers are in the action stage of change. This is a significant and costly mismatch of resources and interventions that could be further investigated.
Whilst the validity of the stages in predicting employment outcomes appears strong, further study is certainly required to address the efficacy of delivering stage-matched interventions. It is advised that rehabilitation counselors retain a flexible approach as there may be a range of jobseekers that do not "fit" the stage-matched interventions. A new study of 5,000 unemployed Australians, both with and without disabilities, is planned. Participants will undertake the PAWR survey, be referred to stage-matched interventions and employment outcomes and jobseeker feedback tracked. Application of the PAWR survey to specific unemployed and rehabilitation cohorts such as young people not in employment, education and training, those experiencing mental illness and so on, might prove valuable. Whilst the data assert that different attitudes to employment do indeed predict jobseeking outcomes, we are not sure exactly which psychological constructs are most relevant. For example, are jobseekers' levels of wellbeing, resilience or psychological flexibility correlated to their stage of change or successful employment outcomes? This understanding could help to refine more appropriate and effective interventions. An attitudinal assessment such as the PAWR is not considered by the researcher as a replacement for other government-administered assessment tools that account for extrinsic barriers to employment. Such barriers (which might include educational attainment, macro-economic conditions, driving license etc.) clearly have a significant impact upon employability. The PAWR assessment might, however, add a very relevant intrinsic component to those extrinsic assessments.
As a final thought, a specific pattern of data emerged from this study and the initial pilot studies that directly relate to considerations of "control" and "adversity" in behavioral change. We found that, consistently, one-third of those unemployed due to disability or considered furthest from employment (termed "Stream 4" by the Australian system) were in the proactive action or preparation stages of change, and two-thirds were in precontemplation/contemplation/unauthentic action. This figure mirrors learned helplessness studies across several animal species which consistently suggest that, in the face of repeated adversity over which one appears to have no control, two-thirds of participants learn helplessness (and conserve energy by not trying to escape the adversity) whilst one-third remain "optimistic" and continue to try to change their circumstances (Seligman, 1975). Investigation into the causation or correlation of this pattern, if confirmed, could have profound implications for rehabilitation and employment services. Four decades of research since the initial "learned helplessness" studies have uncovered interventions that counter learned helplessness and depression. Whether such wellbeing and resilience interventions are highly effective in supporting jobseekers to progress through the stages of change and into sustained employment is certainly worthy of further investigation.
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Table 1 Comparison ofSample Sample Random Data Eigenvalues 10 Random Eigenvalues Eigenvalues Data Eigenval ues Factor Initial Extracted Mean 95th Percentile 1 4.47 4.03 0.17 0.21 2 1.76 1.13 0.13 0.16 3 1.06 0.66 0.10 0.12 Note: Random eigenvalues were generated from random permutations of the raw dataset. Table 2 Item Loadings for 3 Factor Solution Factor Loadings Communality 1 2 3 Item 7 0.89 -0.02 -0.03 .78 Item 3 0.83 -0.08 -0.02 .71 Item 10 0.70 0.06 0.01 .49 Item 5 0.67 0.03 0.16 .58 Item 8 0.36 -0.04 0.20 .26 Item 9 0.09 0.60 -0.06 .34 Item 11 -0.16 0.57 -0.02 .42 Item 6 0.10 0.54 -0.01 .28 Item 2 -0.14 0.53 0.08 .33 Item 1 0.15 -0.10 0.68 .64 Item 4 0.26 -0.05 0.62 .65 Item 12 -0.05 0.03 0.53 .25 Eigenvalue 4.03 3.78 0.66 Cronbach [alpha] 0.85 0.65 0.70
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|Publication:||The Journal of Rehabilitation|
|Date:||Apr 1, 2017|
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