Journal of Management DevelopmentEmerald Article: An exploratory content analysis of situational leadershipMark A. Papworth, Derek Milne, George Boak

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To cite this document: Mark A. Papworth, Derek Milne, George Boak, (2009),"An exploratory content analysis of situational leadership", Journal of Management Development, Vol. 28 Iss: 7 pp. 593 - 606

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An exploratory content analysisof situational leadership

Mark A. PapworthNorth Tyneside Primary Care Trust, Wallsend Health Centre, Wallsend, UK

Derek MilneNewcastle University, Newcastle-upon-Tyne, UK, and

George BoakYork St John University, York, UK

Abstract

Purpose – Hersey and Blanchard’s situational leadership (SL) model is widely utilised, but it haslimited empirical support. This paper aims to investigate the model through content analysis of thetranscripts of supervision sessions.

Design/methodology/approach – Eight transcripts of successful supervision interviews aresubjected to in-depth content analysis to investigate the validity of aspects of the SL model, principallythat successful leadership interactions would vary systematically according to the level of superviseeexperience. The supervisees consist of a novice, four training therapists, and three post-graduatetherapist practitioners. Statistical analyses are undertaken to investigate fundamental, predicteddifferences between the speech behaviours associated with the different developmental levels of thesesupervisees.

Findings – The findings offer only partial support for the model. As predicted, an increased proportionof supervisor speech is observed in the supervision of increasingly less experienced therapists. However,the majority of the more specific speech behaviours associated with supervisee experience level are notin keeping with the model.

Originality/value – These results are consistent with the findings of other evaluations of the SLmodel. As the present results are based on a novel approach, this increases the plausibility of the claimthat SL lacks adequate empirical support. Areas of development and exploration are recommended, andlimits associated with the model’s utility are highlighted.

Keywords Leadership, Leadership development, Management effectiveness

Paper type Research paper

IntroductionHersey and Blanchard’s (1969; Hersey et al., 2001) situational leadership (SL) model isone of the most widely known leadership approaches (Bass, 1990; Northouse, 2004;Vecchio, 1987; Yukl, 2006). It has been a major factor in training and developmentprogrammes for over 400 of the Fortune 500 companies (Hersey et al., 2001). However,a literature search revealed only a handful of published, peer-reviewed studiesinvestigating the approach. These offered only mixed support for the model. Therefore,the present study is a contribution to this modest literature. It investigates the validityof the model through the content analysis of clinical supervision (CS) sessions. This isthe first time that either this methodology or this sample have been utilised to evaluatethe SL model.

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0262-1711.htm

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Received 20 October 2007Revised 9 June 2008

Accepted 5 July 2008

Journal of Management DevelopmentVol. 28 No. 7, 2009

pp. 593-606q Emerald Group Publishing Limited

0262-1711DOI 10.1108/02621710910972706

CS and leadershipThe functions of CS include the facilitation of learning, assurance of fitness to practiceand the maintenance of competence (Milne and James, 2000). The processes involved inCS usually include: the development of a supervisory relationship, educational and skilldevelopment activities, with the primary focus of supervision being outcomesassociated with the welfare of the patient (Townend et al., 2002).

As these definitions suggest, core commonalities exist between leadership and CS.Both occur in the context of a relationship, which usually has explicit differences interms of power and/or expertise, the expert/leader being at least partly responsible forthe actions of supervisee/follower. They both have an objective (and also an explicitagenda) of one individual influencing another. In this way, CS can be seen as an exampleof leadership. This is reflected in policy (NHS Management Executive, 1993) where CS isinterconnected with leadership; leaders providing supervision to subordinates and CS inturn facilitating leadership. These commonalities are also acknowledged withinleadership literature (House, 1996). As such, CS is an ideal context through which tostudy basic leadership processes.

Hersey and Blanchard’s SL modelHersey and Blanchard’s (1969; Hersey et al., 2001) SL model consists of threedimensions. Two of these are associated with leadership style: relationship behaviour(R) and task behaviour (T). These are used to produce four categories:

(1) guiding, telling or directing (S1: low R, high T);

(2) explaining, selling or persuading (S2: high R, high T);

(3) encouraging, participating or problem-solving (S3: high R, low T); and

(4) observing, delegating or monitoring (S4: low R, low T).

The model specifies that the most effective leadership style is determined by the“readiness level” a follower exhibits. The continuum of follower readiness (previouslytermed “maturity”) is similarly divided into four developmental levels, rangingthrough:

(1) they lack ability and also lack commitment or competence (R1);

(2) they lack ability but are motivated or confident (R2);

(3) they have ability but are not willing to utilise this (R3); through to

(4) they have the competence to perform and are committed/confident (R4).

Effectiveness is maximised by matching level of leadership style with followerreadiness. Therefore, an R1 follower level (e.g. an enthusiastic beginner) would respondbetter to “directing” leader behaviours (S1). As followers develop, the SL modelsuggests that they move from the low levels of readiness through to higher levels (jobpermitting), and the associated optimal leadership style should change accordingly.

The model has received criticism for evolving through a series of changes with noempirical basis, for having internal inconsistencies (two partially contradictory modelsare promoted simultaneously), few theoretical bases and little robust empirical support(Graeff, 1997; Nahavandi, 1997). A literature search revealed few published,peer-reviewed studies investigating the model. Of these, Vecchio and colleaguesinvestigated the model on several occasions, none of their results supporting the

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predicted three-factor interaction. Initially, Vecchio (1987) investigated the model usinghigh school teaching staff. Some support was offered in that matched supervision dyads(i.e. where leader and follower were synchronised according to the model) tended to havehigher performance ratings, perceived the relationships to be of higher quality andreported greater satisfaction with their supervisor. These findings were particularlyassociated with the low-readiness follower category. Using a nursing sample, Norris andVecchio (1992) did not find significant differences over supervision satisfaction betweenmatched and mismatched dyads. Fernandez and Vecchio (1997) investigated the modelwith university employees. Their results failed to support the theory for both a within-and across-jobs perspective, although analyses suggested that supervisory monitoringand consideration may have a positive impact for lower level employees, andconsideration for higher level employees. Vecchio et al.’s (2006) results were contrary tothat predicted by the model in that results were most robust in the high-readinesscategory, but in the opposite direction to that predicted.

Additional research also offers mixed support. In a sample of retail chainemployees, Goodson et al. (1989) found that the S2 and S3 styles resulted in the greatestlevel of follower satisfaction, regardless of the readiness level. Butler and Reese (1989)found that insurance agents, working for managers who preferred the S1 style,performed better than agents working for managers who preferred other styles.Blank et al. (1990) investigated the model with university staff and found that matcheddyads reported significantly higher levels of work satisfaction, but were not rated asbeing superior on supervisor appraisal of follower performance, or in providing higherratings of supervisor satisfaction. Cairns et al. (1998) used an executive sample andfound data which were in keeping with the model, but for the low-readiness levels only.Avery (2001) noted that managers rated themselves significantly more effective thantheir subordinates’ ratings indicated. They also exhibited clear preferences for usingthe S3 “supportive” SLII[1] style. Avery and Ryan (2002) used a qualitative approach toinvestigate SLII with managers. Participants reported that the model had face validity,was easy to use, intuitive, relevant, effective and respondents stated that they could“think of no better management tool”. Silverthorne (2000) compared “traditional”vs “adaptive” managers (i.e. who are flexible in their leadership style) and observedthat followers who had leaders with a more adaptable style exhibited a significantlylower level of absenteeism and staff turnover, as well as higher levels of profitability.In a similar study, Silverthorne and Wang (2001) found differences in the percentage ofadaptive leaders within companies rated as being more successful. These latter twostudies are of interest, but do not attempt to examine whether, according to the SL, thisadaptive style is synchronised with follower readiness levels.

Thus, whilst there has been no empirical support for the model’s three-factorstructure to date, leaders who are more flexible in their style appear to deliver greaterperformance. Additionally, some studies have indicated that the model may have valuefor low-readiness individuals where the telling style is advocated. Other studies have,contradictorily, suggested that the S1, S2 and S3 leadership styles are generallypreferable.

Study aimsThe present study aims to explore the relationship between leadership speech behaviourand supervisee experience though examination of successful supervision sessions.

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595

A content analytic approach is used which is a novel form of research in this field. Thismethodology is chosen, at least in part, to overcome some of the issues associated withSL evaluation to date. These include a fundamental contradiction between the model’sbehavioural basis and the evaluative approach used to date (self-report, throughquestionnaire surveys). As such, ambiguous outcomes have been noted (Fernandez andVecchio, 1997). Further, follower readiness is often determined by dividing the sampleinto quartiles (Goodson et al., 1989; Blank et al., 1990) or tertiles (Norris and Vecchio,1992; Vecchio et al., 2006), thus, making untested assumptions regarding the distributionof readiness level. Additionally, Blank et al. (1990) report serious issues associated withsome questionnaire measures.

MethodSampleTherapist supervision sessions were captured by video recording. The individualsinvited to record these supervision sessions were acknowledged experts, some beingattached to training centres of excellence. From an original sample of 12 tapes, eightwere selected because the supervisees clearly expressed high levels of satisfactionwithin the sessions and explicitly described having their needs/issues met by thesupervision. Thus, only successful supervision sessions were used to evaluate thehypotheses.

Follower readiness levels were systematically equated to levels of professionaldevelopment. Categorisation was synchronised through the indicators offered by themodel’s authors (Hersey and Blanchard, 1969; Hersey et al., 2001). Within aneducational context, Hersey and Blanchard (1969) previously allocated undergraduatesto R1, senior undergraduates and master’s students to R2/3 and PhD students to R4.Within our sample, professional development is delayed in comparison to their samplebecause over a UK therapist’s professional track, little if any client contact occurs atundergraduate level. Thus, R1 is equated to the novice, pre-professional training, butpost-graduate therapist. R2 is indicative of a therapist in training where individuals aremost rapidly developing skills and expertise. R3 equates to a recently qualified.Finally, R4 equates to the position of a more senior practitioner. As such, this sampleconsisted of one R1-, four R2- and three R3-level therapists whose needs andcharacteristic fit with the model. No R4-level practitioners participated; hence,the characteristics of the R4 follower sessions could not be investigated.

Recordings ranged in length from 12:18 to 49:06 minutes (Mean ¼ 39:04,SD ¼ 13:23). They were transcribed and analysed by the first author. Reliability ofthe coding system was established by the first author through coding the sameinterview on two occasions: once at the start of data coding and a second time at theend of data collection (six weeks later). Intra-rater reliability over 118 raw codingcategories was found to be highly significant (Pearson-Product Moment Correlation;r ¼ 0.95; p , 0.001).

AnalysisInterviews were subjected to content analysis which is a “distinctive approach toanalysis” that seeks to quantify the content of text in “a systematic and replicablemanner” (Bryman, 2004b, p. 181). Originally used for text analysis, it has beenfrequently applied to transcribed speech (Waltz et al., 1991).

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Interviews were transcribed and proof read. Coding categories associated with themanifest content (Kondracki et al., 2002) were defined through analysing a preliminaryselection of interview segments and by developing a coding dictionary in an iterativefashion[2]; testing and revising the data until no new categories emerged. All text wascoded into mutually exclusive categories. Examples of the categories are given inTable I. Interviews were content analysed by measuring the quantity of text associatedwith each category by using the Microsoft Word “word count” function. Somecategories were combined for the analyses to be in keeping with those offered byHersey et al. (2001). Investigative statistical analyses were undertaken (Weber, 1990) tocompare differences in interview profile and content over follower readiness levels.Finally, more detailed qualitative “micro-analysis” was undertaken over one interview.

ResultsAs is common practice, in order to allow cross-group comparisons, word counts areconverted to percentages of total words spoken within the session (Weber, 1990).Table II displays these summary percentages over the supervisee groups.

R1-level (novices)Hersey et al. (2001) suggest that R1-level supervisees will elicit a higher level of taskspeech behaviour from supervisors (who are predicted to adopt a “telling” style). Thiswill include instructing and controlling behaviour. The R1 staff member did elicit

Category Definition

Role play Real time rehearsal, supervisee involvedFormulate Link speech or behaviour in therapy to a global model of client’s

problem development or maintenanceEmpathise Use of expression which confers understanding of the others’ situation

(e.g. that must have been really difficult)Instruct Instructions of how to do implement techniquesExplain Explanation of the reasons why something is done; the usual process;

didactic educationProvide factual informationabout therapy

Report case material without interpretation; the content of therapyTable I.

Illustrative raw codingcategories and definitions

Novice therapist(R1; N ¼ 1)

Training therapist(R2; N ¼ 4)

Qualified therapist(R3; N ¼ 3)

Supervisor speech (all categories) 63.90 47.32 35.96Supervisor instruction 5.61 5.40 1.77Supervisor control 0 0.16 0.15Supervisor questioning of ability 5.61 2.31 0.32Supervisor explanation 27.74 8.78 17.63Supervisor positive feedback 0 0.60 0.21Supervisor reassurance 0 0.36 0.50Supervisee feedback requests 0 0 0.10

Table II.Percentage of selected

supervisor andsupervisee speech over

follower category

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597

higher levels of instruction-related speech from supervisors. She received marginallymore supervisor speech associated with instruction than R2 staff. However, our R1therapist did not elicit the higher level of control-focused speech than R2s. Levels ofthis category of speech were low across the sample. In fact, our R1 did not receive anyspeech of this nature from their supervisor.

R2-level (trainees)R2 supervisees should receive a greater degree of questioning from their supervisorthan R1 staff, in order to establish their ability level. Additionally, the SL modelpredicts that R2 staff will receive higher levels of explanation from supervisors than R1staff (Hersey et al., 2001). In fact, R2-level staff did not elicit higher levels of questioningfrom supervisors to establish their level of ability. Rather, our R1 participant receivedthe highest proportion of this questioning. Similarly, supervision of these individualsdid not include greater levels of supervisor explanation. R1 supervision contained thegreater amount of supervisor explanation, with R2 staff receiving the least.

R3-level (qualified staff)According to the model, R3 level staff will receive higher levels of positive feedbackand reassurance (with their supervisors using an “encouraging” style), as well as lowerlevels of instruction and explanation than that observed for R2 staff. These staff shouldmake more requests for feedback, the additional responsibility involved in the R2 to R3transition resulting in increased insecurity (Hersey et al., 2001). We found that thesupervision of R3 staff did not contain higher levels of more general positive feedbackthan for R2 participants. Levels of reassurance from supervisors were relatively lowacross all groups. However, a higher percentage of reassurance was directed towardsR3 staff than for R2s. The supervision of qualified staff contained the lowest level ofinstruction and explanatory speech, and whilst feedback requests from all staff wereminimal, R3s did request more feedback than R2 staff.

Whilst the small sample size negates statistical analysis of the magnitude of effectsover follower groups, it is possible to determine whether the vectors of these outcomes arestatistically supported. To establish whether leadership style is matched to the follower’sreadiness level, it was determined whether the nine model predictions noted above weresupported or not by the data. Predictions are associated with: R1 – instruction andcontrolling/limiting behaviours; R2 – questioning and explanation behaviours; R3 –encouragement, reassurance, instruction, explanation and reassurance requestingbehaviours. Of the nine predictions, the data has supported only four of them. Thisresult is not significant and thus, the direction of these differences between follower groupsin speech content might be attributable to chance alone (Binomial test, N ¼ 9, NS).

The ratio of supervisor to supervisee speech is predicted to reduce as the follower’sdevelopmental level rises, leadership style evolving from S1 instructing (dominance ofsupervisor role), S2 explaining (two-way dialogue), through to S3 (follower-led content;Hersey et al., 2001). We found that the supervision of R1 staff contained the highest ratio ofsupervisor to supervisee speech than the supervision for R2s. R2 staff’s supervision, inturn, contained a higher ratio of supervisor to supervisee speech than that for R3s. As such,a trend is visually evident from the data and differences between groups were found at ana-level of 10 per cent (Jonckheere-Terpstra Trend test; J ¼ 4, z ¼ 21.51, p ¼ 0.89).This level of significance is “suggestive” of a true effect (Curran-Everitt and Benos, 2004).

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Thus, the SL model appears to have some merit in that, in terms of the ratio ofsupervisor to supervisee speech, the expert supervisor appears to become less dominantwithin supervision as follower “maturity” increases. However, results associatedspecific speech behaviours and readiness level appear not to be significant. To explorethis latter finding further, a novel and more detailed level of analysis was undertaken.A “micro-level” approach was adopted which consisted of examining predominantspeech categories which occurred over time within the course of a single supervisionsession (the supervisee is R3-level and was previously included in the main analyses).

Micro-level analysisCategories of speech associated with one supervision session are distilled andtemporally displayed within Table III according to numbered turns in speaking whichoccurred between the supervisor and supervisee (“speech turns”; see [3] of construction).Within the 268 turns that took place within that meeting, from turns one to 49, thesupervisor appears to be primarily concerned with the defining the agenda for thesession. Over turns 58-77 the supervisor obtains more detailed information associatedwith the supervisee’s clinical intent, to allow more detailed diagnosis of need andagenda-setting to take place.

Over turns 82-245 the supervisor employs a variety of educational strategiesincluding the provision of instruction, explanation, demonstration, and use of feedbackand questioning; as well as methods of supporting the supervisee emotionally (such asthe giving of reassurance). These are behavioural indicators which, according toHersey et al. (2001), suggest that a variety of leadership styles (ranging from S1 to S3)are being employed within the session. Alternatively, an implication is that theirleadership categories are too limited to capture the variety of activity which occurs inorder to meet supervisee need in this context. In sum, the expert supervisor appears toemploy, in a responsive fashion within the session, a variety of cross-quadrantleadership behaviours in response to a variety of supervisee demands. In the latter partof the session (turns 250-267) the supervisor closes the meeting down by requestingfeedback regarding the supervision, checking out whether learning needs have beenmet and also giving some consideration to the agenda for the next session.

DiscussionHersey and Blanchard’s (1969; Hersey et al., 2001) SL model has received relatively littleempirical analysis or support. In previous evaluations, difficulties exist in terms ofmeasurement, control and design. The aim of this study was to investigate the validityand utility of SL, whilst partially overcoming these methodological issues through useof: analysis of speech content (behaviour), reasoned allocation of participants toreadiness levels, and a controlled evaluative context. A content analysis approach wasadopted to investigate the model, this approach previously being novel to this context.Whilst studies with a qualitative component are relatively rare in leadership research,they have offered important contributions to the field of leadership (Bryman, 2004a;Conger, 1998). Additionally, it is desirable that a variety of appropriate researchmethods are deployed within a field, to increase the certainty associated with commonfindings.

The present findings offer limited support for the SL model. As predicted by themodel, an increasing proportion of supervisee speech is contained in the supervision

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Table III.Summary contentof interview (no. 2) overthe entire session

Supe

rvis

orC

onte

nt o

ver

turn

s 10

to 1

1[3]

:re

ques

t cas

ein

form

atio

n, s

etag

enda

18 to

23:

Req

uest

cas

ein

form

atio

n,se

t age

nda,

ques

tion

topr

ovok

ein

sigh

t,su

mm

aris

e

29 to

37:

Ass

ess

need

s,ag

enda

set

,af

firm

supe

rvis

ion

limits

,su

mm

aris

e

41 to

49:

Ass

ess

need

s,ag

enda

set

,af

firm

supe

rvis

ion

limits

,su

mm

aris

e

58 to

59:

Req

uest

ther

apis

tin

tent

,su

mm

aris

e

72 to

77:

Req

uest

ther

apis

tin

tent

, age

nda

set,

sum

mar

ise

82 to

96:

Req

uest

for

clar

ific

atio

nan

d ca

se p

roce

ssda

ta,

dem

onst

rate

,re

flec

t, in

stru

ct,

expr

ess

insi

ght,

ques

tion

toes

tabl

ish

know

ledg

e/ab

ility

,su

mm

aris

e,pr

ovid

e po

sitiv

efe

edba

ck (

S1, S

3)

Supe

rvis

eeC

onte

nt o

ver

turn

s 1

to 1

6:Pr

ovid

e ca

sem

ater

ial

(inf

orm

atio

n an

dpr

oces

s),

requ

est

info

rmat

ion

and

tech

nica

lgu

idan

ce, r

epor

tm

ista

ke, e

xpre

ssdo

ubt/u

ncer

tain

ty

22 to

26:

Prov

ide

case

mat

eria

l(i

nfor

mat

ion

and

proc

ess)

35 to

40:

Ass

ess

need

s,se

t age

nda,

60 to

71:

Prov

ide

ther

apis

tin

tent

, pro

vide

case

mat

eria

l(i

nfor

mat

ion)

,re

port

on

tech

niqu

e us

e,ca

se f

orm

ulat

e

Sess

ion

prog

ress

(st

art)

(con

tinu

ed)JMD

28,7

600

Table III.

Supe

rvis

or10

0 to

118

:R

eque

st f

or c

ase

proc

ess

data

,ex

plai

n,in

stru

ct,

ques

tion

topr

ovok

ein

sigh

t, ca

sefo

rmul

ate,

prov

ide

prai

se(S

1, S

2, S

3)

127

to 1

34:

Exp

lain

,in

stru

ct,

ques

tion

topr

ovok

ein

sigh

t,re

assu

re(S

1, S

2, S

3)

144

to 2

12:

Req

uest

tech

niqu

e da

ta,

asse

ssne

eds,

red

irec

tco

nver

satio

n,ex

plai

n,de

mon

stra

te,

refl

ect,

inst

ruct

,qu

estio

n to

prov

oke

insi

ght,

theo

rise

,su

mm

aris

e,pr

ovid

epo

sitiv

efe

edba

ck(S

1, S

2, S

3)

220

to 2

21:

Que

stio

n to

prov

oke

insi

ght,

sum

mar

ise

250

to 2

67:

Req

uest

for

clar

ific

atio

n an

dsu

perv

isio

nfe

edba

ck,

ques

tion

toes

tabl

ish

know

ledg

e/ab

ility

,pr

ovid

e po

sitiv

efe

edba

ck, a

sses

sne

eds,

set

agen

da(n

ext s

essi

on),

sum

mar

ise

(S1,

S2,

S3)

Supe

rvis

ee11

7 to

126

:Pr

ovid

e ca

sem

ater

ial

(inf

orm

atio

n),

expr

ess

insi

ght,

disc

lose

are

aof

wea

knes

s

163

to16

5:Pr

ovid

e ca

sem

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ial

(pro

cess

),th

eori

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211

to 2

28:

Pinp

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tech

niqu

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ndou

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late

dgo

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req

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tech

nica

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-ref

lect

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theo

rise

,pr

ovid

epo

sitiv

esu

perv

isio

nfe

edba

ck, e

xpre

ssdo

ubt/u

ncer

tain

ty

246

to 2

47:

Self

-ref

lect

,pr

ovid

epo

sitiv

esu

perv

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nfe

edba

ck

253

to 2

68 (

end)

:Pi

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rela

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self

-dev

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135

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42:

Prov

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229

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45:

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feed

back

,af

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ion

limits

,ex

plai

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war

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prog

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(en

d)

Situationalleadership

601

of followers of higher readiness level. However, the majority of the specific predictionsarising from the model associated with “behavioural indicators” (as well as othermodel-related predictions) were not met. Whilst R1-level therapists elicited higher levelsof instruction from supervisors, the supervision did not contain the supervisor controlbehaviours which are associated with aspects of “closer” supervision. R2 therapists’supervision did not contain the higher levels of explanation and questioning predictedby the model. Similarly, whilst R3 therapists requested more feedback from supervisors,they did not appear to receive an increased proportion of feedback within theirsupervision in comparison to R2s. However, R3 staff did receive predicted higher levelsof reassurance and lower levels of instructional/explanatory supervisory speech.

These findings are in keeping with some extant findings. For instance, they indicatethat the model has some validity on a broader level, in that expert supervisors do tendto be less active within therapy with increasingly experienced supervisees. Theseresults echo those of Silverthorne (2000) and Silverthorne and Wang (2001), whosimilarly noted broader findings in regard to successful leadership and an “adaptive”style. However, more specific predictions associated with the model appear not to havebeen consistently supported in previous studies. A small cluster of studies have notedgreater predictive value of the model with low-readiness groups (Vecchio, 1987; Cairnset al., 1998). Our study’s results offer partial support for its utility for this group.

Of interest are findings which offer insight to an area which is debated. The SLmodel predicts a reduction of confidence and motivation as followers progress from R2to R3. This has been theoretically challenged (Graeff, 1983, 1997). However, our dataoffer support to this aspect of the model, R3 supervisees requesting greater levels offeedback (including reassurance) than other participants, and also receiving greaterlevels of reassurance from their supervisors. These findings might be interpreted asbeing symptomatic of a reduction in confidence. Indeed, the transition from trainingtherapist to qualified staff member involves significantly increased levels ofresponsibility.

Our results highlight evaluation issues and areas for possible further modelrefinement. An area of ambiguity is the model’s level of application. Hersey andBlanchard’s (1969) original description of the model entitled it as a “life cycle theory”.Using human development as an analogy, it described followers maturing graduallyover time. It implied that individuals follow a single pathway of developmentassociated with maturing within a job. The authors have since allocated less specificityto this aspect of the model: “Situational leadership is based on [. . .] the readiness levelthat the followers exhibit in performing a specific task, function, or objective”(Hersey et al., 2001, p. 172). This latter definition implies that individuals might havemultiple tracks of maturity associated with different job sub-components.

By way of illustration, see the example listed in Table IV. On the macro-level, thisexemplar job is categorised as “research psychologist”. It might encompass severalexo-level objectives and, in turn, each objective might have several functions. Forinstance, for the objective listed, these might include provision of research supervision,specific areas of expert support and the running departmental workshops (e.g. writingfor publication). A micro-level task associated with one such function might beprovision of expertise in the analysis of data. Clarification of the level of action of themodel is essential for its evaluation. For instance, this and previous evaluations appearto define readiness according to a macro-level distinction (e.g. how long a person has

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been in their post). However, whilst R3/4 level employees may have many transferablecompetencies, the taking on of new work objectives may necessitate S1/2 levels ofsupervision.

This classificatory model for levels of job specification also highlights an alternativehypothesis or area for further study. A “micro-level” focus for supervision may beappropriate for R1 level staff but as they develop, supervision may broaden toencompass a greater proportion of meso- and exo-level material rather than becomemore relationship-focused (at S2/S3). This might explain why research data tends tooffer more support over the R1/S1 dyad: micro-level task supervision inevitablyinvolving more instruction. This would also explain why a broader level of leaderadaptability has been found to be successful (Silverthorne, 2000; Silverthorne andWang, 2001). Similarly, this might account for the variety of leadership stylesfound in our micro-level of analysis, the interview participant being a R3 therapist whowould, according to this alternative hypothesis, be receiving supervision over a varietyof these job specificity levels, in a responsive fashion according to need.

An additional issue is the model’s neglect of other follower characteristics, such aspersonality. In specific contexts, this has been linked to increased performance(e.g. extroversion in sales and managerial jobs; Barrick and Mount, 1991). Also, whilstthe impact of follower personality upon leadership effectiveness is a topic which hasbeen largely neglected, some work suggests that it is a significant factor. For instance,Kandalla and Krishman (2004) observed that the personality factor “openness toexperience” enhanced transformational leadership, perhaps by encouraging leaders todemonstrate more transformational behaviours. As such, some stable, confoundingfactors could explain why within certain professions (which may attract individualswith specific personality features or learning preferences), specific resonant leadershipstyles are preferred, regardless of the follower’s readiness level (Butler and Reese, 1989;Goodson et al., 1989).

This study contains several methodological limitations. The modest sample sizeinhibited the use of statistical analysis and confines the degree of generalisation toother samples. The inclusion of only one R1 participant and no R4 therapists within thesample limited the study’s scope. Additionally, supervisors were supervising theirfollowers in the implementation of various therapy approaches. It is possible thatthese differing approaches involved supervision which necessitated a menu ofdifferent supervisory behaviours, a demand characteristic that may have biasedour findings. Finally, a self-selection bias may have arisen, through the use ofsupervisee volunteers. In sum, bearing these weaknesses in mind, we believe thatthe present study should be viewed as exploratory, raising some significant issues

Level Label Example

Macro-level Job Research psychologist attached to a clinicalpsychology team

Exo-level Objective To enable all clinical psychologists to becomeresearch-active

Meso-level Function Provision of research supervisionMicro-level Task Statistical analysis of specific data

Table IV.Level of job specificationwith associated example

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about the validity of the SL model. It is also hopefully illustrative, as it shows how anew methodology can be introduced into the field.

Our study has investigated Hersey and Blanchard’s (1969; Hersey et al., 2001) SLmodel and found limited support for broader associated principles, but more specificpredictions arising from the model and its “behavioural indicators” were not generallyupheld. These results are important in that they share similarities with results obtainedby others through use of a questionnaire approach. This synchrony over differingmethodologies adds robustness to these common findings. Issues associated with themodel have been highlighted, as well as areas in need of further exploration. Theseresults draw into question the extent of the utility of the SL model, which isparticularly important given the huge resources that are invested in its use.

Notes

1. A variant of the model was proposed by Blanchard (1985; SLII), where some concepts arere-labelled and adjustment is made to the parameters of the first three stages of followerdevelopment.

2. Coding dictionary available from the first author.

3. Speech turns 1-268: a speech turn consists of a word or series of words spoken continuouslyby one person. These are interchanged between speakers and make up conversation. Thissummary content table is calculated from the raw data by examining clusters of turns.Blocks of 50 or more words which are separated by two turns or less are included in one cellof the Table III. This sampling process is a means of, for summary/clarity purposes,allowing data associated with only larger sections of speech to be included, which form theprinciple focus of discussion.

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Corresponding authorMark A. Papworth can be contacted at: m.a.papworth@ncl.ac.uk

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